ACLY in ACC (n=79): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.657 1.929 0.227 1.237 3.007 2.898 0.004 ** Age 0.017 1.017 0.014 0.988 1.046 1.150 0.250 Gendermale 1.067 2.908 0.506 1.079 7.835 2.110 0.035 * RaceBlack 0.420 1.522 13163.844 0.000 Inf 0.000 1.000 RaceWhite 17.231 30443637.023 11333.485 0.000 Inf 0.002 0.999 Purity 2.216 9.169 2.088 0.153 548.716 1.061 0.289 Rsquare = 0.185 (max possible = 9.38e-01 ) Likelihood ratio test p = 4.13e-02 Wald test p = 1.08e-01 Score (logrank) test p = 6.62e-02 ACLY in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.283 1.326 0.136 1.017 1.730 2.084 0.037 * Age 0.033 1.033 0.009 1.016 1.051 3.855 0.000 *** Gendermale -0.224 0.799 0.180 0.561 1.138 -1.244 0.213 RaceBlack 0.564 1.757 0.454 0.722 4.275 1.242 0.214 RaceWhite 0.012 1.012 0.358 0.501 2.042 0.032 0.974 Stage2 14.731 2498998.302 1865.878 0.000 Inf 0.008 0.994 Stage3 15.143 3772893.103 1865.878 0.000 Inf 0.008 0.994 Stage4 15.648 6247807.605 1865.878 0.000 Inf 0.008 0.993 Purity -0.036 0.965 0.352 0.484 1.925 -0.102 0.919 Rsquare = 0.141 (max possible = 9.91e-01 ) Likelihood ratio test p = 2.97e-08 Wald test p = 1.26e-07 Score (logrank) test p = 4.64e-08 ACLY in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.182 1.200 0.141 0.911 1.581 1.294 0.196 Age 0.036 1.036 0.008 1.021 1.052 4.725 0.000 *** Gendermale 0.002 1.002 1.008 0.139 7.217 0.002 0.999 RaceBlack -0.013 0.987 0.619 0.293 3.324 -0.020 0.984 RaceWhite -0.303 0.738 0.599 0.228 2.390 -0.506 0.613 Stage2 0.396 1.486 0.304 0.820 2.695 1.305 0.192 Stage3 1.178 3.247 0.313 1.758 5.997 3.762 0.000 *** Stage4 2.558 12.905 0.390 6.008 27.720 6.557 0.000 *** Purity 0.433 1.541 0.427 0.668 3.556 1.014 0.311 Rsquare = 0.083 (max possible = 7.85e-01 ) Likelihood ratio test p = 1.15e-12 Wald test p = 4.95e-16 Score (logrank) test p = 4.83e-22 ACLY in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.401 1.493000e+00 0.381 0.708 3.150 1.053 0.292 Age 0.006 1.006000e+00 0.018 0.971 1.042 0.343 0.731 RaceBlack -0.864 4.210000e-01 1.105 0.048 3.678 -0.782 0.434 RaceWhite -1.212 2.980000e-01 1.109 0.034 2.618 -1.092 0.275 Stage2 18.733 1.366179e+08 6438.456 0.000 Inf 0.003 0.998 Stage3 20.185 5.839840e+08 6438.456 0.000 Inf 0.003 0.997 Stage4 21.545 2.274373e+09 6438.456 0.000 Inf 0.003 0.997 Purity 0.702 2.018000e+00 0.960 0.307 13.250 0.731 0.465 Rsquare = 0.163 (max possible = 7.18e-01 ) Likelihood ratio test p = 3.25e-04 Wald test p = 4.81e-03 Score (logrank) test p = 2.94e-06 ACLY in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.649 5.220000e-01 0.576 0.169 1.615 -1.127 0.260 Age 0.027 1.028000e+00 0.029 0.972 1.087 0.952 0.341 RaceBlack -3.381 3.400000e-02 1.860 0.001 1.304 -1.817 0.069 · RaceWhite -1.619 1.980000e-01 1.467 0.011 3.515 -1.103 0.270 Stage2 18.105 7.294080e+07 14829.386 0.000 Inf 0.001 0.999 Stage3 20.062 5.160891e+08 14829.386 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 3.657 3.872800e+01 2.378 0.366 4097.699 1.537 0.124 Rsquare = 0.384 (max possible = 6.68e-01 ) Likelihood ratio test p = 1.74e-04 Wald test p = 2.15e-01 Score (logrank) test p = 8.8e-15 ACLY in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.239 1.270 0.223 0.820 1.968 1.070 0.284 Age 0.049 1.050 0.012 1.026 1.075 4.111 0.000 *** Gendermale -15.545 0.000 3477.295 0.000 Inf -0.004 0.996 RaceBlack -0.520 0.595 1.176 0.059 5.960 -0.442 0.658 RaceWhite 0.019 1.019 1.053 0.129 8.029 0.018 0.986 Stage2 0.283 1.327 0.376 0.635 2.775 0.752 0.452 Stage3 0.854 2.350 0.394 1.086 5.085 2.169 0.030 * Stage4 2.155 8.625 0.592 2.705 27.504 3.642 0.000 *** Purity 0.175 1.191 0.630 0.347 4.091 0.277 0.782 Rsquare = 0.072 (max possible = 6.81e-01 ) Likelihood ratio test p = 6.52e-05 Wald test p = 1.21e-05 Score (logrank) test p = 2.35e-07 ACLY in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.174 1.190 0.383 0.561 2.523 0.453 0.651 Age 0.052 1.053 0.021 1.010 1.098 2.420 0.016 * Gendermale 1.110 3.034 1.143 0.323 28.486 0.971 0.331 RaceBlack 16.678 17504525.189 6431.640 0.000 Inf 0.003 0.998 RaceWhite 16.039 9239135.087 6431.640 0.000 Inf 0.002 0.998 Stage2 0.613 1.847 1.084 0.221 15.455 0.566 0.571 Stage3 1.553 4.725 1.065 0.586 38.127 1.458 0.145 Stage4 2.145 8.543 1.176 0.853 85.575 1.825 0.068 · Purity 0.997 2.709 1.322 0.203 36.158 0.754 0.451 Rsquare = 0.106 (max possible = 6.98e-01 ) Likelihood ratio test p = 3.93e-02 Wald test p = 6.81e-02 Score (logrank) test p = 2.26e-02 ACLY in CESC (n=306): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.556 1.744 0.183 1.218 2.497 3.037 0.002 ** Age 0.007 1.007 0.010 0.987 1.028 0.707 0.480 RaceBlack 1.115 3.049 1.068 0.376 24.749 1.044 0.297 RaceWhite 0.809 2.246 1.015 0.307 16.423 0.797 0.426 Purity 0.513 1.670 0.730 0.399 6.990 0.702 0.483 Rsquare = 0.052 (max possible = 8.91e-01 ) Likelihood ratio test p = 3.33e-02 Wald test p = 3.3e-02 Score (logrank) test p = 3.21e-02 ACLY in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.070 1.073 0.422 0.469 2.451 0.166 0.868 Age 0.018 1.018 0.022 0.976 1.062 0.827 0.408 Gendermale 0.265 1.303 0.567 0.429 3.956 0.467 0.641 RaceBlack -0.370 0.691 1.493 0.037 12.905 -0.247 0.805 RaceWhite -1.042 0.353 0.908 0.060 2.089 -1.148 0.251 Stage2 0.664 1.943 0.673 0.520 7.268 0.987 0.324 Stage3 -15.399 0.000 6968.601 0.000 Inf -0.002 0.998 Stage4 0.800 2.226 0.682 0.584 8.479 1.173 0.241 Purity 2.104 8.201 1.610 0.349 192.560 1.307 0.191 Rsquare = 0.212 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.78e-01 Wald test p = 6.45e-01 Score (logrank) test p = 4.81e-01 ACLY in COAD (n=458): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.288 0.750 0.272 0.440 1.277 -1.061 0.289 Age 0.024 1.024 0.012 1.001 1.047 2.062 0.039 * Gendermale 0.221 1.248 0.269 0.736 2.114 0.822 0.411 RaceBlack -0.451 0.637 0.835 0.124 3.271 -0.540 0.589 RaceWhite -0.496 0.609 0.780 0.132 2.809 -0.636 0.525 Stage2 0.187 1.206 0.563 0.400 3.635 0.332 0.740 Stage3 0.823 2.277 0.549 0.776 6.682 1.498 0.134 Stage4 1.956 7.068 0.556 2.377 21.016 3.517 0.000 *** Purity -0.185 0.831 0.600 0.256 2.693 -0.309 0.757 Rsquare = 0.113 (max possible = 9.04e-01 ) Likelihood ratio test p = 3.02e-04 Wald test p = 1.01e-04 Score (logrank) test p = 1.43e-05 ACLY in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 1.715 5.558 1.041 0.723 42.714 1.648 0.099 · Age -0.025 0.976 0.049 0.886 1.075 -0.498 0.619 Gendermale 0.326 1.385 1.110 0.157 12.197 0.294 0.769 RaceBlack 1.680 5.364 2.071 0.093 310.456 0.811 0.417 RaceWhite -3.433 0.032 1.752 0.001 1.001 -1.959 0.050 · Purity -3.469 0.031 2.755 0.000 6.897 -1.259 0.208 Rsquare = 0.213 (max possible = 5.58e-01 ) Likelihood ratio test p = 1.33e-01 Wald test p = 3.91e-01 Score (logrank) test p = 1.64e-01 ACLY in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.006 1.006 0.192 0.690 1.466 0.029 0.977 Age 0.010 1.010 0.014 0.982 1.038 0.681 0.496 Gendermale 0.482 1.619 0.538 0.564 4.649 0.896 0.370 RaceBlack 0.337 1.401 1.068 0.173 11.364 0.316 0.752 RaceWhite -0.079 0.924 0.447 0.385 2.218 -0.177 0.860 Stage2 0.697 2.007 0.654 0.557 7.227 1.066 0.286 Stage3 1.455 4.283 0.671 1.151 15.942 2.169 0.030 * Stage4 2.860 17.468 0.779 3.797 80.360 3.673 0.000 *** Purity 0.212 1.237 0.777 0.270 5.668 0.273 0.785 Rsquare = 0.141 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.15e-02 Wald test p = 5.34e-03 Score (logrank) test p = 4.44e-04 ACLY in GBM (n=153): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.306 1.358 0.204 0.911 2.026 1.502 0.133 Age 0.030 1.030 0.008 1.014 1.047 3.643 0.000 *** Gendermale -0.045 0.956 0.216 0.627 1.459 -0.206 0.836 RaceBlack 0.620 1.858 0.729 0.445 7.754 0.850 0.395 RaceWhite -0.132 0.876 0.617 0.261 2.937 -0.214 0.831 Purity -1.528 0.217 0.599 0.067 0.702 -2.551 0.011 * Rsquare = 0.144 (max possible = 9.98e-01 ) Likelihood ratio test p = 1.9e-03 Wald test p = 2.16e-03 Score (logrank) test p = 1.9e-03 ACLY in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.165 1.179 0.125 0.923 1.507 1.319 0.187 Age 0.021 1.021 0.008 1.006 1.037 2.792 0.005 ** Gendermale -0.266 0.767 0.173 0.547 1.075 -1.539 0.124 RaceBlack 0.107 1.113 0.559 0.372 3.329 0.192 0.848 RaceWhite -0.251 0.778 0.511 0.286 2.117 -0.492 0.623 Stage2 0.590 1.804 0.544 0.621 5.240 1.084 0.278 Stage3 0.860 2.364 0.537 0.826 6.767 1.604 0.109 Stage4 1.234 3.435 0.510 1.264 9.337 2.419 0.016 * Purity -0.053 0.948 0.365 0.464 1.938 -0.146 0.884 Rsquare = 0.073 (max possible = 9.89e-01 ) Likelihood ratio test p = 2.6e-04 Wald test p = 6.58e-04 Score (logrank) test p = 4.71e-04 ACLY in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.761 2.141000e+00 0.363 1.052 4.358 2.099 0.036 * Age 0.003 1.003000e+00 0.025 0.955 1.053 0.102 0.919 Gendermale -0.379 6.850000e-01 0.560 0.229 2.051 -0.676 0.499 RaceBlack 18.677 1.292104e+08 12865.294 0.000 Inf 0.001 0.999 RaceWhite 17.839 5.587272e+07 12865.294 0.000 Inf 0.001 0.999 Stage2 17.117 2.714549e+07 5623.426 0.000 Inf 0.003 0.998 Stage3 16.784 1.946406e+07 5623.426 0.000 Inf 0.003 0.998 Stage4 17.523 4.075604e+07 5623.426 0.000 Inf 0.003 0.998 Purity -1.433 2.390000e-01 1.101 0.028 2.066 -1.301 0.193 Rsquare = 0.153 (max possible = 9.17e-01 ) Likelihood ratio test p = 2.89e-01 Wald test p = 5.51e-01 Score (logrank) test p = 4.03e-01 ACLY in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.038 1.039 0.137 0.795 1.359 0.280 0.779 Age 0.027 1.027 0.008 1.010 1.044 3.169 0.002 ** Gendermale -0.288 0.750 0.183 0.524 1.074 -1.572 0.116 RaceBlack -0.022 0.979 0.564 0.324 2.957 -0.038 0.969 RaceWhite -0.395 0.674 0.512 0.247 1.839 -0.771 0.441 Stage2 0.360 1.434 0.554 0.484 4.249 0.651 0.515 Stage3 0.728 2.072 0.541 0.718 5.980 1.347 0.178 Stage4 1.141 3.129 0.512 1.146 8.543 2.226 0.026 * Purity 0.202 1.224 0.401 0.558 2.686 0.505 0.614 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.3e-04 Wald test p = 9.18e-04 Score (logrank) test p = 6.93e-04 ACLY in KICH (n=66): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ACLY 2.691 14.741 0.705 3.699 5.873600e+01 3.815 0.000 Age 0.051 1.053 0.028 0.996 1.113000e+00 1.812 0.070 Gendermale -1.726 0.178 0.748 0.041 7.700000e-01 -2.309 0.021 RaceBlack -15.959 0.000 3154.505 0.000 Inf -0.005 0.996 RaceWhite -1.492 0.225 1.169 0.023 2.221000e+00 -1.277 0.202 Stage2 14.187 1449748.915 0.865 266320.010 7.891904e+06 16.410 0.000 Stage3 15.519 5492711.011 0.792 1162972.172 2.594204e+07 19.593 0.000 Stage4 17.359 34586253.050 0.910 5807263.390 2.059850e+08 19.067 0.000 Purity 7.543 1886.832 3.986 0.764 4.662853e+06 1.892 0.058 signif ACLY *** Age · Gendermale * RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity · Rsquare = 0.427 (max possible = 6.71e-01 ) Likelihood ratio test p = 5.88e-05 Wald test p = 3.23e-219 Score (logrank) test p = 2.53e-09 ACLY in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.220 0.802 0.094 0.667 0.965 -2.341 0.019 * Age 0.033 1.033 0.008 1.017 1.050 3.916 0.000 *** Gendermale -0.171 0.842 0.189 0.581 1.221 -0.905 0.365 RaceBlack 0.164 1.178 1.055 0.149 9.321 0.155 0.877 RaceWhite 0.185 1.203 1.014 0.165 8.784 0.182 0.855 Stage2 0.164 1.179 0.346 0.598 2.325 0.475 0.635 Stage3 0.772 2.164 0.230 1.377 3.400 3.350 0.001 ** Stage4 1.677 5.349 0.218 3.492 8.195 7.705 0.000 *** Purity -0.081 0.922 0.365 0.451 1.885 -0.222 0.825 Rsquare = 0.183 (max possible = 9.65e-01 ) Likelihood ratio test p = 1.01e-15 Wald test p = 6.65e-16 Score (logrank) test p = 3.62e-19 ACLY in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.552 1.737 0.284 0.995 3.033 1.942 0.052 · Age 0.016 1.016 0.016 0.985 1.049 0.997 0.319 Gendermale -0.459 0.632 0.384 0.298 1.342 -1.194 0.232 RaceBlack -1.818 0.162 1.212 0.015 1.746 -1.500 0.134 RaceWhite -2.018 0.133 1.189 0.013 1.368 -1.697 0.090 · Stage2 -0.548 0.578 1.055 0.073 4.572 -0.520 0.603 Stage3 1.686 5.399 0.431 2.320 12.565 3.912 0.000 *** Stage4 2.693 14.772 0.513 5.407 40.360 5.251 0.000 *** Purity -0.387 0.679 0.748 0.157 2.942 -0.517 0.605 Rsquare = 0.178 (max possible = 7.58e-01 ) Likelihood ratio test p = 2.13e-06 Wald test p = 1.2e-06 Score (logrank) test p = 1.7e-10 ACLY in LAML (n=173): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.401 1.493 0.302 0.827 2.696 1.330 0.184 Age 0.039 1.040 0.008 1.023 1.056 4.782 0.000 *** Gendermale -0.182 0.834 0.215 0.547 1.271 -0.846 0.398 RaceBlack -0.212 0.809 1.109 0.092 7.106 -0.191 0.848 RaceWhite -0.645 0.525 1.019 0.071 3.862 -0.633 0.527 Rsquare = 0.166 (max possible = 9.96e-01 ) Likelihood ratio test p = 5.49e-05 Wald test p = 1.77e-04 Score (logrank) test p = 1.16e-04 ACLY in LGG (n=516): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.299 1.349 0.204 0.904 2.012 1.465 0.143 Age 0.061 1.063 0.008 1.047 1.079 7.951 0.000 *** Gendermale 0.131 1.140 0.197 0.775 1.676 0.667 0.505 RaceBlack 15.503 5407054.256 2080.276 0.000 Inf 0.007 0.994 RaceWhite 15.459 5173488.138 2080.276 0.000 Inf 0.007 0.994 Purity -1.165 0.312 0.424 0.136 0.716 -2.747 0.006 ** Rsquare = 0.14 (max possible = 9.07e-01 ) Likelihood ratio test p = 4.11e-13 Wald test p = 6.6e-13 Score (logrank) test p = 3.12e-14 ACLY in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.334 1.397 0.124 1.096 1.780 2.704 0.007 ** Age 0.013 1.013 0.008 0.997 1.029 1.550 0.121 Gendermale -0.065 0.937 0.230 0.596 1.471 -0.284 0.776 RaceBlack 0.875 2.398 0.491 0.916 6.279 1.781 0.075 · RaceWhite 0.030 1.031 0.238 0.646 1.644 0.127 0.899 Stage2 0.291 1.337 0.262 0.800 2.237 1.108 0.268 Stage3 0.867 2.380 0.236 1.499 3.777 3.677 0.000 *** Stage4 1.608 4.993 0.620 1.481 16.828 2.594 0.009 ** Purity 0.689 1.991 0.466 0.799 4.962 1.478 0.139 Rsquare = 0.106 (max possible = 9.66e-01 ) Likelihood ratio test p = 6.5e-05 Wald test p = 4.66e-05 Score (logrank) test p = 1.57e-05 ACLY in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.049 1.050 0.123 0.825 1.336 0.397 0.691 Age 0.007 1.007 0.009 0.990 1.025 0.797 0.426 Gendermale 0.006 1.006 0.171 0.719 1.408 0.037 0.971 RaceBlack 16.124 10061423.380 1881.961 0.000 Inf 0.009 0.993 RaceWhite 16.297 11957729.360 1881.961 0.000 Inf 0.009 0.993 Stage2 0.857 2.356 0.202 1.586 3.501 4.242 0.000 *** Stage3 0.997 2.711 0.222 1.755 4.188 4.497 0.000 *** Stage4 1.006 2.734 0.334 1.421 5.259 3.012 0.003 ** Purity 0.598 1.818 0.343 0.928 3.563 1.742 0.082 · Rsquare = 0.097 (max possible = 9.74e-01 ) Likelihood ratio test p = 2.25e-06 Wald test p = 2.94e-05 Score (logrank) test p = 3.43e-06 ACLY in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.156 1.169 0.126 0.912 1.497 1.232 0.218 Age 0.017 1.017 0.009 0.999 1.036 1.806 0.071 · Gendermale 0.400 1.491 0.195 1.017 2.186 2.047 0.041 * RaceBlack 0.023 1.024 0.601 0.315 3.324 0.039 0.969 RaceWhite -0.515 0.598 0.557 0.200 1.782 -0.923 0.356 Stage2 0.158 1.171 0.192 0.804 1.705 0.824 0.410 Stage3 0.604 1.830 0.214 1.203 2.785 2.822 0.005 ** Stage4 0.831 2.296 0.788 0.490 10.749 1.055 0.291 Purity -0.382 0.683 0.366 0.333 1.398 -1.044 0.297 Rsquare = 0.054 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.44e-02 Wald test p = 1.11e-02 Score (logrank) test p = 9.21e-03 ACLY in MESO (n=87): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.742 2.100 0.205 1.404 3.141 3.612 0.000 *** Age 0.015 1.016 0.016 0.984 1.048 0.947 0.343 Gendermale -0.467 0.627 0.338 0.323 1.216 -1.381 0.167 RaceBlack -1.209 0.298 1.570 0.014 6.479 -0.770 0.441 RaceWhite -1.108 0.330 1.064 0.041 2.659 -1.041 0.298 Stage2 -0.166 0.847 0.459 0.344 2.085 -0.360 0.719 Stage3 -0.140 0.870 0.411 0.388 1.947 -0.339 0.734 Stage4 -0.223 0.800 0.468 0.320 2.003 -0.477 0.634 Purity -0.504 0.604 0.565 0.200 1.828 -0.892 0.372 Rsquare = 0.197 (max possible = 9.98e-01 ) Likelihood ratio test p = 2.85e-02 Wald test p = 3.8e-02 Score (logrank) test p = 3.09e-02 ACLY in OV (n=303): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.230 1.258 0.152 0.934 1.695 1.510 0.131 Age 0.037 1.038 0.008 1.021 1.054 4.533 0.000 *** RaceBlack -0.112 0.894 0.578 0.288 2.775 -0.193 0.847 RaceWhite -0.236 0.790 0.519 0.286 2.182 -0.456 0.649 Purity -0.417 0.659 0.668 0.178 2.439 -0.625 0.532 Rsquare = 0.09 (max possible = 9.97e-01 ) Likelihood ratio test p = 4.31e-04 Wald test p = 3.83e-04 Score (logrank) test p = 3.05e-04 ACLY in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.111 0.895 0.190 0.617 1.298 -0.585 0.558 Age 0.020 1.021 0.011 0.998 1.043 1.803 0.071 · Gendermale -0.237 0.789 0.220 0.512 1.214 -1.079 0.280 RaceBlack 0.050 1.052 0.748 0.243 4.556 0.067 0.946 RaceWhite 0.405 1.499 0.479 0.586 3.835 0.844 0.399 Stage2 0.578 1.782 0.444 0.747 4.251 1.302 0.193 Stage3 -0.342 0.710 1.105 0.081 6.193 -0.310 0.757 Stage4 0.238 1.268 0.824 0.252 6.373 0.289 0.773 Purity -0.701 0.496 0.413 0.221 1.115 -1.697 0.090 · Rsquare = 0.09 (max possible = 9.91e-01 ) Likelihood ratio test p = 7.52e-02 Wald test p = 1.1e-01 Score (logrank) test p = 1.05e-01 ACLY in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.665 1.944 0.568 0.638 5.918 1.170 0.242 Age 0.038 1.039 0.028 0.984 1.098 1.368 0.171 Gendermale 1.245 3.474 0.906 0.589 20.500 1.375 0.169 RaceBlack -0.405 0.667 19743.458 0.000 Inf 0.000 1.000 RaceWhite 16.994 24013884.865 15280.152 0.000 Inf 0.001 0.999 Purity 5.689 295.482 3.432 0.354 246389.861 1.658 0.097 · Rsquare = 0.063 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.01e-01 Wald test p = 2.62e-01 Score (logrank) test p = 1.89e-01 ACLY in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.812 2.252 0.541 0.780 6.500 1.501 0.133 Age 0.020 1.020 0.055 0.916 1.136 0.366 0.715 RaceBlack 15.240 4157273.652 6747.209 0.000 Inf 0.002 0.998 RaceWhite 16.378 12969401.399 6747.209 0.000 Inf 0.002 0.998 Purity 0.899 2.458 1.361 0.171 35.390 0.661 0.509 Rsquare = 0.013 (max possible = 1.83e-01 ) Likelihood ratio test p = 3.76e-01 Wald test p = 5.17e-01 Score (logrank) test p = 4.47e-01 ACLY in READ (n=166): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.051 0.951 0.547 0.325 2.778 -0.092 0.926 Age 0.108 1.114 0.046 1.018 1.220 2.347 0.019 * Gendermale -0.346 0.707 0.692 0.182 2.747 -0.500 0.617 RaceBlack 13.512 738474.566 10451.923 0.000 Inf 0.001 0.999 RaceWhite 12.498 267886.769 10451.923 0.000 Inf 0.001 0.999 Stage2 -1.855 0.156 1.255 0.013 1.831 -1.478 0.139 Stage3 -0.504 0.604 0.938 0.096 3.798 -0.537 0.591 Stage4 -0.157 0.855 0.960 0.130 5.607 -0.163 0.870 Purity 0.081 1.085 1.440 0.065 18.240 0.056 0.955 Rsquare = 0.209 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.69e-02 Wald test p = 2.31e-01 Score (logrank) test p = 4.17e-02 ACLY in SARC (n=260): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.404 1.498 0.167 1.081 2.076 2.426 0.015 * Age 0.020 1.020 0.008 1.004 1.037 2.417 0.016 * Gendermale -0.052 0.950 0.223 0.613 1.470 -0.232 0.816 RaceBlack 0.019 1.020 1.089 0.121 8.615 0.018 0.986 RaceWhite -0.359 0.698 1.022 0.094 5.173 -0.352 0.725 Purity 1.004 2.729 0.588 0.862 8.632 1.708 0.088 · Rsquare = 0.067 (max possible = 9.75e-01 ) Likelihood ratio test p = 1.35e-02 Wald test p = 1.98e-02 Score (logrank) test p = 1.9e-02 ACLY in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.083 0.920 0.126 0.719 1.179 -0.657 0.511 Age 0.019 1.019 0.005 1.009 1.029 3.584 0.000 *** Gendermale -0.053 0.948 0.157 0.697 1.291 -0.337 0.736 RaceWhite -1.277 0.279 0.402 0.127 0.613 -3.179 0.001 ** Stage2 0.283 1.327 0.219 0.864 2.038 1.293 0.196 Stage3 0.607 1.836 0.204 1.230 2.739 2.975 0.003 ** Stage4 1.342 3.826 0.352 1.920 7.622 3.816 0.000 *** Purity 1.048 2.852 0.342 1.458 5.577 3.061 0.002 ** Rsquare = 0.124 (max possible = 9.92e-01 ) Likelihood ratio test p = 1.85e-08 Wald test p = 9.67e-09 Score (logrank) test p = 1.17e-09 ACLY in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.334 1.397000e+00 0.331 0.730 2.673 1.009 0.313 Age 0.012 1.012000e+00 0.016 0.981 1.044 0.771 0.441 Gendermale 0.177 1.194000e+00 0.434 0.510 2.794 0.408 0.684 RaceWhite -1.198 3.020000e-01 0.631 0.088 1.040 -1.898 0.058 · Stage2 17.504 3.999103e+07 6234.262 0.000 Inf 0.003 0.998 Stage3 18.077 7.094255e+07 6234.262 0.000 Inf 0.003 0.998 Stage4 20.139 5.576115e+08 6234.262 0.000 Inf 0.003 0.997 Purity -0.172 8.420000e-01 1.036 0.111 6.409 -0.166 0.868 Rsquare = 0.156 (max possible = 8.69e-01 ) Likelihood ratio test p = 4.28e-02 Wald test p = 4.21e-02 Score (logrank) test p = 3.13e-03 ACLY in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.103 0.902 0.142 0.683 1.192 -0.727 0.467 Age 0.021 1.021 0.006 1.010 1.033 3.703 0.000 *** Gendermale -0.065 0.937 0.172 0.668 1.313 -0.379 0.705 RaceWhite -1.038 0.354 0.600 0.109 1.149 -1.729 0.084 · Stage2 0.167 1.181 0.231 0.751 1.859 0.721 0.471 Stage3 0.560 1.750 0.209 1.162 2.636 2.676 0.007 ** Stage4 1.118 3.057 0.400 1.396 6.694 2.795 0.005 ** Purity 1.172 3.228 0.371 1.560 6.679 3.158 0.002 ** Rsquare = 0.135 (max possible = 9.95e-01 ) Likelihood ratio test p = 8.78e-07 Wald test p = 1.35e-06 Score (logrank) test p = 5.14e-07 ACLY in STAD (n=415): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.115 1.122 0.125 0.879 1.433 0.923 0.356 Age 0.026 1.027 0.010 1.006 1.047 2.566 0.010 * Gendermale 0.089 1.093 0.211 0.723 1.653 0.421 0.674 RaceBlack 0.213 1.237 0.451 0.511 2.993 0.472 0.637 RaceWhite 0.076 1.079 0.245 0.668 1.742 0.309 0.757 Stage2 0.475 1.608 0.390 0.748 3.456 1.217 0.224 Stage3 0.896 2.451 0.365 1.199 5.009 2.458 0.014 * Stage4 1.335 3.801 0.504 1.414 10.214 2.647 0.008 ** Purity -0.574 0.563 0.382 0.266 1.190 -1.505 0.132 Rsquare = 0.072 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.03e-02 Wald test p = 1.4e-02 Score (logrank) test p = 1.15e-02 ACLY in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -5.528 4.000000e-03 41577.678 0 Inf 0.000 1.000 Age -1.747 1.740000e-01 1681.316 0 Inf -0.001 0.999 RaceBlack -1.517 2.190000e-01 12741337.961 0 Inf 0.000 1.000 RaceWhite -49.699 0.000000e+00 21166074.604 0 Inf 0.000 1.000 Stage2 -0.054 9.480000e-01 41927.041 0 Inf 0.000 1.000 Stage3 23.061 1.035346e+10 120885.231 0 Inf 0.000 1.000 Purity 27.805 1.189775e+12 199103.045 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.11e-03 ACLY in THCA (n=509): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.749 2.115 0.484 0.819 5.461 1.547 0.122 Age 0.146 1.157 0.028 1.096 1.222 5.274 0.000 *** Gendermale -0.257 0.773 0.654 0.214 2.788 -0.393 0.694 RaceBlack 17.563 42411634.658 9172.139 0.000 Inf 0.002 0.998 RaceWhite 17.383 35428149.560 9172.139 0.000 Inf 0.002 0.998 Stage2 0.701 2.015 1.156 0.209 19.432 0.606 0.545 Stage3 0.374 1.454 0.862 0.269 7.871 0.434 0.664 Stage4 1.888 6.605 0.992 0.946 46.132 1.904 0.057 · Purity 2.421 11.254 1.121 1.252 101.201 2.160 0.031 * Rsquare = 0.155 (max possible = 3.47e-01 ) Likelihood ratio test p = 7.81e-11 Wald test p = 5.2e-05 Score (logrank) test p = 3.96e-11 ACLY in THYM (n=120): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.825 0.438 0.463 0.177 1.087 -1.780 0.075 · Age 0.059 1.061 0.036 0.990 1.138 1.668 0.095 · Gendermale -0.172 0.842 0.765 0.188 3.775 -0.224 0.822 RaceBlack -16.505 0.000 11507.462 0.000 Inf -0.001 0.999 RaceWhite 0.361 1.435 1.095 0.168 12.264 0.330 0.742 Purity 0.434 1.544 1.152 0.161 14.768 0.377 0.706 Rsquare = 0.069 (max possible = 4.51e-01 ) Likelihood ratio test p = 2.31e-01 Wald test p = 3.76e-01 Score (logrank) test p = 2.26e-01 ACLY in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.001 1.001 0.192 0.687 1.458 0.005 0.996 Age 0.050 1.051 0.016 1.019 1.084 3.163 0.002 ** RaceBlack -0.414 0.661 0.794 0.140 3.131 -0.521 0.602 RaceWhite -0.526 0.591 0.745 0.137 2.546 -0.706 0.480 Purity 0.447 1.563 0.646 0.441 5.542 0.691 0.489 Rsquare = 0.038 (max possible = 7.81e-01 ) Likelihood ratio test p = 5.03e-02 Wald test p = 5.93e-02 Score (logrank) test p = 5.77e-02 ACLY in UCS (n=57): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY -0.065 0.937 0.238 0.588 1.494 -0.272 0.785 Age 0.044 1.045 0.024 0.997 1.096 1.824 0.068 · RaceBlack 17.579 43103338.717 6475.034 0.000 Inf 0.003 0.998 RaceWhite 17.843 56141332.401 6475.034 0.000 Inf 0.003 0.998 Purity -0.902 0.406 1.064 0.050 3.267 -0.848 0.397 Rsquare = 0.12 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.47e-01 Wald test p = 3.55e-01 Score (logrank) test p = 2.62e-01 ACLY in UVM (n=80): Model: Surv(OS, EVENT) ~ `ACLY` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACLY 0.968 2.633 0.421 1.155 6.004 2.302 0.021 * Age 0.045 1.046 0.019 1.008 1.086 2.394 0.017 * Gendermale 0.398 1.489 0.479 0.582 3.808 0.830 0.406 Stage3 0.189 1.208 0.508 0.447 3.266 0.372 0.710 Stage4 4.045 57.105 1.215 5.277 617.970 3.329 0.001 ** Purity 1.873 6.506 1.293 0.516 82.032 1.448 0.148 Rsquare = 0.308 (max possible = 8.72e-01 ) Likelihood ratio test p = 8.11e-05 Wald test p = 1.56e-03 Score (logrank) test p = 6.61e-10 ACACA in ACC (n=79): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.566 1.762 0.302 0.974 3.186 1.873 0.061 · Age 0.009 1.009 0.014 0.982 1.036 0.653 0.514 Gendermale 0.613 1.846 0.436 0.786 4.336 1.408 0.159 RaceBlack 0.164 1.178 12584.931 0.000 Inf 0.000 1.000 RaceWhite 16.762 19038013.403 10762.468 0.000 Inf 0.002 0.999 Purity 1.975 7.206 2.345 0.073 713.884 0.842 0.400 Rsquare = 0.119 (max possible = 9.38e-01 ) Likelihood ratio test p = 2.31e-01 Wald test p = 4.23e-01 Score (logrank) test p = 2.8e-01 ACACA in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.239 1.270 0.138 0.969 1.665 1.732 0.083 · Age 0.032 1.032 0.009 1.015 1.050 3.722 0.000 *** Gendermale -0.227 0.797 0.181 0.558 1.137 -1.254 0.210 RaceBlack 0.689 1.993 0.447 0.829 4.787 1.542 0.123 RaceWhite 0.099 1.105 0.355 0.551 2.214 0.280 0.779 Stage2 14.352 1710549.399 1899.731 0.000 Inf 0.008 0.994 Stage3 14.815 2716107.705 1899.731 0.000 Inf 0.008 0.994 Stage4 15.299 4407040.439 1899.731 0.000 Inf 0.008 0.994 Purity -0.013 0.987 0.352 0.495 1.967 -0.038 0.970 Rsquare = 0.138 (max possible = 9.91e-01 ) Likelihood ratio test p = 5.5e-08 Wald test p = 2.54e-07 Score (logrank) test p = 7.24e-08 ACACA in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.047 1.048 0.115 0.837 1.314 0.411 0.681 Age 0.036 1.037 0.008 1.021 1.052 4.734 0.000 *** Gendermale 0.000 1.000 1.012 0.138 7.277 0.000 1.000 RaceBlack -0.012 0.988 0.620 0.293 3.330 -0.019 0.985 RaceWhite -0.236 0.790 0.597 0.245 2.545 -0.395 0.693 Stage2 0.411 1.508 0.304 0.832 2.736 1.353 0.176 Stage3 1.194 3.300 0.313 1.786 6.096 3.812 0.000 *** Stage4 2.510 12.299 0.389 5.741 26.349 6.456 0.000 *** Purity 0.492 1.635 0.425 0.711 3.760 1.158 0.247 Rsquare = 0.081 (max possible = 7.85e-01 ) Likelihood ratio test p = 2.3e-12 Wald test p = 6.72e-16 Score (logrank) test p = 8.29e-22 ACACA in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.038 1.038000e+00 0.376 0.497 2.170 0.100 0.920 Age 0.010 1.010000e+00 0.018 0.975 1.047 0.554 0.579 RaceBlack -0.917 4.000000e-01 1.108 0.046 3.504 -0.828 0.408 RaceWhite -1.246 2.880000e-01 1.118 0.032 2.574 -1.114 0.265 Stage2 18.685 1.303182e+08 6475.224 0.000 Inf 0.003 0.998 Stage3 20.109 5.407898e+08 6475.224 0.000 Inf 0.003 0.998 Stage4 21.412 1.991051e+09 6475.224 0.000 Inf 0.003 0.997 Purity 0.742 2.101000e+00 0.967 0.316 13.973 0.768 0.443 Rsquare = 0.157 (max possible = 7.18e-01 ) Likelihood ratio test p = 5.2e-04 Wald test p = 7.14e-03 Score (logrank) test p = 4.73e-06 ACACA in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.337 7.140000e-01 0.383 0.337 1.513 -0.880 0.379 Age 0.021 1.021000e+00 0.030 0.963 1.084 0.699 0.484 RaceBlack -3.218 4.000000e-02 1.880 0.001 1.594 -1.712 0.087 · RaceWhite -1.800 1.650000e-01 1.473 0.009 2.965 -1.222 0.222 Stage2 18.276 8.654328e+07 15410.970 0.000 Inf 0.001 0.999 Stage3 20.002 4.860670e+08 15410.970 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 2.921 1.855500e+01 2.263 0.220 1564.795 1.291 0.197 Rsquare = 0.379 (max possible = 6.68e-01 ) Likelihood ratio test p = 2.09e-04 Wald test p = 2.73e-01 Score (logrank) test p = 1.08e-14 ACACA in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.041 1.041 0.204 0.698 1.553 0.199 0.842 Age 0.049 1.050 0.012 1.026 1.075 4.083 0.000 *** Gendermale -15.409 0.000 3455.656 0.000 Inf -0.004 0.996 RaceBlack -0.457 0.633 1.180 0.063 6.392 -0.387 0.699 RaceWhite 0.217 1.243 1.042 0.161 9.576 0.209 0.835 Stage2 0.328 1.388 0.374 0.667 2.889 0.876 0.381 Stage3 0.874 2.396 0.398 1.099 5.223 2.197 0.028 * Stage4 2.113 8.273 0.623 2.441 28.035 3.393 0.001 ** Purity 0.282 1.326 0.627 0.388 4.527 0.450 0.653 Rsquare = 0.07 (max possible = 6.81e-01 ) Likelihood ratio test p = 1.03e-04 Wald test p = 1.9e-05 Score (logrank) test p = 3.94e-07 ACACA in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.162 1.176 0.290 0.667 2.075 0.560 0.575 Age 0.051 1.052 0.021 1.009 1.097 2.394 0.017 * Gendermale 0.903 2.467 1.121 0.274 22.197 0.806 0.421 RaceBlack 16.652 17061771.809 6386.559 0.000 Inf 0.003 0.998 RaceWhite 16.060 9433830.772 6386.559 0.000 Inf 0.003 0.998 Stage2 0.677 1.968 1.072 0.241 16.089 0.631 0.528 Stage3 1.598 4.945 1.060 0.619 39.514 1.507 0.132 Stage4 2.196 8.991 1.181 0.888 91.058 1.859 0.063 · Purity 1.232 3.429 1.375 0.232 50.722 0.896 0.370 Rsquare = 0.107 (max possible = 6.98e-01 ) Likelihood ratio test p = 3.79e-02 Wald test p = 7.49e-02 Score (logrank) test p = 2.41e-02 ACACA in CESC (n=306): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.420 1.521 0.227 0.976 2.372 1.851 0.064 · Age 0.008 1.008 0.010 0.989 1.028 0.834 0.404 RaceBlack 1.027 2.792 1.068 0.344 22.647 0.961 0.336 RaceWhite 0.848 2.334 1.015 0.319 17.077 0.835 0.404 Purity 0.427 1.533 0.745 0.356 6.601 0.573 0.567 Rsquare = 0.029 (max possible = 8.91e-01 ) Likelihood ratio test p = 2.5e-01 Wald test p = 2.68e-01 Score (logrank) test p = 2.57e-01 ACACA in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.217 1.243 0.452 0.513 3.011 0.481 0.630 Age 0.019 1.019 0.022 0.976 1.063 0.845 0.398 Gendermale 0.184 1.202 0.580 0.386 3.745 0.318 0.751 RaceBlack -0.397 0.672 1.511 0.035 12.985 -0.263 0.793 RaceWhite -0.983 0.374 0.919 0.062 2.268 -1.069 0.285 Stage2 0.689 1.991 0.678 0.527 7.525 1.015 0.310 Stage3 -15.065 0.000 6946.011 0.000 Inf -0.002 0.998 Stage4 0.805 2.237 0.670 0.601 8.323 1.201 0.230 Purity 2.304 10.010 1.696 0.360 277.977 1.358 0.174 Rsquare = 0.216 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.58e-01 Wald test p = 6.54e-01 Score (logrank) test p = 4.82e-01 ACACA in COAD (n=458): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.162 0.851 0.240 0.532 1.360 -0.676 0.499 Age 0.024 1.024 0.011 1.001 1.047 2.075 0.038 * Gendermale 0.222 1.249 0.269 0.737 2.115 0.826 0.409 RaceBlack -0.418 0.658 0.829 0.130 3.344 -0.504 0.614 RaceWhite -0.470 0.625 0.777 0.136 2.865 -0.605 0.545 Stage2 0.182 1.199 0.564 0.397 3.624 0.322 0.747 Stage3 0.792 2.209 0.550 0.752 6.487 1.442 0.149 Stage4 1.911 6.762 0.554 2.285 20.010 3.453 0.001 ** Purity -0.188 0.828 0.599 0.256 2.679 -0.314 0.753 Rsquare = 0.111 (max possible = 9.04e-01 ) Likelihood ratio test p = 3.89e-04 Wald test p = 1.35e-04 Score (logrank) test p = 1.98e-05 ACACA in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 2.676 14.526 1.558 0.686 307.757 1.718 0.086 · Age -0.014 0.986 0.047 0.899 1.082 -0.289 0.773 Gendermale 0.820 2.271 1.063 0.283 18.238 0.772 0.440 RaceBlack 2.264 9.624 2.290 0.108 856.326 0.989 0.323 RaceWhite -3.199 0.041 1.620 0.002 0.977 -1.974 0.048 * Purity -4.395 0.012 2.986 0.000 4.295 -1.472 0.141 Rsquare = 0.22 (max possible = 5.58e-01 ) Likelihood ratio test p = 1.17e-01 Wald test p = 4.6e-01 Score (logrank) test p = 1.66e-01 ACACA in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.275 0.760 0.246 0.469 1.232 -1.114 0.265 Age 0.006 1.006 0.014 0.978 1.035 0.422 0.673 Gendermale 0.450 1.568 0.538 0.546 4.503 0.837 0.403 RaceBlack 0.475 1.608 1.077 0.195 13.277 0.441 0.659 RaceWhite -0.145 0.865 0.448 0.359 2.081 -0.324 0.746 Stage2 0.645 1.906 0.656 0.527 6.898 0.983 0.326 Stage3 1.406 4.081 0.673 1.092 15.248 2.091 0.037 * Stage4 2.960 19.303 0.776 4.219 88.305 3.816 0.000 *** Purity 0.222 1.249 0.779 0.271 5.748 0.285 0.775 Rsquare = 0.149 (max possible = 9.32e-01 ) Likelihood ratio test p = 7.4e-03 Wald test p = 3.37e-03 Score (logrank) test p = 2.72e-04 ACACA in GBM (n=153): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.116 1.123 0.150 0.837 1.508 0.774 0.439 Age 0.030 1.030 0.008 1.014 1.047 3.657 0.000 *** Gendermale -0.073 0.930 0.215 0.610 1.417 -0.338 0.735 RaceBlack 0.531 1.700 0.727 0.409 7.070 0.730 0.466 RaceWhite -0.218 0.804 0.615 0.241 2.684 -0.355 0.723 Purity -1.263 0.283 0.575 0.092 0.873 -2.195 0.028 * Rsquare = 0.133 (max possible = 9.98e-01 ) Likelihood ratio test p = 3.76e-03 Wald test p = 4.92e-03 Score (logrank) test p = 4.34e-03 ACACA in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.009 1.009 0.136 0.774 1.317 0.067 0.946 Age 0.022 1.022 0.008 1.007 1.038 2.888 0.004 ** Gendermale -0.250 0.779 0.172 0.556 1.092 -1.451 0.147 RaceBlack 0.132 1.141 0.559 0.381 3.416 0.236 0.813 RaceWhite -0.248 0.780 0.511 0.286 2.125 -0.486 0.627 Stage2 0.617 1.853 0.544 0.638 5.377 1.134 0.257 Stage3 0.853 2.346 0.537 0.818 6.726 1.587 0.113 Stage4 1.254 3.505 0.510 1.290 9.522 2.460 0.014 * Purity -0.049 0.952 0.367 0.464 1.953 -0.135 0.893 Rsquare = 0.069 (max possible = 9.89e-01 ) Likelihood ratio test p = 5.26e-04 Wald test p = 1.38e-03 Score (logrank) test p = 1.01e-03 ACACA in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.214 1.238000e+00 0.499 0.466 3.293 0.428 0.669 Age 0.009 1.009000e+00 0.025 0.961 1.061 0.371 0.711 Gendermale -0.195 8.230000e-01 0.549 0.281 2.415 -0.354 0.723 RaceBlack 18.855 1.544059e+08 12049.228 0.000 Inf 0.002 0.999 RaceWhite 18.084 7.141009e+07 12049.228 0.000 Inf 0.002 0.999 Stage2 17.414 3.652505e+07 5308.996 0.000 Inf 0.003 0.997 Stage3 16.638 1.681182e+07 5308.996 0.000 Inf 0.003 0.997 Stage4 17.501 3.987034e+07 5308.996 0.000 Inf 0.003 0.997 Purity -1.672 1.880000e-01 1.105 0.022 1.638 -1.513 0.130 Rsquare = 0.09 (max possible = 9.17e-01 ) Likelihood ratio test p = 7.29e-01 Wald test p = 9.48e-01 Score (logrank) test p = 8.56e-01 ACACA in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.025 0.976 0.142 0.738 1.290 -0.172 0.863 Age 0.027 1.027 0.008 1.010 1.044 3.194 0.001 ** Gendermale -0.283 0.753 0.183 0.526 1.078 -1.551 0.121 RaceBlack -0.014 0.987 0.564 0.326 2.983 -0.024 0.981 RaceWhite -0.392 0.675 0.513 0.247 1.845 -0.766 0.444 Stage2 0.366 1.442 0.554 0.487 4.268 0.661 0.509 Stage3 0.721 2.057 0.542 0.711 5.948 1.331 0.183 Stage4 1.149 3.154 0.512 1.156 8.603 2.243 0.025 * Purity 0.217 1.243 0.402 0.565 2.731 0.541 0.589 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.36e-04 Wald test p = 9.47e-04 Score (logrank) test p = 7.17e-04 ACACA in KICH (n=66): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ACACA 1.275 3.580000e+00 0.499 1.347 9.513000e+00 2.558 0.011 Age 0.048 1.049000e+00 0.028 0.992 1.109000e+00 1.681 0.093 Gendermale -0.502 6.050000e-01 0.728 0.145 2.521000e+00 -0.689 0.491 RaceBlack -13.718 0.000000e+00 5022.199 0.000 Inf -0.003 0.998 RaceWhite 1.431 4.181000e+00 1.160 0.430 4.064400e+01 1.233 0.218 Stage2 14.925 3.032405e+06 0.847 576536.398 1.594953e+07 17.621 0.000 Stage3 15.838 7.560274e+06 0.776 1651746.200 3.460444e+07 20.408 0.000 Stage4 18.649 1.256582e+08 0.893 21838678.664 7.230279e+08 20.888 0.000 Purity 1.578 4.847000e+00 3.989 0.002 1.203968e+04 0.396 0.692 signif ACACA * Age · Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.364 (max possible = 6.71e-01 ) Likelihood ratio test p = 7.86e-04 Wald test p = 3.29e-247 Score (logrank) test p = 5.28e-09 ACACA in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.662 1.939 0.168 1.394 2.695 3.937 0.000 *** Age 0.037 1.038 0.008 1.021 1.055 4.367 0.000 *** Gendermale -0.022 0.978 0.185 0.681 1.404 -0.121 0.903 RaceBlack 0.348 1.417 1.058 0.178 11.259 0.329 0.742 RaceWhite 0.295 1.343 1.015 0.184 9.821 0.291 0.771 Stage2 0.258 1.295 0.346 0.657 2.549 0.747 0.455 Stage3 0.901 2.462 0.232 1.562 3.878 3.884 0.000 *** Stage4 1.859 6.418 0.219 4.179 9.859 8.491 0.000 *** Purity 0.161 1.175 0.366 0.573 2.410 0.441 0.659 Rsquare = 0.2 (max possible = 9.65e-01 ) Likelihood ratio test p = 1.15e-17 Wald test p = 2.48e-17 Score (logrank) test p = 7.71e-21 ACACA in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.280 1.323 0.302 0.732 2.390 0.926 0.354 Age 0.012 1.012 0.016 0.980 1.045 0.754 0.451 Gendermale -0.498 0.608 0.382 0.287 1.286 -1.301 0.193 RaceBlack -1.876 0.153 1.202 0.015 1.614 -1.561 0.118 RaceWhite -2.014 0.133 1.176 0.013 1.337 -1.713 0.087 · Stage2 -0.481 0.618 1.058 0.078 4.913 -0.455 0.649 Stage3 1.663 5.278 0.426 2.288 12.174 3.901 0.000 *** Stage4 2.687 14.686 0.511 5.390 40.015 5.254 0.000 *** Purity -0.264 0.768 0.746 0.178 3.315 -0.354 0.723 Rsquare = 0.166 (max possible = 7.58e-01 ) Likelihood ratio test p = 8.14e-06 Wald test p = 3.65e-06 Score (logrank) test p = 5.61e-10 ACACA in LAML (n=173): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.173 1.188 0.186 0.825 1.712 0.925 0.355 Age 0.039 1.040 0.008 1.023 1.056 4.739 0.000 *** Gendermale -0.164 0.849 0.214 0.558 1.291 -0.766 0.444 RaceBlack -0.322 0.724 1.106 0.083 6.326 -0.291 0.771 RaceWhite -0.711 0.491 1.018 0.067 3.608 -0.699 0.485 Rsquare = 0.161 (max possible = 9.96e-01 ) Likelihood ratio test p = 8.61e-05 Wald test p = 2.95e-04 Score (logrank) test p = 1.97e-04 ACACA in LGG (n=516): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.484 0.616 0.196 0.419 0.906 -2.464 0.014 * Age 0.062 1.064 0.008 1.048 1.080 8.114 0.000 *** Gendermale 0.022 1.022 0.196 0.696 1.500 0.111 0.912 RaceBlack 15.562 5733112.888 1957.284 0.000 Inf 0.008 0.994 RaceWhite 15.561 5728383.170 1957.284 0.000 Inf 0.008 0.994 Purity -0.758 0.469 0.418 0.207 1.063 -1.814 0.070 · Rsquare = 0.147 (max possible = 9.07e-01 ) Likelihood ratio test p = 6.86e-14 Wald test p = 5.53e-14 Score (logrank) test p = 2.68e-15 ACACA in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.375 1.455 0.134 1.120 1.890 2.808 0.005 ** Age 0.012 1.012 0.008 0.996 1.028 1.453 0.146 Gendermale -0.167 0.846 0.229 0.541 1.324 -0.731 0.465 RaceBlack 0.857 2.355 0.493 0.896 6.189 1.738 0.082 · RaceWhite 0.041 1.042 0.237 0.655 1.659 0.175 0.861 Stage2 0.222 1.249 0.263 0.745 2.092 0.843 0.399 Stage3 0.818 2.266 0.238 1.421 3.613 3.438 0.001 ** Stage4 1.528 4.607 0.619 1.370 15.493 2.469 0.014 * Purity 0.476 1.610 0.462 0.652 3.979 1.032 0.302 Rsquare = 0.108 (max possible = 9.66e-01 ) Likelihood ratio test p = 4.96e-05 Wald test p = 3.47e-05 Score (logrank) test p = 1.05e-05 ACACA in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.024 0.976 0.129 0.759 1.256 -0.185 0.853 Age 0.007 1.007 0.009 0.989 1.025 0.765 0.444 Gendermale 0.019 1.019 0.169 0.732 1.420 0.112 0.911 RaceBlack 16.071 9537040.784 1881.731 0.000 Inf 0.009 0.993 RaceWhite 16.254 11455566.112 1881.731 0.000 Inf 0.009 0.993 Stage2 0.866 2.376 0.201 1.603 3.523 4.308 0.000 *** Stage3 1.020 2.774 0.221 1.801 4.274 4.628 0.000 *** Stage4 1.005 2.732 0.334 1.420 5.258 3.009 0.003 ** Purity 0.606 1.833 0.350 0.924 3.636 1.732 0.083 · Rsquare = 0.097 (max possible = 9.74e-01 ) Likelihood ratio test p = 2.37e-06 Wald test p = 3.02e-05 Score (logrank) test p = 3.55e-06 ACACA in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.170 1.185 0.133 0.913 1.538 1.276 0.202 Age 0.017 1.017 0.009 0.998 1.035 1.766 0.077 · Gendermale 0.383 1.467 0.197 0.997 2.159 1.946 0.052 · RaceBlack -0.002 0.998 0.599 0.308 3.231 -0.003 0.998 RaceWhite -0.520 0.594 0.556 0.200 1.767 -0.935 0.350 Stage2 0.168 1.182 0.190 0.815 1.715 0.883 0.377 Stage3 0.584 1.794 0.214 1.178 2.731 2.726 0.006 ** Stage4 0.894 2.445 0.790 0.520 11.511 1.131 0.258 Purity -0.418 0.658 0.371 0.318 1.361 -1.128 0.259 Rsquare = 0.055 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.38e-02 Wald test p = 1.09e-02 Score (logrank) test p = 9.11e-03 ACACA in MESO (n=87): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.445 1.560 0.188 1.078 2.258 2.361 0.018 * Age 0.017 1.017 0.016 0.986 1.050 1.063 0.288 Gendermale -0.229 0.795 0.333 0.414 1.527 -0.688 0.491 RaceBlack -0.102 0.903 1.536 0.044 18.345 -0.066 0.947 RaceWhite -0.654 0.520 1.049 0.067 4.062 -0.623 0.533 Stage2 -0.360 0.698 0.466 0.280 1.740 -0.772 0.440 Stage3 -0.175 0.840 0.412 0.374 1.884 -0.424 0.672 Stage4 -0.244 0.784 0.477 0.308 1.998 -0.510 0.610 Purity -0.806 0.447 0.561 0.149 1.341 -1.437 0.151 Rsquare = 0.121 (max possible = 9.98e-01 ) Likelihood ratio test p = 2.78e-01 Wald test p = 2.86e-01 Score (logrank) test p = 2.69e-01 ACACA in OV (n=303): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.191 1.211 0.122 0.954 1.537 1.571 0.116 Age 0.036 1.037 0.008 1.020 1.053 4.414 0.000 *** RaceBlack 0.049 1.050 0.581 0.336 3.279 0.084 0.933 RaceWhite -0.042 0.958 0.523 0.344 2.672 -0.081 0.935 Purity -0.516 0.597 0.670 0.161 2.217 -0.771 0.441 Rsquare = 0.091 (max possible = 9.97e-01 ) Likelihood ratio test p = 3.97e-04 Wald test p = 3.32e-04 Score (logrank) test p = 2.65e-04 ACACA in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.059 1.061 0.203 0.712 1.580 0.291 0.771 Age 0.022 1.022 0.011 1.001 1.044 2.044 0.041 * Gendermale -0.202 0.817 0.221 0.530 1.259 -0.917 0.359 RaceBlack -0.030 0.970 0.738 0.228 4.121 -0.041 0.967 RaceWhite 0.363 1.437 0.474 0.568 3.635 0.766 0.444 Stage2 0.643 1.902 0.442 0.800 4.522 1.455 0.146 Stage3 -0.198 0.821 1.100 0.095 7.086 -0.180 0.857 Stage4 0.242 1.273 0.824 0.253 6.403 0.293 0.769 Purity -0.658 0.518 0.411 0.231 1.158 -1.603 0.109 Rsquare = 0.089 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.12e-02 Wald test p = 1.17e-01 Score (logrank) test p = 1.13e-01 ACACA in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.154 1.166 0.664 0.318 4.282 0.232 0.817 Age 0.041 1.041 0.031 0.980 1.107 1.310 0.190 Gendermale 1.415 4.118 0.899 0.707 23.986 1.574 0.115 RaceBlack -0.336 0.714 19567.774 0.000 Inf 0.000 1.000 RaceWhite 17.166 28516780.273 15666.279 0.000 Inf 0.001 0.999 Purity 5.695 297.339 3.385 0.391 226145.087 1.682 0.092 · Rsquare = 0.055 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.59e-01 Wald test p = 4.25e-01 Score (logrank) test p = 3.11e-01 ACACA in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.062 0.940 0.533 0.331 2.671 -0.116 0.907 Age 0.009 1.009 0.057 0.902 1.128 0.158 0.874 RaceBlack 15.001 3271674.163 6742.727 0.000 Inf 0.002 0.998 RaceWhite 16.252 11433564.714 6742.727 0.000 Inf 0.002 0.998 Purity 1.131 3.099 1.452 0.180 53.402 0.779 0.436 Rsquare = 0.007 (max possible = 1.83e-01 ) Likelihood ratio test p = 7.43e-01 Wald test p = 8.65e-01 Score (logrank) test p = 8.13e-01 ACACA in READ (n=166): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.064 0.938 0.608 0.285 3.084 -0.106 0.915 Age 0.108 1.114 0.047 1.016 1.221 2.308 0.021 * Gendermale -0.348 0.706 0.692 0.182 2.743 -0.503 0.615 RaceBlack 13.430 680129.228 10262.682 0.000 Inf 0.001 0.999 RaceWhite 12.425 248991.186 10262.682 0.000 Inf 0.001 0.999 Stage2 -1.847 0.158 1.254 0.014 1.841 -1.473 0.141 Stage3 -0.484 0.617 0.905 0.105 3.634 -0.534 0.593 Stage4 -0.148 0.862 0.954 0.133 5.599 -0.155 0.877 Purity 0.114 1.121 1.343 0.081 15.571 0.085 0.932 Rsquare = 0.209 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.69e-02 Wald test p = 2.32e-01 Score (logrank) test p = 4.52e-02 ACACA in SARC (n=260): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.365 1.440 0.131 1.115 1.862 2.789 0.005 ** Age 0.025 1.025 0.008 1.008 1.042 2.926 0.003 ** Gendermale 0.116 1.123 0.228 0.719 1.755 0.509 0.611 RaceBlack -0.096 0.909 1.086 0.108 7.643 -0.088 0.930 RaceWhite -0.527 0.591 1.023 0.080 4.385 -0.515 0.607 Purity 0.723 2.061 0.579 0.662 6.411 1.249 0.212 Rsquare = 0.07 (max possible = 9.75e-01 ) Likelihood ratio test p = 9.38e-03 Wald test p = 1.14e-02 Score (logrank) test p = 1.08e-02 ACACA in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.229 1.258 0.133 0.969 1.633 1.720 0.085 · Age 0.018 1.018 0.005 1.008 1.029 3.549 0.000 *** Gendermale -0.062 0.940 0.157 0.691 1.280 -0.391 0.696 RaceWhite -1.283 0.277 0.402 0.126 0.610 -3.191 0.001 ** Stage2 0.245 1.277 0.219 0.832 1.961 1.119 0.263 Stage3 0.600 1.822 0.204 1.221 2.718 2.937 0.003 ** Stage4 1.417 4.123 0.355 2.058 8.260 3.996 0.000 *** Purity 0.903 2.466 0.348 1.247 4.876 2.596 0.009 ** Rsquare = 0.13 (max possible = 9.92e-01 ) Likelihood ratio test p = 5.84e-09 Wald test p = 3.23e-09 Score (logrank) test p = 3.82e-10 ACACA in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.524 1.688000e+00 0.432 0.724 3.938 1.212 0.226 Age 0.016 1.016000e+00 0.016 0.984 1.048 0.966 0.334 Gendermale 0.205 1.227000e+00 0.435 0.524 2.876 0.471 0.637 RaceWhite -1.072 3.420000e-01 0.655 0.095 1.236 -1.636 0.102 Stage2 17.673 4.736339e+07 6244.709 0.000 Inf 0.003 0.998 Stage3 18.307 8.923338e+07 6244.709 0.000 Inf 0.003 0.998 Stage4 20.416 7.354225e+08 6244.709 0.000 Inf 0.003 0.997 Purity 0.136 1.145000e+00 0.943 0.180 7.272 0.144 0.886 Rsquare = 0.16 (max possible = 8.69e-01 ) Likelihood ratio test p = 3.66e-02 Wald test p = 3.96e-02 Score (logrank) test p = 2.79e-03 ACACA in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.226 1.254 0.145 0.944 1.664 1.563 0.118 Age 0.020 1.020 0.006 1.009 1.032 3.637 0.000 *** Gendermale -0.069 0.933 0.172 0.666 1.308 -0.401 0.688 RaceWhite -1.073 0.342 0.600 0.106 1.108 -1.788 0.074 · Stage2 0.117 1.124 0.231 0.715 1.768 0.507 0.612 Stage3 0.548 1.730 0.209 1.148 2.608 2.621 0.009 ** Stage4 1.205 3.336 0.403 1.514 7.350 2.989 0.003 ** Purity 1.027 2.794 0.379 1.330 5.868 2.713 0.007 ** Rsquare = 0.141 (max possible = 9.95e-01 ) Likelihood ratio test p = 3.74e-07 Wald test p = 5.73e-07 Score (logrank) test p = 2.27e-07 ACACA in STAD (n=415): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.055 0.947 0.144 0.713 1.256 -0.381 0.703 Age 0.026 1.027 0.010 1.006 1.047 2.574 0.010 * Gendermale 0.125 1.133 0.208 0.754 1.702 0.602 0.547 RaceBlack 0.300 1.349 0.455 0.553 3.293 0.658 0.510 RaceWhite 0.106 1.112 0.246 0.687 1.801 0.431 0.666 Stage2 0.487 1.628 0.390 0.758 3.493 1.250 0.211 Stage3 0.920 2.509 0.363 1.231 5.114 2.531 0.011 * Stage4 1.312 3.715 0.505 1.381 9.992 2.599 0.009 ** Purity -0.543 0.581 0.382 0.275 1.228 -1.423 0.155 Rsquare = 0.07 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.3e-02 Wald test p = 1.77e-02 Score (logrank) test p = 1.44e-02 ACACA in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -25.500 0.000000e+00 67346.370 0 Inf 0.000 1.000 Age -1.208 2.990000e-01 1709.352 0 Inf -0.001 0.999 RaceBlack 2.416 1.120500e+01 17778183.057 0 Inf 0.000 1.000 RaceWhite -61.615 0.000000e+00 18113362.542 0 Inf 0.000 1.000 Stage2 13.145 5.113659e+05 40370.937 0 Inf 0.000 1.000 Stage3 33.478 3.461992e+14 117650.251 0 Inf 0.000 1.000 Purity 12.704 3.292173e+05 192659.871 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.29e-03 ACACA in THCA (n=509): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.990 2.692 0.651 0.752 9.642 1.521 0.128 Age 0.152 1.164 0.029 1.100 1.231 5.298 0.000 *** Gendermale -0.319 0.727 0.645 0.205 2.573 -0.494 0.621 RaceBlack 17.369 34930547.754 9182.543 0.000 Inf 0.002 0.998 RaceWhite 17.315 33098970.954 9182.543 0.000 Inf 0.002 0.998 Stage2 0.405 1.500 1.129 0.164 13.720 0.359 0.720 Stage3 0.604 1.830 0.884 0.324 10.347 0.684 0.494 Stage4 2.031 7.624 1.036 1.000 58.114 1.960 0.050 · Purity 2.597 13.424 1.123 1.485 121.374 2.312 0.021 * Rsquare = 0.154 (max possible = 3.47e-01 ) Likelihood ratio test p = 8.84e-11 Wald test p = 2.49e-04 Score (logrank) test p = 6.93e-11 ACACA in THYM (n=120): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.338 1.402 0.517 0.509 3.865 0.653 0.514 Age 0.045 1.046 0.031 0.984 1.113 1.434 0.152 Gendermale -0.191 0.826 0.730 0.198 3.457 -0.261 0.794 RaceBlack -16.306 0.000 10153.190 0.000 Inf -0.002 0.999 RaceWhite 0.719 2.052 1.179 0.204 20.677 0.610 0.542 Purity 0.238 1.269 1.129 0.139 11.592 0.211 0.833 Rsquare = 0.048 (max possible = 4.51e-01 ) Likelihood ratio test p = 4.79e-01 Wald test p = 6.36e-01 Score (logrank) test p = 5.26e-01 ACACA in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 0.117 1.125 0.228 0.719 1.759 0.515 0.607 Age 0.050 1.051 0.016 1.019 1.084 3.165 0.002 ** RaceBlack -0.400 0.670 0.794 0.141 3.173 -0.505 0.614 RaceWhite -0.499 0.607 0.746 0.141 2.617 -0.670 0.503 Purity 0.441 1.554 0.644 0.440 5.486 0.685 0.494 Rsquare = 0.039 (max possible = 7.81e-01 ) Likelihood ratio test p = 4.54e-02 Wald test p = 5.29e-02 Score (logrank) test p = 5.31e-02 ACACA in UCS (n=57): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA -0.029 0.971 0.280 0.561 1.683 -0.103 0.918 Age 0.044 1.045 0.025 0.996 1.097 1.784 0.074 · RaceBlack 17.582 43243967.718 6474.868 0.000 Inf 0.003 0.998 RaceWhite 17.835 55667621.165 6474.868 0.000 Inf 0.003 0.998 Purity -0.883 0.413 1.063 0.051 3.323 -0.831 0.406 Rsquare = 0.119 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.53e-01 Wald test p = 3.6e-01 Score (logrank) test p = 2.66e-01 ACACA in UVM (n=80): Model: Surv(OS, EVENT) ~ `ACACA` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACACA 1.348 3.849 0.494 1.461 10.141 2.727 0.006 ** Age 0.041 1.042 0.019 1.004 1.082 2.197 0.028 * Gendermale 0.342 1.408 0.485 0.544 3.645 0.705 0.481 Stage3 0.171 1.186 0.510 0.437 3.222 0.335 0.738 Stage4 4.308 74.265 1.228 6.690 824.415 3.508 0.000 *** Purity 1.647 5.192 1.311 0.398 67.757 1.257 0.209 Rsquare = 0.333 (max possible = 8.72e-01 ) Likelihood ratio test p = 2.34e-05 Wald test p = 7.23e-04 Score (logrank) test p = 2.09e-10 AACS in ACC (n=79): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.683 1.980 0.237 1.244 3.151 2.881 0.004 ** Age 0.016 1.017 0.015 0.988 1.046 1.123 0.262 Gendermale 0.789 2.201 0.453 0.905 5.350 1.740 0.082 · RaceBlack -0.776 0.460 13042.708 0.000 Inf 0.000 1.000 RaceWhite 15.824 7451924.559 11173.110 0.000 Inf 0.001 0.999 Purity 0.777 2.174 2.272 0.025 186.697 0.342 0.732 Rsquare = 0.197 (max possible = 9.38e-01 ) Likelihood ratio test p = 2.92e-02 Wald test p = 1.12e-01 Score (logrank) test p = 6.31e-02 AACS in BLCA (n=408): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.150 1.162 0.123 0.913 1.478 1.219 0.223 Age 0.034 1.035 0.009 1.018 1.052 3.988 0.000 *** Gendermale -0.179 0.836 0.178 0.589 1.186 -1.005 0.315 RaceBlack 0.657 1.930 0.449 0.801 4.649 1.465 0.143 RaceWhite 0.094 1.098 0.355 0.548 2.201 0.265 0.791 Stage2 14.575 2136624.920 1855.065 0.000 Inf 0.008 0.994 Stage3 15.040 3400774.060 1855.065 0.000 Inf 0.008 0.994 Stage4 15.535 5581952.054 1855.065 0.000 Inf 0.008 0.993 Purity 0.150 1.161 0.340 0.596 2.263 0.440 0.660 Rsquare = 0.134 (max possible = 9.91e-01 ) Likelihood ratio test p = 1.07e-07 Wald test p = 6.13e-07 Score (logrank) test p = 1.94e-07 AACS in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.079 0.924 0.139 0.704 1.212 -0.572 0.567 Age 0.036 1.036 0.008 1.021 1.052 4.704 0.000 *** Gendermale 0.038 1.038 1.007 0.144 7.477 0.037 0.970 RaceBlack 0.001 1.001 0.619 0.298 3.366 0.002 0.999 RaceWhite -0.220 0.803 0.596 0.250 2.579 -0.369 0.712 Stage2 0.398 1.489 0.304 0.820 2.702 1.308 0.191 Stage3 1.193 3.298 0.313 1.786 6.090 3.814 0.000 *** Stage4 2.521 12.438 0.389 5.805 26.653 6.483 0.000 *** Purity 0.541 1.717 0.423 0.750 3.935 1.278 0.201 Rsquare = 0.081 (max possible = 7.85e-01 ) Likelihood ratio test p = 2.14e-12 Wald test p = 5.43e-16 Score (logrank) test p = 6.92e-22 AACS in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `AACS` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.130 8.780000e-01 0.250 0.538 1.433 -0.519 0.603 Age 0.011 1.011000e+00 0.017 0.977 1.046 0.609 0.543 RaceBlack -0.988 3.720000e-01 1.121 0.041 3.353 -0.881 0.378 RaceWhite -1.349 2.600000e-01 1.143 0.028 2.439 -1.180 0.238 Stage2 18.656 1.264884e+08 6485.478 0.000 Inf 0.003 0.998 Stage3 20.083 5.272325e+08 6485.478 0.000 Inf 0.003 0.998 Stage4 21.491 2.154534e+09 6485.478 0.000 Inf 0.003 0.997 Purity 0.794 2.212000e+00 0.957 0.339 14.438 0.829 0.407 Rsquare = 0.158 (max possible = 7.18e-01 ) Likelihood ratio test p = 4.69e-04 Wald test p = 6.88e-03 Score (logrank) test p = 4.31e-06 AACS in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `AACS` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.179 1.196000e+00 0.527 0.425 3.360 0.339 0.735 Age 0.032 1.033000e+00 0.028 0.977 1.091 1.141 0.254 RaceBlack -3.056 4.700000e-02 1.797 0.001 1.594 -1.701 0.089 · RaceWhite -1.663 1.900000e-01 1.454 0.011 3.276 -1.144 0.253 Stage2 18.134 7.507027e+07 14957.882 0.000 Inf 0.001 0.999 Stage3 19.807 4.000239e+08 14957.882 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 3.234 2.538500e+01 2.319 0.269 2391.775 1.394 0.163 Rsquare = 0.371 (max possible = 6.68e-01 ) Likelihood ratio test p = 2.86e-04 Wald test p = 2.44e-01 Score (logrank) test p = 1.19e-14 AACS in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.188 0.829 0.243 0.514 1.336 -0.771 0.441 Age 0.048 1.049 0.012 1.025 1.074 4.041 0.000 *** Gendermale -15.331 0.000 3432.364 0.000 Inf -0.004 0.996 RaceBlack -0.424 0.655 1.173 0.066 6.528 -0.361 0.718 RaceWhite 0.279 1.321 1.031 0.175 9.975 0.270 0.787 Stage2 0.305 1.357 0.375 0.651 2.830 0.814 0.416 Stage3 0.881 2.414 0.394 1.116 5.222 2.238 0.025 * Stage4 2.188 8.916 0.594 2.783 28.563 3.683 0.000 *** Purity 0.394 1.483 0.623 0.437 5.026 0.632 0.527 Rsquare = 0.071 (max possible = 6.81e-01 ) Likelihood ratio test p = 8.15e-05 Wald test p = 1.53e-05 Score (logrank) test p = 3.16e-07 AACS in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.053 1.055 0.372 0.509 2.185 0.143 0.886 Age 0.051 1.052 0.022 1.008 1.098 2.323 0.020 * Gendermale 0.988 2.685 1.108 0.306 23.554 0.891 0.373 RaceBlack 16.573 15766243.357 6514.097 0.000 Inf 0.003 0.998 RaceWhite 15.944 8400308.142 6514.097 0.000 Inf 0.002 0.998 Stage2 0.668 1.949 1.076 0.237 16.070 0.620 0.535 Stage3 1.593 4.917 1.061 0.615 39.343 1.501 0.133 Stage4 2.076 7.971 1.173 0.799 79.484 1.769 0.077 · Purity 0.999 2.716 1.351 0.192 38.333 0.740 0.459 Rsquare = 0.105 (max possible = 6.98e-01 ) Likelihood ratio test p = 4.18e-02 Wald test p = 7.29e-02 Score (logrank) test p = 2.44e-02 AACS in CESC (n=306): Model: Surv(OS, EVENT) ~ `AACS` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.189 1.208 0.238 0.757 1.926 0.793 0.428 Age 0.011 1.011 0.010 0.991 1.031 1.055 0.291 RaceBlack 1.077 2.935 1.068 0.362 23.818 1.008 0.313 RaceWhite 0.821 2.274 1.015 0.311 16.621 0.809 0.418 Purity 0.545 1.724 0.733 0.410 7.248 0.744 0.457 Rsquare = 0.016 (max possible = 8.91e-01 ) Likelihood ratio test p = 5.83e-01 Wald test p = 6.15e-01 Score (logrank) test p = 6.06e-01 AACS in CHOL (n=36): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.295 0.744 0.586 0.236 2.346 -0.504 0.614 Age 0.012 1.012 0.024 0.966 1.060 0.508 0.612 Gendermale 0.117 1.124 0.624 0.331 3.816 0.187 0.852 RaceBlack -0.631 0.532 1.571 0.024 11.565 -0.402 0.688 RaceWhite -1.126 0.324 0.896 0.056 1.877 -1.257 0.209 Stage2 0.678 1.970 0.659 0.541 7.167 1.029 0.304 Stage3 -16.225 0.000 7047.017 0.000 Inf -0.002 0.998 Stage4 0.793 2.209 0.667 0.597 8.171 1.188 0.235 Purity 1.973 7.194 1.550 0.345 150.096 1.273 0.203 Rsquare = 0.217 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.56e-01 Wald test p = 6.09e-01 Score (logrank) test p = 4.36e-01 AACS in COAD (n=458): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.097 0.908 0.282 0.523 1.576 -0.345 0.730 Age 0.024 1.024 0.012 1.001 1.047 2.063 0.039 * Gendermale 0.209 1.232 0.269 0.727 2.088 0.776 0.438 RaceBlack -0.432 0.649 0.828 0.128 3.288 -0.522 0.602 RaceWhite -0.458 0.632 0.775 0.138 2.890 -0.591 0.554 Stage2 0.217 1.242 0.562 0.412 3.740 0.385 0.700 Stage3 0.809 2.245 0.549 0.765 6.586 1.472 0.141 Stage4 1.881 6.561 0.553 2.220 19.389 3.403 0.001 ** Purity -0.236 0.790 0.602 0.243 2.568 -0.392 0.695 Rsquare = 0.11 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.44e-04 Wald test p = 1.64e-04 Score (logrank) test p = 2.33e-05 AACS in DLBC (n=48): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.233 0.792 0.822 0.158 3.964 -0.284 0.776 Age -0.007 0.993 0.044 0.911 1.083 -0.162 0.871 Gendermale 0.606 1.833 1.070 0.225 14.925 0.566 0.571 RaceBlack 0.359 1.433 1.597 0.063 32.787 0.225 0.822 RaceWhite -2.096 0.123 1.276 0.010 1.499 -1.643 0.100 Purity -2.019 0.133 2.137 0.002 8.759 -0.945 0.345 Rsquare = 0.132 (max possible = 5.58e-01 ) Likelihood ratio test p = 4.43e-01 Wald test p = 5.75e-01 Score (logrank) test p = 3.22e-01 AACS in ESCA (n=185): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.185 1.204 0.257 0.727 1.993 0.721 0.471 Age 0.010 1.010 0.014 0.983 1.038 0.723 0.470 Gendermale 0.492 1.636 0.538 0.570 4.694 0.915 0.360 RaceBlack 0.262 1.300 1.072 0.159 10.621 0.245 0.807 RaceWhite 0.023 1.023 0.472 0.406 2.578 0.048 0.961 Stage2 0.751 2.120 0.659 0.582 7.719 1.139 0.255 Stage3 1.492 4.447 0.672 1.190 16.615 2.219 0.026 * Stage4 2.888 17.949 0.777 3.911 82.366 3.714 0.000 *** Purity 0.170 1.186 0.768 0.263 5.341 0.222 0.824 Rsquare = 0.144 (max possible = 9.32e-01 ) Likelihood ratio test p = 9.6e-03 Wald test p = 4.56e-03 Score (logrank) test p = 3.69e-04 AACS in GBM (n=153): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.544 1.724 0.224 1.112 2.673 2.433 0.015 * Age 0.029 1.029 0.008 1.013 1.046 3.518 0.000 *** Gendermale -0.047 0.954 0.214 0.627 1.451 -0.220 0.826 RaceBlack 0.443 1.557 0.729 0.373 6.499 0.607 0.544 RaceWhite -0.344 0.709 0.617 0.212 2.374 -0.558 0.577 Purity -1.092 0.336 0.516 0.122 0.922 -2.117 0.034 * Rsquare = 0.167 (max possible = 9.98e-01 ) Likelihood ratio test p = 3.94e-04 Wald test p = 4.85e-04 Score (logrank) test p = 3.71e-04 AACS in HNSC (n=522): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.109 0.897 0.126 0.701 1.147 -0.866 0.387 Age 0.022 1.022 0.008 1.007 1.037 2.825 0.005 ** Gendermale -0.248 0.780 0.172 0.557 1.092 -1.446 0.148 RaceBlack 0.163 1.177 0.559 0.393 3.522 0.291 0.771 RaceWhite -0.216 0.806 0.512 0.296 2.198 -0.421 0.673 Stage2 0.591 1.805 0.544 0.621 5.247 1.085 0.278 Stage3 0.820 2.271 0.538 0.791 6.514 1.525 0.127 Stage4 1.229 3.416 0.511 1.255 9.297 2.405 0.016 * Purity -0.049 0.952 0.363 0.468 1.937 -0.136 0.891 Rsquare = 0.071 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.93e-04 Wald test p = 1.05e-03 Score (logrank) test p = 7.54e-04 AACS in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.694 4.990000e-01 0.327 0.263 0.948 -2.123 0.034 * Age 0.003 1.003000e+00 0.027 0.951 1.057 0.108 0.914 Gendermale -0.037 9.640000e-01 0.577 0.311 2.986 -0.064 0.949 RaceBlack 18.720 1.349383e+08 12649.387 0.000 Inf 0.001 0.999 RaceWhite 17.507 4.010883e+07 12649.387 0.000 Inf 0.001 0.999 Stage2 17.180 2.892650e+07 5315.721 0.000 Inf 0.003 0.997 Stage3 16.351 1.262308e+07 5315.721 0.000 Inf 0.003 0.998 Stage4 17.258 3.125811e+07 5315.721 0.000 Inf 0.003 0.997 Purity -1.562 2.100000e-01 1.052 0.027 1.650 -1.484 0.138 Rsquare = 0.155 (max possible = 9.17e-01 ) Likelihood ratio test p = 2.81e-01 Wald test p = 5.64e-01 Score (logrank) test p = 4.28e-01 AACS in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.044 1.045 0.146 0.785 1.392 0.304 0.761 Age 0.027 1.027 0.008 1.011 1.045 3.203 0.001 ** Gendermale -0.284 0.753 0.183 0.526 1.077 -1.556 0.120 RaceBlack -0.033 0.968 0.566 0.319 2.937 -0.058 0.954 RaceWhite -0.414 0.661 0.516 0.241 1.817 -0.803 0.422 Stage2 0.376 1.456 0.555 0.491 4.318 0.678 0.498 Stage3 0.740 2.095 0.543 0.723 6.067 1.363 0.173 Stage4 1.157 3.182 0.513 1.164 8.698 2.256 0.024 * Purity 0.212 1.236 0.400 0.564 2.709 0.529 0.596 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.28e-04 Wald test p = 9.14e-04 Score (logrank) test p = 6.94e-04 AACS in KICH (n=66): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p AACS 0.273 1.314000e+00 0.542 0.454 3.799000e+00 0.504 0.614 Age 0.074 1.076000e+00 0.029 1.016 1.140000e+00 2.504 0.012 Gendermale -0.727 4.840000e-01 0.726 0.116 2.008000e+00 -1.000 0.317 RaceBlack -16.972 0.000000e+00 6180.272 0.000 Inf -0.003 0.998 RaceWhite -1.673 1.880000e-01 1.158 0.019 1.816000e+00 -1.445 0.149 Stage2 15.861 7.732198e+06 0.847 1470880.219 4.064701e+07 18.732 0.000 Stage3 17.009 2.436890e+07 0.777 5313843.333 1.117540e+08 21.889 0.000 Stage4 19.275 2.349739e+08 0.895 40662288.395 1.357836e+09 21.536 0.000 Purity 0.962 2.618000e+00 3.718 0.002 3.825323e+03 0.259 0.796 signif AACS Age * Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.347 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.47e-03 Wald test p = 5.39e-275 Score (logrank) test p = 1.03e-08 AACS in KIRC (n=533): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.192 1.212 0.162 0.883 1.664 1.188 0.235 Age 0.036 1.037 0.008 1.020 1.054 4.285 0.000 *** Gendermale -0.041 0.960 0.187 0.666 1.383 -0.221 0.825 RaceBlack 0.197 1.217 1.056 0.154 9.642 0.186 0.852 RaceWhite 0.123 1.131 1.014 0.155 8.252 0.121 0.903 Stage2 0.206 1.229 0.344 0.626 2.414 0.600 0.549 Stage3 0.827 2.286 0.230 1.456 3.589 3.594 0.000 *** Stage4 1.781 5.937 0.217 3.884 9.075 8.226 0.000 *** Purity 0.011 1.012 0.368 0.492 2.081 0.031 0.975 Rsquare = 0.177 (max possible = 9.65e-01 ) Likelihood ratio test p = 5.4e-15 Wald test p = 6.09e-15 Score (logrank) test p = 2.93e-18 AACS in KIRP (n=290): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.185 0.831 0.339 0.428 1.615 -0.545 0.586 Age 0.007 1.007 0.016 0.976 1.038 0.417 0.676 Gendermale -0.522 0.593 0.385 0.279 1.263 -1.354 0.176 RaceBlack -2.091 0.124 1.203 0.012 1.306 -1.738 0.082 · RaceWhite -2.119 0.120 1.178 0.012 1.208 -1.799 0.072 · Stage2 -0.342 0.711 1.062 0.089 5.696 -0.322 0.748 Stage3 1.643 5.168 0.425 2.246 11.893 3.863 0.000 *** Stage4 2.703 14.919 0.505 5.545 40.137 5.352 0.000 *** Purity -0.235 0.790 0.759 0.179 3.497 -0.310 0.756 Rsquare = 0.164 (max possible = 7.58e-01 ) Likelihood ratio test p = 1.03e-05 Wald test p = 3.16e-06 Score (logrank) test p = 5.69e-10 AACS in LAML (n=173): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.187 1.205 0.169 0.866 1.677 1.109 0.268 Age 0.040 1.041 0.008 1.024 1.058 4.777 0.000 *** Gendermale -0.169 0.844 0.214 0.555 1.285 -0.789 0.430 RaceBlack -0.282 0.755 1.106 0.086 6.593 -0.255 0.799 RaceWhite -0.684 0.505 1.018 0.069 3.710 -0.672 0.502 Rsquare = 0.163 (max possible = 9.96e-01 ) Likelihood ratio test p = 7.32e-05 Wald test p = 2.53e-04 Score (logrank) test p = 1.82e-04 AACS in LGG (n=516): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.040 1.041 0.138 0.794 1.364 0.287 0.774 Age 0.061 1.063 0.008 1.047 1.079 7.993 0.000 *** Gendermale 0.098 1.103 0.197 0.750 1.622 0.497 0.619 RaceBlack 15.391 4832253.819 2011.281 0.000 Inf 0.008 0.994 RaceWhite 15.412 4937168.734 2011.281 0.000 Inf 0.008 0.994 Purity -0.935 0.393 0.410 0.176 0.876 -2.282 0.022 * Rsquare = 0.136 (max possible = 9.07e-01 ) Likelihood ratio test p = 1.11e-12 Wald test p = 1.03e-12 Score (logrank) test p = 9e-14 AACS in LIHC (n=371): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.322 1.380 0.111 1.110 1.716 2.897 0.004 ** Age 0.014 1.014 0.008 0.998 1.031 1.670 0.095 · Gendermale 0.007 1.007 0.235 0.636 1.595 0.031 0.975 RaceBlack 0.774 2.168 0.491 0.828 5.674 1.576 0.115 RaceWhite -0.019 0.981 0.240 0.613 1.570 -0.079 0.937 Stage2 0.235 1.265 0.263 0.756 2.118 0.896 0.370 Stage3 0.824 2.281 0.240 1.424 3.652 3.431 0.001 ** Stage4 1.756 5.790 0.620 1.718 19.518 2.832 0.005 ** Purity 0.658 1.932 0.464 0.777 4.800 1.418 0.156 Rsquare = 0.109 (max possible = 9.66e-01 ) Likelihood ratio test p = 4.5e-05 Wald test p = 1.99e-05 Score (logrank) test p = 5.89e-06 AACS in LUAD (n=515): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.042 1.043 0.115 0.833 1.306 0.369 0.712 Age 0.007 1.007 0.009 0.989 1.025 0.792 0.428 Gendermale 0.012 1.012 0.170 0.725 1.411 0.068 0.946 RaceBlack 16.098 9801352.721 1881.097 0.000 Inf 0.009 0.993 RaceWhite 16.277 11716712.920 1881.097 0.000 Inf 0.009 0.993 Stage2 0.858 2.359 0.202 1.588 3.504 4.250 0.000 *** Stage3 1.000 2.717 0.221 1.761 4.194 4.515 0.000 *** Stage4 1.005 2.731 0.334 1.419 5.254 3.008 0.003 ** Purity 0.579 1.784 0.345 0.906 3.510 1.676 0.094 · Rsquare = 0.097 (max possible = 9.74e-01 ) Likelihood ratio test p = 2.27e-06 Wald test p = 2.91e-05 Score (logrank) test p = 3.41e-06 AACS in LUSC (n=501): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.075 1.078 0.134 0.830 1.401 0.562 0.574 Age 0.015 1.016 0.009 0.997 1.034 1.629 0.103 Gendermale 0.444 1.559 0.194 1.066 2.281 2.290 0.022 * RaceBlack 0.006 1.006 0.606 0.307 3.300 0.009 0.993 RaceWhite -0.536 0.585 0.564 0.194 1.768 -0.950 0.342 Stage2 0.204 1.227 0.187 0.850 1.770 1.093 0.274 Stage3 0.579 1.784 0.219 1.162 2.738 2.648 0.008 ** Stage4 0.771 2.163 0.795 0.455 10.276 0.970 0.332 Purity -0.396 0.673 0.378 0.321 1.411 -1.049 0.294 Rsquare = 0.051 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.18e-02 Wald test p = 1.67e-02 Score (logrank) test p = 1.43e-02 AACS in MESO (n=87): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.168 0.845 0.210 0.560 1.275 -0.803 0.422 Age 0.018 1.019 0.016 0.988 1.050 1.180 0.238 Gendermale -0.138 0.871 0.331 0.455 1.668 -0.416 0.678 RaceBlack 0.220 1.246 1.531 0.062 25.041 0.144 0.886 RaceWhite -0.455 0.635 1.047 0.081 4.943 -0.434 0.664 Stage2 -0.222 0.801 0.468 0.320 2.005 -0.475 0.635 Stage3 -0.199 0.820 0.439 0.347 1.939 -0.452 0.651 Stage4 -0.201 0.818 0.482 0.318 2.103 -0.418 0.676 Purity -0.801 0.449 0.552 0.152 1.324 -1.451 0.147 Rsquare = 0.067 (max possible = 9.98e-01 ) Likelihood ratio test p = 7.49e-01 Wald test p = 7.17e-01 Score (logrank) test p = 7.06e-01 AACS in OV (n=303): Model: Surv(OS, EVENT) ~ `AACS` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.084 1.088 0.122 0.857 1.382 0.691 0.489 Age 0.037 1.037 0.008 1.021 1.054 4.471 0.000 *** RaceBlack -0.008 0.992 0.580 0.318 3.095 -0.014 0.989 RaceWhite -0.128 0.879 0.517 0.319 2.422 -0.249 0.804 Purity -0.537 0.584 0.668 0.158 2.165 -0.804 0.421 Rsquare = 0.083 (max possible = 9.97e-01 ) Likelihood ratio test p = 9.41e-04 Wald test p = 8.85e-04 Score (logrank) test p = 7.29e-04 AACS in PAAD (n=179): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.056 0.945 0.193 0.647 1.380 -0.292 0.770 Age 0.021 1.022 0.011 1.000 1.044 1.952 0.051 · Gendermale -0.214 0.807 0.216 0.528 1.234 -0.989 0.323 RaceBlack 0.007 1.007 0.744 0.234 4.331 0.009 0.993 RaceWhite 0.374 1.453 0.476 0.572 3.695 0.785 0.432 Stage2 0.601 1.825 0.444 0.765 4.353 1.356 0.175 Stage3 -0.289 0.749 1.105 0.086 6.535 -0.261 0.794 Stage4 0.210 1.233 0.829 0.243 6.262 0.253 0.800 Purity -0.666 0.514 0.409 0.231 1.144 -1.631 0.103 Rsquare = 0.089 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.12e-02 Wald test p = 1.17e-01 Score (logrank) test p = 1.11e-01 AACS in PCPG (n=181): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 1.554 4.728 0.826 0.938 23.845 1.882 0.060 · Age 0.033 1.034 0.028 0.978 1.093 1.168 0.243 Gendermale 0.973 2.647 0.903 0.451 15.539 1.078 0.281 RaceBlack -1.267 0.282 30531.681 0.000 Inf 0.000 1.000 RaceWhite 18.393 97300654.228 28097.873 0.000 Inf 0.001 0.999 Purity 5.498 244.135 3.398 0.313 190550.839 1.618 0.106 Rsquare = 0.074 (max possible = 3.07e-01 ) Likelihood ratio test p = 4.88e-02 Wald test p = 1.63e-01 Score (logrank) test p = 1.15e-01 AACS in PRAD (n=498): Model: Surv(OS, EVENT) ~ `AACS` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.652 1.919 0.711 0.477 7.725 0.917 0.359 Age 0.011 1.011 0.056 0.905 1.128 0.187 0.852 RaceBlack 15.303 4426990.646 6816.660 0.000 Inf 0.002 0.998 RaceWhite 16.421 13532734.488 6816.660 0.000 Inf 0.002 0.998 Purity 1.121 3.067 1.383 0.204 46.130 0.810 0.418 Rsquare = 0.009 (max possible = 1.83e-01 ) Likelihood ratio test p = 6.08e-01 Wald test p = 7.24e-01 Score (logrank) test p = 6.61e-01 AACS in READ (n=166): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.355 0.702 0.737 0.165 2.975 -0.481 0.631 Age 0.104 1.110 0.044 1.018 1.210 2.373 0.018 * Gendermale -0.374 0.688 0.695 0.176 2.686 -0.539 0.590 RaceBlack 13.370 640709.595 10300.322 0.000 Inf 0.001 0.999 RaceWhite 12.376 237111.504 10300.322 0.000 Inf 0.001 0.999 Stage2 -1.967 0.140 1.278 0.011 1.713 -1.539 0.124 Stage3 -0.638 0.528 0.971 0.079 3.545 -0.657 0.511 Stage4 -0.228 0.796 0.967 0.120 5.299 -0.236 0.813 Purity 0.061 1.063 1.337 0.077 14.615 0.046 0.964 Rsquare = 0.212 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.44e-02 Wald test p = 2.09e-01 Score (logrank) test p = 3.95e-02 AACS in SARC (n=260): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.057 1.058 0.186 0.735 1.523 0.304 0.761 Age 0.022 1.023 0.008 1.006 1.039 2.693 0.007 ** Gendermale -0.008 0.992 0.222 0.642 1.534 -0.034 0.972 RaceBlack -0.106 0.899 1.088 0.107 7.585 -0.098 0.922 RaceWhite -0.460 0.631 1.022 0.085 4.681 -0.450 0.652 Purity 0.930 2.534 0.578 0.817 7.862 1.609 0.108 Rsquare = 0.043 (max possible = 9.75e-01 ) Likelihood ratio test p = 1.16e-01 Wald test p = 1.54e-01 Score (logrank) test p = 1.53e-01 AACS in SKCM (n=471): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.227 1.255 0.101 1.028 1.531 2.236 0.025 * Age 0.019 1.019 0.005 1.008 1.029 3.564 0.000 *** Gendermale -0.039 0.961 0.157 0.706 1.309 -0.250 0.802 RaceWhite -1.226 0.293 0.402 0.133 0.645 -3.050 0.002 ** Stage2 0.244 1.276 0.218 0.831 1.957 1.115 0.265 Stage3 0.607 1.836 0.205 1.229 2.741 2.969 0.003 ** Stage4 1.341 3.824 0.352 1.917 7.626 3.808 0.000 *** Purity 1.053 2.867 0.340 1.471 5.586 3.094 0.002 ** Rsquare = 0.134 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.46e-09 Wald test p = 1.45e-09 Score (logrank) test p = 1.67e-10 AACS in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 1.005 2.731000e+00 0.417 1.207 6.180 2.412 0.016 * Age 0.025 1.025000e+00 0.017 0.991 1.061 1.455 0.146 Gendermale 0.416 1.517000e+00 0.446 0.633 3.632 0.934 0.350 RaceWhite -1.125 3.250000e-01 0.624 0.095 1.104 -1.802 0.072 · Stage2 17.595 4.378650e+07 6387.662 0.000 Inf 0.003 0.998 Stage3 18.641 1.246492e+08 6387.662 0.000 Inf 0.003 0.998 Stage4 21.101 1.459119e+09 6387.662 0.000 Inf 0.003 0.997 Purity 0.249 1.282000e+00 0.914 0.214 7.688 0.272 0.785 Rsquare = 0.208 (max possible = 8.69e-01 ) Likelihood ratio test p = 5.03e-03 Wald test p = 1.43e-02 Score (logrank) test p = 5.81e-04 AACS in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.166 1.180 0.109 0.952 1.463 1.515 0.130 Age 0.021 1.021 0.006 1.010 1.032 3.651 0.000 *** Gendermale -0.052 0.949 0.172 0.677 1.330 -0.305 0.761 RaceWhite -1.022 0.360 0.600 0.111 1.165 -1.705 0.088 · Stage2 0.133 1.142 0.230 0.727 1.794 0.577 0.564 Stage3 0.558 1.747 0.210 1.159 2.635 2.664 0.008 ** Stage4 1.123 3.075 0.400 1.404 6.738 2.807 0.005 ** Purity 1.164 3.203 0.371 1.549 6.623 3.140 0.002 ** Rsquare = 0.14 (max possible = 9.95e-01 ) Likelihood ratio test p = 4.11e-07 Wald test p = 6.78e-07 Score (logrank) test p = 2.63e-07 AACS in STAD (n=415): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.224 0.799 0.141 0.606 1.054 -1.588 0.112 Age 0.026 1.026 0.010 1.006 1.047 2.536 0.011 * Gendermale 0.166 1.181 0.209 0.784 1.778 0.796 0.426 RaceBlack 0.405 1.500 0.456 0.613 3.669 0.888 0.375 RaceWhite 0.140 1.151 0.246 0.710 1.865 0.571 0.568 Stage2 0.479 1.614 0.389 0.753 3.463 1.230 0.219 Stage3 0.913 2.493 0.363 1.224 5.076 2.518 0.012 * Stage4 1.290 3.634 0.505 1.351 9.779 2.555 0.011 * Purity -0.556 0.574 0.378 0.274 1.202 -1.472 0.141 Rsquare = 0.077 (max possible = 9.79e-01 ) Likelihood ratio test p = 5.63e-03 Wald test p = 7.29e-03 Score (logrank) test p = 5.46e-03 AACS in TGCT (n=150): Model: Surv(OS, EVENT) ~ `AACS` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 4.909 1.354850e+02 34805.444 0 Inf 0.000 1.000 Age -1.666 1.890000e-01 1880.831 0 Inf -0.001 0.999 RaceBlack 14.668 2.344349e+06 33946825.489 0 Inf 0.000 1.000 RaceWhite -27.437 0.000000e+00 31165836.804 0 Inf 0.000 1.000 Stage2 -5.857 3.000000e-03 50606.431 0 Inf 0.000 1.000 Stage3 8.892 7.270817e+03 163886.810 0 Inf 0.000 1.000 Purity 20.003 4.864775e+08 232793.140 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 1.99e-03 AACS in THCA (n=509): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.617 1.853 0.564 0.613 5.601 1.093 0.274 Age 0.145 1.157 0.028 1.095 1.222 5.218 0.000 *** Gendermale -0.163 0.850 0.636 0.244 2.958 -0.256 0.798 RaceBlack 17.661 46801719.202 9033.963 0.000 Inf 0.002 0.998 RaceWhite 17.690 48172437.397 9033.963 0.000 Inf 0.002 0.998 Stage2 0.135 1.145 1.104 0.132 9.960 0.122 0.903 Stage3 0.409 1.506 0.866 0.276 8.226 0.472 0.637 Stage4 2.024 7.569 1.040 0.987 58.061 1.947 0.052 · Purity 2.135 8.458 1.080 1.019 70.230 1.977 0.048 * Rsquare = 0.152 (max possible = 3.47e-01 ) Likelihood ratio test p = 1.5e-10 Wald test p = 2.15e-04 Score (logrank) test p = 6.54e-11 AACS in THYM (n=120): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.288 1.333 0.418 0.588 3.024 0.688 0.491 Age 0.052 1.053 0.032 0.989 1.121 1.627 0.104 Gendermale -0.084 0.919 0.734 0.218 3.874 -0.115 0.909 RaceBlack -16.772 0.000 10266.119 0.000 Inf -0.002 0.999 RaceWhite 0.412 1.509 1.092 0.178 12.820 0.377 0.706 Purity 0.279 1.322 1.113 0.149 11.723 0.251 0.802 Rsquare = 0.048 (max possible = 4.51e-01 ) Likelihood ratio test p = 4.81e-01 Wald test p = 6.26e-01 Score (logrank) test p = 5.25e-01 AACS in UCEC (n=545): Model: Surv(OS, EVENT) ~ `AACS` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS -0.364 0.695 0.237 0.437 1.107 -1.533 0.125 Age 0.047 1.048 0.016 1.017 1.081 3.010 0.003 ** RaceBlack -0.504 0.604 0.798 0.126 2.886 -0.632 0.527 RaceWhite -0.587 0.556 0.750 0.128 2.417 -0.783 0.434 Purity 0.437 1.548 0.645 0.437 5.484 0.677 0.499 Rsquare = 0.046 (max possible = 7.81e-01 ) Likelihood ratio test p = 1.95e-02 Wald test p = 2.13e-02 Score (logrank) test p = 1.97e-02 AACS in UCS (n=57): Model: Surv(OS, EVENT) ~ `AACS` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.058 1.059 0.326 0.559 2.007 0.177 0.859 Age 0.043 1.044 0.024 0.995 1.095 1.749 0.080 · RaceBlack 17.599 43985888.882 6472.483 0.000 Inf 0.003 0.998 RaceWhite 17.853 56689104.477 6472.483 0.000 Inf 0.003 0.998 Purity -0.845 0.429 1.068 0.053 3.485 -0.791 0.429 Rsquare = 0.119 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.51e-01 Wald test p = 3.61e-01 Score (logrank) test p = 2.65e-01 AACS in UVM (n=80): Model: Surv(OS, EVENT) ~ `AACS` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif AACS 0.950 2.586 0.462 1.045 6.397 2.056 0.040 * Age 0.033 1.034 0.019 0.996 1.073 1.740 0.082 · Gendermale 0.402 1.495 0.480 0.583 3.834 0.838 0.402 Stage3 -0.084 0.920 0.539 0.320 2.647 -0.155 0.877 Stage4 3.828 45.963 1.213 4.264 495.398 3.156 0.002 ** Purity 1.702 5.487 1.272 0.453 66.425 1.338 0.181 Rsquare = 0.295 (max possible = 8.72e-01 ) Likelihood ratio test p = 1.47e-04 Wald test p = 1.29e-03 Score (logrank) test p = 5.22e-10 ACSL3 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.116 8.91000e-01 0.266 0.529 1.501 -0.435 0.664 Age 0.004 1.00400e+00 0.014 0.977 1.031 0.263 0.793 Gendermale 0.340 1.40500e+00 0.420 0.617 3.199 0.809 0.418 RaceBlack 0.064 1.06600e+00 12009.674 0.000 Inf 0.000 1.000 RaceWhite 16.957 2.31456e+07 10230.401 0.000 Inf 0.002 0.999 Purity 2.912 1.83930e+01 2.331 0.191 1773.110 1.249 0.212 Rsquare = 0.069 (max possible = 9.38e-01 ) Likelihood ratio test p = 5.99e-01 Wald test p = 8.81e-01 Score (logrank) test p = 7.3e-01 ACSL3 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.010 0.990 0.127 0.771 1.270 -0.082 0.934 Age 0.033 1.034 0.009 1.017 1.052 3.873 0.000 *** Gendermale -0.172 0.842 0.179 0.593 1.195 -0.963 0.335 RaceBlack 0.713 2.041 0.447 0.849 4.902 1.595 0.111 RaceWhite 0.117 1.124 0.355 0.561 2.253 0.331 0.741 Stage2 14.506 1994026.183 1860.408 0.000 Inf 0.008 0.994 Stage3 14.939 3075625.759 1860.408 0.000 Inf 0.008 0.994 Stage4 15.482 5290955.104 1860.408 0.000 Inf 0.008 0.993 Purity 0.142 1.152 0.338 0.593 2.236 0.418 0.676 Rsquare = 0.13 (max possible = 9.91e-01 ) Likelihood ratio test p = 2.02e-07 Wald test p = 1.22e-06 Score (logrank) test p = 3.4e-07 ACSL3 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.076 1.079 0.120 0.854 1.365 0.639 0.523 Age 0.036 1.037 0.008 1.022 1.052 4.769 0.000 *** Gendermale 0.047 1.048 1.007 0.146 7.550 0.047 0.963 RaceBlack 0.014 1.014 0.619 0.301 3.414 0.023 0.982 RaceWhite -0.246 0.782 0.597 0.243 2.520 -0.412 0.681 Stage2 0.402 1.495 0.304 0.825 2.712 1.325 0.185 Stage3 1.179 3.251 0.313 1.760 6.007 3.765 0.000 *** Stage4 2.536 12.630 0.390 5.883 27.118 6.505 0.000 *** Purity 0.474 1.606 0.426 0.697 3.698 1.113 0.266 Rsquare = 0.081 (max possible = 7.85e-01 ) Likelihood ratio test p = 2.06e-12 Wald test p = 7.31e-16 Score (logrank) test p = 8.29e-22 ACSL3 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.429 6.510000e-01 0.264 0.388 1.092 -1.625 0.104 Age 0.013 1.013000e+00 0.017 0.979 1.048 0.737 0.461 RaceBlack -0.993 3.700000e-01 1.101 0.043 3.207 -0.902 0.367 RaceWhite -1.137 3.210000e-01 1.103 0.037 2.785 -1.031 0.303 Stage2 18.702 1.324831e+08 6506.558 0.000 Inf 0.003 0.998 Stage3 20.240 6.167440e+08 6506.558 0.000 Inf 0.003 0.998 Stage4 21.588 2.374293e+09 6506.559 0.000 Inf 0.003 0.997 Purity 0.992 2.698000e+00 0.927 0.438 16.606 1.070 0.284 Rsquare = 0.17 (max possible = 7.18e-01 ) Likelihood ratio test p = 1.75e-04 Wald test p = 4.23e-03 Score (logrank) test p = 1.7e-06 ACSL3 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.477 1.611000e+00 0.450 0.667 3.891 1.061 0.289 Age 0.021 1.021000e+00 0.029 0.964 1.082 0.708 0.479 RaceBlack -2.753 6.400000e-02 1.796 0.002 2.153 -1.533 0.125 RaceWhite -1.660 1.900000e-01 1.441 0.011 3.204 -1.152 0.249 Stage2 18.083 7.135797e+07 14919.974 0.000 Inf 0.001 0.999 Stage3 20.036 5.030044e+08 14919.974 0.000 Inf 0.001 0.999 Stage4 52.263 4.982125e+22 1946915.244 0.000 Inf 0.000 1.000 Purity 3.425 3.073000e+01 2.353 0.305 3093.198 1.456 0.145 Rsquare = 0.382 (max possible = 6.68e-01 ) Likelihood ratio test p = 4.1e-04 Wald test p = 1e+00 Score (logrank) test p = 2.65e-14 ACSL3 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.215 1.240 0.209 0.823 1.870 1.028 0.304 Age 0.050 1.051 0.012 1.026 1.076 4.131 0.000 *** Gendermale -15.338 0.000 3473.926 0.000 Inf -0.004 0.996 RaceBlack -0.514 0.598 1.178 0.059 6.017 -0.436 0.663 RaceWhite 0.094 1.099 1.043 0.142 8.485 0.090 0.928 Stage2 0.297 1.345 0.375 0.645 2.808 0.790 0.429 Stage3 0.852 2.345 0.394 1.083 5.078 2.162 0.031 * Stage4 2.106 8.211 0.593 2.569 26.250 3.551 0.000 *** Purity 0.215 1.240 0.624 0.365 4.214 0.344 0.731 Rsquare = 0.072 (max possible = 6.81e-01 ) Likelihood ratio test p = 6.8e-05 Wald test p = 1.83e-05 Score (logrank) test p = 3.23e-07 ACSL3 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.080 0.923 0.333 0.480 1.774 -0.240 0.811 Age 0.049 1.050 0.021 1.007 1.095 2.299 0.021 * Gendermale 0.953 2.594 1.108 0.296 22.741 0.861 0.390 RaceBlack 16.499 14635069.101 6438.753 0.000 Inf 0.003 0.998 RaceWhite 15.882 7898745.522 6438.753 0.000 Inf 0.002 0.998 Stage2 0.710 2.034 1.079 0.246 16.844 0.658 0.510 Stage3 1.621 5.056 1.064 0.629 40.671 1.523 0.128 Stage4 2.048 7.749 1.184 0.761 78.889 1.729 0.084 · Purity 1.066 2.905 1.319 0.219 38.564 0.808 0.419 Rsquare = 0.106 (max possible = 6.98e-01 ) Likelihood ratio test p = 4.13e-02 Wald test p = 7.14e-02 Score (logrank) test p = 2.43e-02 ACSL3 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.239 1.270 0.197 0.863 1.869 1.212 0.226 Age 0.010 1.010 0.010 0.991 1.030 1.052 0.293 RaceBlack 1.155 3.174 1.071 0.389 25.915 1.078 0.281 RaceWhite 0.922 2.514 1.019 0.341 18.503 0.905 0.365 Purity 0.486 1.626 0.737 0.383 6.895 0.659 0.510 Rsquare = 0.02 (max possible = 8.91e-01 ) Likelihood ratio test p = 4.65e-01 Wald test p = 4.88e-01 Score (logrank) test p = 4.77e-01 ACSL3 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.479 1.614 0.554 0.545 4.776 0.865 0.387 Age 0.019 1.019 0.022 0.977 1.063 0.867 0.386 Gendermale 0.217 1.243 0.562 0.413 3.739 0.386 0.699 RaceBlack -0.411 0.663 1.469 0.037 11.802 -0.280 0.780 RaceWhite -1.061 0.346 0.876 0.062 1.929 -1.210 0.226 Stage2 0.657 1.929 0.672 0.517 7.196 0.978 0.328 Stage3 -14.869 0.000 7009.656 0.000 Inf -0.002 0.998 Stage4 0.650 1.916 0.708 0.478 7.681 0.918 0.359 Purity 2.135 8.455 1.540 0.413 173.131 1.386 0.166 Rsquare = 0.228 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.09e-01 Wald test p = 5.84e-01 Score (logrank) test p = 4.11e-01 ACSL3 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.035 0.966 0.180 0.679 1.374 -0.193 0.847 Age 0.024 1.024 0.011 1.001 1.047 2.082 0.037 * Gendermale 0.220 1.246 0.271 0.732 2.120 0.811 0.417 RaceBlack -0.417 0.659 0.828 0.130 3.338 -0.504 0.614 RaceWhite -0.449 0.638 0.776 0.140 2.920 -0.579 0.563 Stage2 0.207 1.230 0.562 0.409 3.705 0.368 0.713 Stage3 0.805 2.237 0.549 0.762 6.566 1.466 0.143 Stage4 1.886 6.592 0.552 2.232 19.465 3.414 0.001 ** Purity -0.225 0.798 0.598 0.247 2.579 -0.376 0.707 Rsquare = 0.109 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.58e-04 Wald test p = 1.53e-04 Score (logrank) test p = 2.28e-05 ACSL3 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 1.172 3.229 0.869 0.588 17.729 1.349 0.177 Age -0.013 0.987 0.045 0.903 1.078 -0.296 0.767 Gendermale 0.327 1.387 1.109 0.158 12.203 0.295 0.768 RaceBlack -0.087 0.917 1.742 0.030 27.841 -0.050 0.960 RaceWhite -2.856 0.058 1.489 0.003 1.065 -1.918 0.055 · Purity -2.383 0.092 2.190 0.001 6.746 -1.088 0.277 Rsquare = 0.173 (max possible = 5.58e-01 ) Likelihood ratio test p = 2.53e-01 Wald test p = 4.21e-01 Score (logrank) test p = 2.48e-01 ACSL3 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.227 0.797 0.264 0.475 1.338 -0.858 0.391 Age 0.011 1.011 0.014 0.983 1.039 0.749 0.454 Gendermale 0.492 1.636 0.538 0.570 4.696 0.915 0.360 RaceBlack 0.186 1.205 1.082 0.145 10.038 0.172 0.863 RaceWhite -0.125 0.883 0.452 0.364 2.139 -0.276 0.782 Stage2 0.746 2.108 0.657 0.582 7.637 1.136 0.256 Stage3 1.466 4.334 0.669 1.168 16.078 2.192 0.028 * Stage4 2.967 19.431 0.786 4.160 90.761 3.773 0.000 *** Purity 0.319 1.376 0.781 0.298 6.357 0.409 0.683 Rsquare = 0.145 (max possible = 9.32e-01 ) Likelihood ratio test p = 8.89e-03 Wald test p = 4.18e-03 Score (logrank) test p = 3.39e-04 ACSL3 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.014 0.986 0.124 0.772 1.258 -0.116 0.908 Age 0.030 1.030 0.008 1.013 1.047 3.555 0.000 *** Gendermale -0.099 0.906 0.215 0.594 1.381 -0.459 0.646 RaceBlack 0.524 1.688 0.727 0.406 7.025 0.720 0.472 RaceWhite -0.243 0.784 0.615 0.235 2.616 -0.396 0.692 Purity -1.078 0.340 0.538 0.118 0.978 -2.002 0.045 * Rsquare = 0.129 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.78e-03 Wald test p = 6.77e-03 Score (logrank) test p = 5.88e-03 ACSL3 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.274 1.316 0.136 1.008 1.716 2.022 0.043 * Age 0.021 1.021 0.008 1.006 1.037 2.804 0.005 ** Gendermale -0.257 0.774 0.172 0.552 1.085 -1.488 0.137 RaceBlack 0.124 1.132 0.559 0.378 3.389 0.222 0.824 RaceWhite -0.261 0.770 0.511 0.283 2.098 -0.510 0.610 Stage2 0.620 1.860 0.544 0.641 5.398 1.141 0.254 Stage3 0.909 2.481 0.537 0.865 7.115 1.691 0.091 · Stage4 1.269 3.559 0.510 1.310 9.670 2.489 0.013 * Purity -0.035 0.965 0.363 0.474 1.965 -0.097 0.923 Rsquare = 0.079 (max possible = 9.89e-01 ) Likelihood ratio test p = 1.01e-04 Wald test p = 2.33e-04 Score (logrank) test p = 1.69e-04 ACSL3 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.629 1.875000e+00 0.370 0.907 3.876 1.698 0.090 · Age 0.013 1.013000e+00 0.025 0.964 1.065 0.527 0.598 Gendermale -0.143 8.670000e-01 0.538 0.302 2.486 -0.266 0.790 RaceBlack 19.469 2.852642e+08 12344.040 0.000 Inf 0.002 0.999 RaceWhite 18.487 1.068761e+08 12344.040 0.000 Inf 0.001 0.999 Stage2 17.279 3.193985e+07 5422.088 0.000 Inf 0.003 0.997 Stage3 16.248 1.139159e+07 5422.088 0.000 Inf 0.003 0.998 Stage4 17.338 3.386556e+07 5422.088 0.000 Inf 0.003 0.997 Purity -1.643 1.930000e-01 1.124 0.021 1.752 -1.461 0.144 Rsquare = 0.127 (max possible = 9.17e-01 ) Likelihood ratio test p = 4.54e-01 Wald test p = 7.95e-01 Score (logrank) test p = 6.56e-01 ACSL3 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.224 1.251 0.147 0.938 1.669 1.525 0.127 Age 0.026 1.026 0.008 1.009 1.043 3.064 0.002 ** Gendermale -0.285 0.752 0.183 0.526 1.076 -1.558 0.119 RaceBlack -0.045 0.956 0.565 0.316 2.894 -0.079 0.937 RaceWhite -0.422 0.656 0.513 0.240 1.792 -0.823 0.410 Stage2 0.388 1.474 0.554 0.498 4.366 0.701 0.483 Stage3 0.800 2.225 0.543 0.768 6.449 1.473 0.141 Stage4 1.176 3.242 0.512 1.188 8.849 2.296 0.022 * Purity 0.197 1.217 0.397 0.559 2.650 0.496 0.620 Rsquare = 0.091 (max possible = 9.89e-01 ) Likelihood ratio test p = 1.32e-04 Wald test p = 2.97e-04 Score (logrank) test p = 2.29e-04 ACSL3 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ACSL3 -0.114 8.920000e-01 0.455 0.366 2.175000e+00 -0.250 0.802 Age 0.076 1.079000e+00 0.029 1.019 1.142000e+00 2.622 0.009 Gendermale -0.943 3.900000e-01 0.729 0.093 1.625000e+00 -1.294 0.196 RaceBlack -17.254 0.000000e+00 6245.209 0.000 Inf -0.003 0.998 RaceWhite -2.113 1.210000e-01 1.161 0.012 1.177000e+00 -1.819 0.069 Stage2 16.098 9.805486e+06 0.849 1858193.142 5.174250e+07 18.969 0.000 Stage3 17.257 3.123699e+07 0.778 6799816.795 1.434964e+08 22.183 0.000 Stage4 19.706 3.616852e+08 0.903 61640937.007 2.122229e+09 21.828 0.000 Purity 1.023 2.781000e+00 3.674 0.002 3.726032e+03 0.278 0.781 signif ACSL3 Age ** Gendermale RaceBlack RaceWhite · Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.346 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.52e-03 Wald test p = 5.79e-283 Score (logrank) test p = 1.07e-08 ACSL3 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.134 0.875 0.158 0.642 1.192 -0.847 0.397 Age 0.034 1.035 0.008 1.018 1.052 4.065 0.000 *** Gendermale -0.105 0.900 0.186 0.626 1.296 -0.564 0.572 RaceBlack 0.265 1.303 1.059 0.163 10.390 0.250 0.803 RaceWhite 0.257 1.293 1.022 0.174 9.592 0.251 0.802 Stage2 0.218 1.244 0.344 0.633 2.443 0.634 0.526 Stage3 0.789 2.202 0.231 1.399 3.464 3.413 0.001 ** Stage4 1.733 5.657 0.218 3.693 8.666 7.962 0.000 *** Purity -0.060 0.942 0.373 0.454 1.956 -0.160 0.873 Rsquare = 0.175 (max possible = 9.65e-01 ) Likelihood ratio test p = 7.47e-15 Wald test p = 5.81e-15 Score (logrank) test p = 3.19e-18 ACSL3 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.499 1.646 0.268 0.973 2.784 1.859 0.063 · Age 0.012 1.012 0.016 0.981 1.043 0.749 0.454 Gendermale -0.479 0.620 0.391 0.288 1.334 -1.223 0.221 RaceBlack -1.862 0.155 1.201 0.015 1.636 -1.550 0.121 RaceWhite -1.760 0.172 1.188 0.017 1.766 -1.481 0.139 Stage2 -0.259 0.772 1.059 0.097 6.152 -0.245 0.807 Stage3 1.760 5.812 0.435 2.480 13.620 4.050 0.000 *** Stage4 2.826 16.877 0.521 6.083 46.826 5.427 0.000 *** Purity -0.325 0.723 0.741 0.169 3.089 -0.438 0.661 Rsquare = 0.176 (max possible = 7.58e-01 ) Likelihood ratio test p = 2.63e-06 Wald test p = 1.25e-06 Score (logrank) test p = 1.84e-10 ACSL3 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.074 1.077 0.197 0.732 1.586 0.378 0.706 Age 0.038 1.039 0.008 1.022 1.055 4.649 0.000 *** Gendermale -0.143 0.867 0.213 0.571 1.316 -0.671 0.502 RaceBlack -0.292 0.747 1.115 0.084 6.643 -0.262 0.793 RaceWhite -0.676 0.509 1.021 0.069 3.766 -0.662 0.508 Rsquare = 0.156 (max possible = 9.96e-01 ) Likelihood ratio test p = 1.19e-04 Wald test p = 3.77e-04 Score (logrank) test p = 2.76e-04 ACSL3 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.252 1.287 0.163 0.935 1.771 1.549 0.121 Age 0.060 1.062 0.008 1.046 1.078 7.793 0.000 *** Gendermale 0.118 1.125 0.196 0.767 1.650 0.601 0.548 RaceBlack 15.342 4601194.433 2002.697 0.000 Inf 0.008 0.994 RaceWhite 15.405 4901128.472 2002.697 0.000 Inf 0.008 0.994 Purity -0.930 0.394 0.402 0.179 0.868 -2.312 0.021 * Rsquare = 0.141 (max possible = 9.07e-01 ) Likelihood ratio test p = 3.7e-13 Wald test p = 5.23e-13 Score (logrank) test p = 2.98e-14 ACSL3 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.275 1.316 0.121 1.038 1.668 2.271 0.023 * Age 0.014 1.014 0.008 0.998 1.030 1.682 0.093 · Gendermale -0.098 0.906 0.227 0.581 1.415 -0.433 0.665 RaceBlack 0.960 2.612 0.490 1.000 6.821 1.960 0.050 · RaceWhite 0.000 1.000 0.235 0.631 1.586 0.002 0.999 Stage2 0.294 1.342 0.262 0.803 2.240 1.123 0.261 Stage3 0.906 2.475 0.236 1.558 3.933 3.837 0.000 *** Stage4 1.511 4.532 0.620 1.343 15.289 2.436 0.015 * Purity 0.661 1.936 0.462 0.783 4.788 1.430 0.153 Rsquare = 0.1 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.61e-04 Wald test p = 1.04e-04 Score (logrank) test p = 3.59e-05 ACSL3 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.266 1.305 0.115 1.041 1.636 2.305 0.021 * Age 0.006 1.006 0.009 0.988 1.024 0.606 0.545 Gendermale -0.010 0.990 0.169 0.711 1.379 -0.057 0.955 RaceBlack 16.235 11244139.963 1922.873 0.000 Inf 0.008 0.993 RaceWhite 16.319 12229626.186 1922.873 0.000 Inf 0.008 0.993 Stage2 0.873 2.394 0.201 1.613 3.551 4.337 0.000 *** Stage3 0.981 2.667 0.218 1.739 4.090 4.496 0.000 *** Stage4 0.880 2.411 0.339 1.242 4.682 2.599 0.009 ** Purity 0.455 1.576 0.349 0.795 3.122 1.303 0.192 Rsquare = 0.108 (max possible = 9.74e-01 ) Likelihood ratio test p = 2.6e-07 Wald test p = 3.52e-06 Score (logrank) test p = 3.59e-07 ACSL3 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.070 1.073 0.140 0.815 1.412 0.500 0.617 Age 0.016 1.016 0.009 0.998 1.035 1.735 0.083 · Gendermale 0.430 1.537 0.194 1.051 2.247 2.215 0.027 * RaceBlack 0.004 1.004 0.606 0.306 3.292 0.007 0.994 RaceWhite -0.514 0.598 0.562 0.199 1.801 -0.914 0.361 Stage2 0.200 1.222 0.188 0.845 1.766 1.065 0.287 Stage3 0.607 1.834 0.214 1.205 2.793 2.828 0.005 ** Stage4 0.752 2.122 0.793 0.448 10.040 0.949 0.343 Purity -0.329 0.720 0.367 0.351 1.477 -0.896 0.370 Rsquare = 0.051 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.23e-02 Wald test p = 1.72e-02 Score (logrank) test p = 1.47e-02 ACSL3 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.208 1.231 0.230 0.784 1.933 0.904 0.366 Age 0.017 1.018 0.016 0.986 1.050 1.086 0.277 Gendermale -0.297 0.743 0.354 0.371 1.485 -0.841 0.400 RaceBlack -0.219 0.803 1.580 0.036 17.759 -0.139 0.890 RaceWhite -0.553 0.575 1.047 0.074 4.481 -0.528 0.598 Stage2 -0.233 0.792 0.467 0.317 1.977 -0.500 0.617 Stage3 -0.071 0.932 0.419 0.410 2.119 -0.168 0.866 Stage4 -0.172 0.842 0.480 0.329 2.156 -0.358 0.721 Purity -0.729 0.482 0.555 0.163 1.430 -1.315 0.189 Rsquare = 0.069 (max possible = 9.98e-01 ) Likelihood ratio test p = 7.33e-01 Wald test p = 7.14e-01 Score (logrank) test p = 7.03e-01 ACSL3 in OV (n=303): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.212 1.237 0.157 0.909 1.682 1.354 0.176 Age 0.035 1.035 0.008 1.019 1.052 4.197 0.000 *** RaceBlack -0.148 0.863 0.580 0.277 2.691 -0.254 0.799 RaceWhite -0.256 0.774 0.520 0.279 2.144 -0.493 0.622 Purity -0.510 0.600 0.670 0.161 2.233 -0.761 0.447 Rsquare = 0.088 (max possible = 9.97e-01 ) Likelihood ratio test p = 5.24e-04 Wald test p = 4.82e-04 Score (logrank) test p = 3.88e-04 ACSL3 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.019 0.981 0.178 0.692 1.391 -0.108 0.914 Age 0.022 1.022 0.011 1.000 1.044 1.998 0.046 * Gendermale -0.215 0.807 0.216 0.528 1.233 -0.993 0.321 RaceBlack -0.018 0.982 0.739 0.231 4.181 -0.024 0.981 RaceWhite 0.357 1.429 0.473 0.565 3.614 0.755 0.450 Stage2 0.624 1.867 0.437 0.792 4.399 1.428 0.153 Stage3 -0.246 0.782 1.094 0.092 6.675 -0.224 0.822 Stage4 0.240 1.271 0.825 0.253 6.399 0.291 0.771 Purity -0.671 0.511 0.408 0.230 1.138 -1.644 0.100 Rsquare = 0.089 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.31e-02 Wald test p = 1.19e-01 Score (logrank) test p = 1.13e-01 ACSL3 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.318 0.728 0.598 0.225 2.350 -0.531 0.595 Age 0.040 1.041 0.029 0.983 1.101 1.379 0.168 Gendermale 1.545 4.687 0.941 0.741 29.636 1.642 0.101 RaceBlack -0.065 0.937 19313.437 0.000 Inf 0.000 1.000 RaceWhite 17.335 33761816.362 15382.463 0.000 Inf 0.001 0.999 Purity 5.382 217.564 3.360 0.300 157681.510 1.602 0.109 Rsquare = 0.056 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.47e-01 Wald test p = 3.89e-01 Score (logrank) test p = 2.94e-01 ACSL3 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.398 1.489 0.368 0.724 3.061 1.082 0.279 Age 0.021 1.022 0.058 0.912 1.144 0.371 0.711 RaceBlack 14.998 3261322.762 6907.212 0.000 Inf 0.002 0.998 RaceWhite 16.275 11694059.280 6907.212 0.000 Inf 0.002 0.998 Purity 0.919 2.508 1.381 0.167 37.549 0.666 0.505 Rsquare = 0.01 (max possible = 1.83e-01 ) Likelihood ratio test p = 5.61e-01 Wald test p = 6.84e-01 Score (logrank) test p = 6.1e-01 ACSL3 in READ (n=166): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.362 1.437 0.466 0.577 3.580 0.778 0.437 Age 0.120 1.127 0.048 1.026 1.239 2.484 0.013 * Gendermale -0.433 0.648 0.695 0.166 2.531 -0.624 0.533 RaceBlack 13.226 554387.142 10245.042 0.000 Inf 0.001 0.999 RaceWhite 12.072 174868.540 10245.042 0.000 Inf 0.001 0.999 Stage2 -1.775 0.169 1.259 0.014 2.000 -1.410 0.159 Stage3 -0.371 0.690 0.906 0.117 4.070 -0.410 0.682 Stage4 0.041 1.042 0.985 0.151 7.181 0.042 0.967 Purity 0.397 1.487 1.389 0.098 22.637 0.285 0.775 Rsquare = 0.215 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.04e-02 Wald test p = 2.7e-01 Score (logrank) test p = 4.89e-02 ACSL3 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.028 0.972 0.153 0.721 1.312 -0.183 0.855 Age 0.023 1.023 0.008 1.006 1.040 2.721 0.007 ** Gendermale -0.013 0.987 0.223 0.638 1.527 -0.059 0.953 RaceBlack -0.136 0.873 1.088 0.104 7.362 -0.125 0.901 RaceWhite -0.473 0.623 1.023 0.084 4.633 -0.462 0.644 Purity 0.954 2.596 0.575 0.841 8.015 1.659 0.097 · Rsquare = 0.043 (max possible = 9.75e-01 ) Likelihood ratio test p = 1.18e-01 Wald test p = 1.59e-01 Score (logrank) test p = 1.6e-01 ACSL3 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.154 0.857 0.071 0.747 0.985 -2.178 0.029 * Age 0.018 1.018 0.005 1.008 1.029 3.424 0.001 ** Gendermale -0.016 0.984 0.158 0.722 1.341 -0.104 0.917 RaceWhite -1.131 0.323 0.408 0.145 0.718 -2.771 0.006 ** Stage2 0.276 1.317 0.219 0.857 2.024 1.258 0.209 Stage3 0.642 1.901 0.206 1.271 2.844 3.125 0.002 ** Stage4 1.382 3.984 0.353 1.996 7.951 3.920 0.000 *** Purity 1.022 2.779 0.338 1.434 5.387 3.027 0.002 ** Rsquare = 0.134 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.85e-09 Wald test p = 1.24e-09 Score (logrank) test p = 1.44e-10 ACSL3 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.054 9.470000e-01 0.167 0.683 1.313 -0.326 0.744 Age 0.012 1.012000e+00 0.016 0.980 1.044 0.716 0.474 Gendermale 0.233 1.262000e+00 0.437 0.536 2.970 0.533 0.594 RaceWhite -1.259 2.840000e-01 0.618 0.085 0.955 -2.035 0.042 * Stage2 17.438 3.743692e+07 6201.533 0.000 Inf 0.003 0.998 Stage3 17.901 5.947222e+07 6201.533 0.000 Inf 0.003 0.998 Stage4 20.122 5.483660e+08 6201.534 0.000 Inf 0.003 0.997 Purity 0.348 1.417000e+00 0.974 0.210 9.564 0.358 0.721 Rsquare = 0.147 (max possible = 8.69e-01 ) Likelihood ratio test p = 5.93e-02 Wald test p = 5.16e-02 Score (logrank) test p = 4.31e-03 ACSL3 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.157 0.854 0.080 0.731 0.998 -1.979 0.048 * Age 0.020 1.020 0.006 1.009 1.032 3.550 0.000 *** Gendermale -0.023 0.977 0.173 0.696 1.372 -0.132 0.895 RaceWhite -0.837 0.433 0.611 0.131 1.435 -1.370 0.171 Stage2 0.151 1.163 0.231 0.739 1.829 0.652 0.514 Stage3 0.605 1.831 0.211 1.211 2.769 2.868 0.004 ** Stage4 1.155 3.174 0.401 1.448 6.960 2.884 0.004 ** Purity 1.129 3.093 0.368 1.505 6.357 3.072 0.002 ** Rsquare = 0.145 (max possible = 9.95e-01 ) Likelihood ratio test p = 2.07e-07 Wald test p = 2.8e-07 Score (logrank) test p = 1.03e-07 ACSL3 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.032 0.968 0.170 0.693 1.352 -0.190 0.849 Age 0.026 1.027 0.010 1.006 1.047 2.578 0.010 * Gendermale 0.125 1.133 0.208 0.754 1.703 0.601 0.548 RaceBlack 0.279 1.322 0.451 0.546 3.202 0.618 0.537 RaceWhite 0.097 1.102 0.244 0.682 1.779 0.396 0.692 Stage2 0.489 1.631 0.390 0.760 3.501 1.254 0.210 Stage3 0.923 2.517 0.364 1.233 5.139 2.536 0.011 * Stage4 1.320 3.744 0.504 1.394 10.052 2.620 0.009 ** Purity -0.549 0.577 0.382 0.273 1.221 -1.438 0.150 Rsquare = 0.069 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.36e-02 Wald test p = 1.84e-02 Score (logrank) test p = 1.49e-02 ACSL3 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -2.882 0.056 27781.649 0 Inf 0.000 1.000 Age -1.821 0.162 1692.767 0 Inf -0.001 0.999 RaceBlack 7.722 2257.198 20527583.666 0 Inf 0.000 1.000 RaceWhite -35.364 0.000 20668052.619 0 Inf 0.000 1.000 Stage2 4.307 74.212 42058.911 0 Inf 0.000 1.000 Stage3 14.584 2157220.231 127125.935 0 Inf 0.000 1.000 Purity -4.628 0.010 247022.377 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.25e-03 ACSL3 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.101 1.106 0.441 0.466 2.626 0.229 0.818 Age 0.146 1.157 0.028 1.094 1.223 5.128 0.000 *** Gendermale -0.082 0.922 0.637 0.264 3.212 -0.128 0.898 RaceBlack 16.839 20566311.002 6038.022 0.000 Inf 0.003 0.998 RaceWhite 16.651 17033023.329 6038.022 0.000 Inf 0.003 0.998 Stage2 -0.112 0.894 1.159 0.092 8.673 -0.097 0.923 Stage3 0.287 1.333 0.886 0.235 7.559 0.324 0.746 Stage4 1.708 5.516 0.982 0.805 37.790 1.739 0.082 · Purity 2.210 9.112 1.103 1.048 79.198 2.003 0.045 * Rsquare = 0.149 (max possible = 3.47e-01 ) Likelihood ratio test p = 2.48e-10 Wald test p = 3.15e-04 Score (logrank) test p = 1.07e-10 ACSL3 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 -0.635 0.530 0.397 0.243 1.155 -1.597 0.110 Age 0.062 1.064 0.034 0.995 1.138 1.818 0.069 · Gendermale -0.181 0.835 0.754 0.190 3.659 -0.240 0.811 RaceBlack -16.907 0.000 11164.780 0.000 Inf -0.002 0.999 RaceWhite 0.238 1.269 1.097 0.148 10.903 0.217 0.828 Purity 0.541 1.719 1.132 0.187 15.795 0.478 0.632 Rsquare = 0.063 (max possible = 4.51e-01 ) Likelihood ratio test p = 2.87e-01 Wald test p = 3.75e-01 Score (logrank) test p = 2.63e-01 ACSL3 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.092 1.097 0.201 0.740 1.626 0.459 0.647 Age 0.050 1.052 0.016 1.020 1.085 3.183 0.001 ** RaceBlack -0.406 0.667 0.794 0.141 3.157 -0.511 0.609 RaceWhite -0.524 0.592 0.745 0.137 2.551 -0.703 0.482 Purity 0.459 1.583 0.648 0.445 5.635 0.709 0.478 Rsquare = 0.039 (max possible = 7.81e-01 ) Likelihood ratio test p = 4.63e-02 Wald test p = 5.47e-02 Score (logrank) test p = 5.35e-02 ACSL3 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.117 1.124 0.283 0.645 1.958 0.412 0.680 Age 0.044 1.045 0.024 0.997 1.095 1.821 0.069 · RaceBlack 17.555 42055653.800 6489.939 0.000 Inf 0.003 0.998 RaceWhite 17.761 51723760.738 6489.939 0.000 Inf 0.003 0.998 Purity -0.900 0.407 1.066 0.050 3.287 -0.844 0.399 Rsquare = 0.122 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.4e-01 Wald test p = 3.36e-01 Score (logrank) test p = 2.46e-01 ACSL3 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ACSL3` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL3 0.407 1.502 0.255 0.911 2.478 1.594 0.111 Age 0.040 1.041 0.018 1.004 1.079 2.173 0.030 * Gendermale 0.367 1.443 0.484 0.559 3.725 0.758 0.448 Stage3 0.141 1.152 0.510 0.424 3.130 0.277 0.781 Stage4 3.711 40.901 1.209 3.826 437.296 3.070 0.002 ** Purity 1.846 6.331 1.241 0.556 72.042 1.487 0.137 Rsquare = 0.278 (max possible = 8.72e-01 ) Likelihood ratio test p = 3.33e-04 Wald test p = 1.7e-03 Score (logrank) test p = 1.2e-09 ACSL4 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.403 0.668 0.170 0.479 0.933 -2.368 0.018 * Age 0.007 1.007 0.013 0.981 1.033 0.490 0.624 Gendermale 0.247 1.281 0.421 0.561 2.924 0.587 0.557 RaceBlack -0.302 0.740 13090.892 0.000 Inf 0.000 1.000 RaceWhite 16.365 12800739.336 11211.189 0.000 Inf 0.001 0.999 Purity 1.351 3.860 2.337 0.040 376.475 0.578 0.563 Rsquare = 0.141 (max possible = 9.38e-01 ) Likelihood ratio test p = 1.38e-01 Wald test p = 1.96e-01 Score (logrank) test p = 1.26e-01 ACSL4 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.119 0.888 0.084 0.753 1.047 -1.414 0.157 Age 0.032 1.033 0.009 1.016 1.051 3.762 0.000 *** Gendermale -0.170 0.844 0.179 0.595 1.198 -0.948 0.343 RaceBlack 0.743 2.102 0.446 0.877 5.038 1.666 0.096 · RaceWhite 0.160 1.173 0.355 0.585 2.353 0.450 0.653 Stage2 14.378 1755338.855 1875.844 0.000 Inf 0.008 0.994 Stage3 14.795 2663420.238 1875.844 0.000 Inf 0.008 0.994 Stage4 15.314 4473824.403 1875.844 0.000 Inf 0.008 0.993 Purity 0.066 1.068 0.340 0.549 2.077 0.193 0.847 Rsquare = 0.135 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.38e-08 Wald test p = 4.77e-07 Score (logrank) test p = 1.25e-07 ACSL4 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.138 1.148 0.089 0.964 1.367 1.549 0.121 Age 0.037 1.038 0.008 1.022 1.053 4.907 0.000 *** Gendermale 0.130 1.138 1.009 0.158 8.226 0.128 0.898 RaceBlack -0.036 0.965 0.620 0.286 3.254 -0.057 0.954 RaceWhite -0.267 0.766 0.597 0.238 2.466 -0.447 0.655 Stage2 0.421 1.524 0.304 0.840 2.765 1.385 0.166 Stage3 1.202 3.326 0.313 1.800 6.144 3.837 0.000 *** Stage4 2.662 14.321 0.400 6.535 31.383 6.649 0.000 *** Purity 0.707 2.029 0.436 0.863 4.768 1.623 0.105 Rsquare = 0.083 (max possible = 7.85e-01 ) Likelihood ratio test p = 8.44e-13 Wald test p = 1.47e-16 Score (logrank) test p = 2.35e-22 ACSL4 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.272 7.620000e-01 0.208 0.507 1.144 -1.312 0.190 Age 0.017 1.017000e+00 0.018 0.982 1.053 0.929 0.353 RaceBlack -0.880 4.150000e-01 1.141 0.044 3.880 -0.771 0.441 RaceWhite -1.141 3.200000e-01 1.165 0.033 3.134 -0.979 0.327 Stage2 18.568 1.158348e+08 6468.707 0.000 Inf 0.003 0.998 Stage3 20.068 5.195148e+08 6468.707 0.000 Inf 0.003 0.998 Stage4 21.310 1.797872e+09 6468.707 0.000 Inf 0.003 0.997 Purity 0.667 1.948000e+00 0.989 0.281 13.524 0.675 0.500 Rsquare = 0.165 (max possible = 7.18e-01 ) Likelihood ratio test p = 2.61e-04 Wald test p = 4.19e-03 Score (logrank) test p = 2.48e-06 ACSL4 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.362 1.436000e+00 0.719 0.350 5.880 0.503 0.615 Age 0.042 1.043000e+00 0.035 0.974 1.118 1.209 0.227 RaceBlack -2.919 5.400000e-02 1.816 0.002 1.897 -1.607 0.108 RaceWhite -1.555 2.110000e-01 1.487 0.011 3.893 -1.046 0.296 Stage2 18.196 7.989081e+07 15153.727 0.000 Inf 0.001 0.999 Stage3 19.675 3.505349e+08 15153.727 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 3.268 2.624700e+01 2.301 0.288 2388.000 1.420 0.156 Rsquare = 0.373 (max possible = 6.68e-01 ) Likelihood ratio test p = 2.68e-04 Wald test p = 2.51e-01 Score (logrank) test p = 1.16e-14 ACSL4 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.304 1.356 0.176 0.961 1.912 1.733 0.083 · Age 0.050 1.052 0.012 1.028 1.076 4.312 0.000 *** Gendermale -15.348 0.000 3483.970 0.000 Inf -0.004 0.996 RaceBlack -0.333 0.717 1.176 0.072 7.182 -0.283 0.777 RaceWhite 0.121 1.128 1.035 0.148 8.571 0.117 0.907 Stage2 0.327 1.387 0.374 0.667 2.886 0.876 0.381 Stage3 0.915 2.496 0.394 1.153 5.403 2.322 0.020 * Stage4 2.299 9.967 0.598 3.085 32.198 3.843 0.000 *** Purity 0.793 2.209 0.673 0.591 8.263 1.178 0.239 Rsquare = 0.076 (max possible = 6.81e-01 ) Likelihood ratio test p = 3.05e-05 Wald test p = 5.25e-06 Score (logrank) test p = 1.04e-07 ACSL4 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.334 1.397 0.281 0.805 2.424 1.189 0.234 Age 0.054 1.055 0.021 1.012 1.100 2.545 0.011 * Gendermale 1.319 3.738 1.145 0.396 35.268 1.151 0.250 RaceBlack 16.723 18303424.789 7117.858 0.000 Inf 0.002 0.998 RaceWhite 16.021 9076247.065 7117.858 0.000 Inf 0.002 0.998 Stage2 0.897 2.452 1.092 0.288 20.850 0.821 0.411 Stage3 1.721 5.589 1.069 0.687 45.457 1.609 0.108 Stage4 2.695 14.799 1.299 1.161 188.598 2.075 0.038 * Purity 2.074 7.954 1.583 0.357 177.069 1.310 0.190 Rsquare = 0.114 (max possible = 6.98e-01 ) Likelihood ratio test p = 2.58e-02 Wald test p = 4.31e-02 Score (logrank) test p = 1.46e-02 ACSL4 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.145 1.156 0.138 0.882 1.516 1.050 0.294 Age 0.011 1.011 0.010 0.992 1.031 1.121 0.262 RaceBlack 1.127 3.087 1.070 0.379 25.146 1.053 0.292 RaceWhite 0.853 2.348 1.015 0.321 17.172 0.841 0.401 Purity 0.702 2.018 0.736 0.477 8.544 0.953 0.340 Rsquare = 0.018 (max possible = 8.91e-01 ) Likelihood ratio test p = 5.18e-01 Wald test p = 5.49e-01 Score (logrank) test p = 5.41e-01 ACSL4 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.317 1.373 0.238 0.861 2.191 1.331 0.183 Age 0.022 1.023 0.021 0.982 1.065 1.086 0.278 Gendermale 0.439 1.552 0.564 0.514 4.687 0.779 0.436 RaceBlack -0.047 0.954 1.440 0.057 16.027 -0.033 0.974 RaceWhite -0.957 0.384 0.862 0.071 2.080 -1.110 0.267 Stage2 0.428 1.534 0.686 0.400 5.884 0.624 0.533 Stage3 -15.072 0.000 7127.084 0.000 Inf -0.002 0.998 Stage4 0.837 2.309 0.669 0.623 8.563 1.251 0.211 Purity 2.206 9.076 1.549 0.436 188.998 1.424 0.155 Rsquare = 0.248 (max possible = 9.46e-01 ) Likelihood ratio test p = 3.29e-01 Wald test p = 4.44e-01 Score (logrank) test p = 2.76e-01 ACSL4 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.047 0.954 0.148 0.714 1.276 -0.316 0.752 Age 0.024 1.024 0.011 1.001 1.047 2.071 0.038 * Gendermale 0.215 1.240 0.269 0.732 2.102 0.800 0.424 RaceBlack -0.416 0.659 0.829 0.130 3.349 -0.502 0.616 RaceWhite -0.431 0.650 0.777 0.142 2.978 -0.555 0.579 Stage2 0.206 1.229 0.562 0.408 3.700 0.366 0.714 Stage3 0.802 2.230 0.549 0.760 6.545 1.459 0.144 Stage4 1.893 6.639 0.553 2.246 19.620 3.424 0.001 ** Purity -0.272 0.762 0.618 0.227 2.559 -0.439 0.660 Rsquare = 0.11 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.47e-04 Wald test p = 1.49e-04 Score (logrank) test p = 2.18e-05 ACSL4 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 3.485 32.632 1.608 1.395 763.080 2.167 0.030 * Age -0.015 0.985 0.062 0.873 1.112 -0.239 0.811 Gendermale -0.985 0.373 1.677 0.014 9.990 -0.587 0.557 RaceBlack 1.638 5.147 3.008 0.014 1870.755 0.545 0.586 RaceWhite -4.842 0.008 2.519 0.000 1.100 -1.922 0.055 · Purity -5.378 0.005 3.977 0.000 11.199 -1.352 0.176 Rsquare = 0.362 (max possible = 5.58e-01 ) Likelihood ratio test p = 5.25e-03 Wald test p = 2.52e-01 Score (logrank) test p = 3.03e-02 ACSL4 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.045 1.046 0.182 0.732 1.496 0.249 0.804 Age 0.009 1.009 0.014 0.982 1.037 0.653 0.514 Gendermale 0.491 1.633 0.539 0.568 4.698 0.910 0.363 RaceBlack 0.394 1.482 1.092 0.174 12.611 0.360 0.719 RaceWhite -0.066 0.936 0.449 0.389 2.257 -0.146 0.884 Stage2 0.689 1.992 0.654 0.552 7.182 1.053 0.292 Stage3 1.458 4.298 0.671 1.153 16.025 2.172 0.030 * Stage4 2.857 17.414 0.775 3.812 79.553 3.686 0.000 *** Purity 0.267 1.306 0.795 0.275 6.200 0.336 0.737 Rsquare = 0.141 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.13e-02 Wald test p = 5.17e-03 Score (logrank) test p = 4.32e-04 ACSL4 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.178 0.837 0.201 0.564 1.242 -0.884 0.377 Age 0.030 1.030 0.008 1.014 1.047 3.590 0.000 *** Gendermale -0.099 0.905 0.213 0.596 1.375 -0.466 0.641 RaceBlack 0.525 1.691 0.724 0.409 6.991 0.725 0.468 RaceWhite -0.298 0.742 0.615 0.222 2.478 -0.485 0.628 Purity -1.364 0.256 0.617 0.076 0.856 -2.211 0.027 * Rsquare = 0.134 (max possible = 9.98e-01 ) Likelihood ratio test p = 3.5e-03 Wald test p = 5.28e-03 Score (logrank) test p = 4.62e-03 ACSL4 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.115 1.122 0.083 0.954 1.320 1.389 0.165 Age 0.023 1.023 0.008 1.008 1.039 3.036 0.002 ** Gendermale -0.257 0.773 0.172 0.552 1.083 -1.495 0.135 RaceBlack 0.108 1.114 0.559 0.373 3.332 0.194 0.846 RaceWhite -0.268 0.765 0.511 0.281 2.084 -0.524 0.600 Stage2 0.622 1.863 0.544 0.642 5.407 1.144 0.253 Stage3 0.892 2.441 0.537 0.852 6.995 1.661 0.097 · Stage4 1.278 3.590 0.510 1.321 9.757 2.506 0.012 * Purity 0.015 1.015 0.367 0.495 2.083 0.041 0.967 Rsquare = 0.074 (max possible = 9.89e-01 ) Likelihood ratio test p = 2.44e-04 Wald test p = 6.22e-04 Score (logrank) test p = 4.4e-04 ACSL4 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.408 1.503000e+00 0.217 0.982 2.302 1.875 0.061 · Age 0.006 1.006000e+00 0.026 0.957 1.058 0.228 0.820 Gendermale -0.272 7.620000e-01 0.540 0.265 2.193 -0.505 0.614 RaceBlack 19.009 1.800955e+08 12654.096 0.000 Inf 0.002 0.999 RaceWhite 18.047 6.882664e+07 12654.096 0.000 Inf 0.001 0.999 Stage2 17.459 3.822358e+07 5546.209 0.000 Inf 0.003 0.997 Stage3 16.637 1.680353e+07 5546.209 0.000 Inf 0.003 0.998 Stage4 17.677 4.754153e+07 5546.209 0.000 Inf 0.003 0.997 Purity -1.387 2.500000e-01 1.129 0.027 2.284 -1.228 0.219 Rsquare = 0.136 (max possible = 9.17e-01 ) Likelihood ratio test p = 3.94e-01 Wald test p = 6.84e-01 Score (logrank) test p = 5.22e-01 ACSL4 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.072 1.075 0.091 0.900 1.284 0.796 0.426 Age 0.028 1.028 0.008 1.011 1.045 3.277 0.001 ** Gendermale -0.286 0.751 0.183 0.525 1.075 -1.566 0.117 RaceBlack -0.035 0.966 0.564 0.320 2.920 -0.061 0.951 RaceWhite -0.412 0.663 0.513 0.243 1.810 -0.803 0.422 Stage2 0.369 1.447 0.554 0.489 4.283 0.667 0.505 Stage3 0.751 2.120 0.542 0.733 6.128 1.387 0.165 Stage4 1.158 3.183 0.512 1.167 8.684 2.261 0.024 * Purity 0.240 1.271 0.401 0.579 2.791 0.598 0.550 Rsquare = 0.086 (max possible = 9.89e-01 ) Likelihood ratio test p = 2.64e-04 Wald test p = 7.32e-04 Score (logrank) test p = 5.36e-04 ACSL4 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ACSL4 0.102 1.107000e+00 0.316 0.595 2.058000e+00 0.321 0.748 Age 0.081 1.085000e+00 0.029 1.025 1.149000e+00 2.794 0.005 Gendermale -0.994 3.700000e-01 0.728 0.089 1.541000e+00 -1.365 0.172 RaceBlack -17.374 0.000000e+00 6236.903 0.000 Inf -0.003 0.998 RaceWhite -2.236 1.070000e-01 1.159 0.011 1.036000e+00 -1.930 0.054 Stage2 16.334 1.240946e+07 0.847 2357372.497 6.532476e+07 19.275 0.000 Stage3 17.377 3.522836e+07 0.778 7662602.942 1.619602e+08 22.326 0.000 Stage4 19.693 3.568875e+08 0.900 61122441.666 2.083828e+09 21.874 0.000 Purity 1.325 3.762000e+00 3.551 0.004 3.960085e+03 0.373 0.709 signif ACSL4 Age ** Gendermale RaceBlack RaceWhite · Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.346 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.52e-03 Wald test p = 1.19e-287 Score (logrank) test p = 1.07e-08 ACSL4 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.125 0.882 0.127 0.688 1.132 -0.986 0.324 Age 0.035 1.035 0.008 1.018 1.052 4.115 0.000 *** Gendermale -0.080 0.923 0.184 0.644 1.324 -0.434 0.664 RaceBlack 0.170 1.185 1.057 0.149 9.404 0.160 0.873 RaceWhite 0.165 1.180 1.014 0.162 8.613 0.163 0.871 Stage2 0.213 1.237 0.345 0.630 2.430 0.617 0.537 Stage3 0.798 2.220 0.230 1.414 3.485 3.467 0.001 ** Stage4 1.757 5.794 0.216 3.797 8.841 8.148 0.000 *** Purity -0.079 0.924 0.375 0.443 1.928 -0.211 0.832 Rsquare = 0.176 (max possible = 9.65e-01 ) Likelihood ratio test p = 6.67e-15 Wald test p = 6.89e-15 Score (logrank) test p = 3.62e-18 ACSL4 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.533 1.703 0.189 1.176 2.467 2.817 0.005 ** Age 0.020 1.021 0.016 0.989 1.053 1.281 0.200 Gendermale -0.106 0.899 0.423 0.393 2.058 -0.252 0.801 RaceBlack -2.268 0.104 1.206 0.010 1.101 -1.880 0.060 · RaceWhite -2.392 0.091 1.177 0.009 0.919 -2.032 0.042 * Stage2 -0.334 0.716 1.056 0.090 5.676 -0.316 0.752 Stage3 1.713 5.544 0.432 2.377 12.931 3.963 0.000 *** Stage4 2.924 18.620 0.531 6.579 52.696 5.509 0.000 *** Purity 0.027 1.028 0.736 0.243 4.351 0.037 0.970 Rsquare = 0.192 (max possible = 7.58e-01 ) Likelihood ratio test p = 4.35e-07 Wald test p = 5.32e-07 Score (logrank) test p = 2.82e-11 ACSL4 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.175 1.191 0.172 0.851 1.667 1.018 0.309 Age 0.037 1.038 0.008 1.021 1.054 4.526 0.000 *** Gendermale -0.152 0.859 0.213 0.566 1.303 -0.716 0.474 RaceBlack -0.149 0.861 1.121 0.096 7.754 -0.133 0.894 RaceWhite -0.588 0.556 1.024 0.075 4.135 -0.574 0.566 Rsquare = 0.162 (max possible = 9.96e-01 ) Likelihood ratio test p = 7.92e-05 Wald test p = 2.25e-04 Score (logrank) test p = 1.5e-04 ACSL4 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.207 0.813 0.161 0.593 1.114 -1.290 0.197 Age 0.061 1.063 0.008 1.047 1.079 7.949 0.000 *** Gendermale 0.073 1.076 0.195 0.734 1.576 0.375 0.708 RaceBlack 15.458 5166349.610 1942.591 0.000 Inf 0.008 0.994 RaceWhite 15.455 5154134.710 1942.591 0.000 Inf 0.008 0.994 Purity -0.961 0.382 0.408 0.172 0.851 -2.356 0.018 * Rsquare = 0.139 (max possible = 9.07e-01 ) Likelihood ratio test p = 5.28e-13 Wald test p = 4.96e-13 Score (logrank) test p = 4.34e-14 ACSL4 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.072 1.075 0.047 0.979 1.179 1.518 0.129 Age 0.013 1.013 0.008 0.997 1.030 1.586 0.113 Gendermale -0.098 0.907 0.227 0.581 1.416 -0.429 0.668 RaceBlack 0.889 2.434 0.491 0.929 6.375 1.811 0.070 · RaceWhite -0.013 0.988 0.237 0.621 1.570 -0.053 0.958 Stage2 0.326 1.385 0.261 0.830 2.312 1.245 0.213 Stage3 1.015 2.759 0.239 1.728 4.408 4.248 0.000 *** Stage4 1.595 4.929 0.618 1.467 16.561 2.579 0.010 * Purity 0.694 2.001 0.469 0.798 5.014 1.480 0.139 Rsquare = 0.091 (max possible = 9.66e-01 ) Likelihood ratio test p = 4.87e-04 Wald test p = 2.98e-04 Score (logrank) test p = 1.16e-04 ACSL4 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.101 1.106 0.086 0.934 1.310 1.170 0.242 Age 0.007 1.007 0.009 0.989 1.025 0.788 0.430 Gendermale 0.018 1.019 0.169 0.732 1.418 0.109 0.913 RaceBlack 16.091 9735388.716 1893.921 0.000 Inf 0.008 0.993 RaceWhite 16.226 11142872.131 1893.921 0.000 Inf 0.009 0.993 Stage2 0.847 2.332 0.202 1.571 3.461 4.200 0.000 *** Stage3 0.976 2.655 0.221 1.723 4.090 4.428 0.000 *** Stage4 1.010 2.746 0.334 1.427 5.281 3.026 0.002 ** Purity 0.694 2.001 0.351 1.005 3.983 1.975 0.048 * Rsquare = 0.099 (max possible = 9.74e-01 ) Likelihood ratio test p = 1.35e-06 Wald test p = 1.74e-05 Score (logrank) test p = 1.94e-06 ACSL4 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.105 1.111 0.097 0.919 1.343 1.090 0.276 Age 0.017 1.017 0.009 0.998 1.036 1.789 0.074 · Gendermale 0.455 1.576 0.195 1.076 2.308 2.338 0.019 * RaceBlack 0.068 1.071 0.609 0.324 3.534 0.112 0.911 RaceWhite -0.488 0.614 0.564 0.203 1.855 -0.864 0.387 Stage2 0.217 1.242 0.187 0.862 1.791 1.162 0.245 Stage3 0.629 1.876 0.216 1.229 2.864 2.917 0.004 ** Stage4 0.812 2.252 0.796 0.473 10.719 1.020 0.308 Purity -0.279 0.756 0.369 0.367 1.559 -0.757 0.449 Rsquare = 0.053 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.62e-02 Wald test p = 1.28e-02 Score (logrank) test p = 1.08e-02 ACSL4 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.060 1.062 0.137 0.813 1.388 0.440 0.660 Age 0.020 1.020 0.016 0.989 1.052 1.247 0.212 Gendermale -0.194 0.824 0.331 0.431 1.575 -0.586 0.558 RaceBlack -0.022 0.978 1.571 0.045 21.245 -0.014 0.989 RaceWhite -0.589 0.555 1.063 0.069 4.458 -0.554 0.580 Stage2 -0.203 0.816 0.475 0.322 2.072 -0.427 0.669 Stage3 -0.083 0.920 0.423 0.401 2.109 -0.197 0.844 Stage4 -0.126 0.882 0.482 0.343 2.266 -0.261 0.794 Purity -0.721 0.486 0.562 0.162 1.462 -1.284 0.199 Rsquare = 0.062 (max possible = 9.98e-01 ) Likelihood ratio test p = 7.93e-01 Wald test p = 7.68e-01 Score (logrank) test p = 7.61e-01 ACSL4 in OV (n=303): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.176 1.193 0.117 0.948 1.501 1.501 0.133 Age 0.037 1.038 0.008 1.021 1.054 4.518 0.000 *** RaceBlack -0.103 0.902 0.578 0.290 2.802 -0.178 0.859 RaceWhite -0.160 0.852 0.515 0.310 2.338 -0.311 0.756 Purity -0.319 0.727 0.691 0.187 2.816 -0.462 0.644 Rsquare = 0.09 (max possible = 9.97e-01 ) Likelihood ratio test p = 4.31e-04 Wald test p = 3.87e-04 Score (logrank) test p = 3.03e-04 ACSL4 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.063 1.065 0.165 0.771 1.472 0.384 0.701 Age 0.023 1.024 0.011 1.001 1.047 2.040 0.041 * Gendermale -0.206 0.814 0.218 0.531 1.247 -0.946 0.344 RaceBlack -0.042 0.958 0.739 0.225 4.083 -0.057 0.954 RaceWhite 0.339 1.404 0.476 0.552 3.571 0.713 0.476 Stage2 0.604 1.829 0.440 0.772 4.332 1.373 0.170 Stage3 -0.225 0.799 1.092 0.094 6.791 -0.206 0.837 Stage4 0.179 1.196 0.837 0.232 6.167 0.214 0.831 Purity -0.635 0.530 0.418 0.234 1.201 -1.521 0.128 Rsquare = 0.089 (max possible = 9.91e-01 ) Likelihood ratio test p = 7.96e-02 Wald test p = 1.15e-01 Score (logrank) test p = 1.11e-01 ACSL4 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.126 0.881 0.693 0.226 3.431 -0.182 0.856 Age 0.038 1.038 0.028 0.982 1.097 1.330 0.183 Gendermale 1.394 4.031 0.895 0.697 23.295 1.557 0.119 RaceBlack -0.196 0.822 19815.074 0.000 Inf 0.000 1.000 RaceWhite 17.310 32924218.942 15865.089 0.000 Inf 0.001 0.999 Purity 5.503 245.413 3.422 0.300 200668.773 1.608 0.108 Rsquare = 0.055 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.6e-01 Wald test p = 4.06e-01 Score (logrank) test p = 3e-01 ACSL4 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.286 1.330 0.442 0.559 3.166 0.646 0.519 Age 0.014 1.014 0.057 0.906 1.135 0.239 0.811 RaceBlack 15.003 3277253.418 6773.832 0.000 Inf 0.002 0.998 RaceWhite 16.237 11265541.967 6773.832 0.000 Inf 0.002 0.998 Purity 1.544 4.684 1.567 0.217 101.095 0.985 0.325 Rsquare = 0.008 (max possible = 1.83e-01 ) Likelihood ratio test p = 6.8e-01 Wald test p = 8.07e-01 Score (logrank) test p = 7.49e-01 ACSL4 in READ (n=166): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.293 0.746 0.353 0.374 1.491 -0.829 0.407 Age 0.102 1.108 0.043 1.018 1.206 2.362 0.018 * Gendermale -0.288 0.750 0.674 0.200 2.806 -0.428 0.669 RaceBlack 13.342 622753.493 10578.854 0.000 Inf 0.001 0.999 RaceWhite 12.613 300471.706 10578.854 0.000 Inf 0.001 0.999 Stage2 -2.057 0.128 1.277 0.010 1.562 -1.611 0.107 Stage3 -0.627 0.534 0.917 0.089 3.221 -0.684 0.494 Stage4 -0.306 0.736 0.977 0.108 5.002 -0.313 0.754 Purity -0.149 0.862 1.328 0.064 11.627 -0.112 0.911 Rsquare = 0.217 (max possible = 7.22e-01 ) Likelihood ratio test p = 2.89e-02 Wald test p = 1.64e-01 Score (logrank) test p = 3.06e-02 ACSL4 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.206 0.814 0.124 0.638 1.038 -1.661 0.097 · Age 0.024 1.024 0.008 1.008 1.041 2.919 0.004 ** Gendermale 0.031 1.032 0.224 0.665 1.599 0.139 0.890 RaceBlack -0.185 0.831 1.087 0.099 6.993 -0.170 0.865 RaceWhite -0.627 0.534 1.027 0.071 3.998 -0.610 0.542 Purity 0.830 2.293 0.568 0.753 6.986 1.460 0.144 Rsquare = 0.054 (max possible = 9.75e-01 ) Likelihood ratio test p = 4.53e-02 Wald test p = 4.98e-02 Score (logrank) test p = 5.08e-02 ACSL4 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.253 0.777 0.068 0.679 0.888 -3.709 0.000 *** Age 0.019 1.019 0.005 1.008 1.029 3.550 0.000 *** Gendermale -0.029 0.971 0.157 0.713 1.322 -0.185 0.853 RaceWhite -1.067 0.344 0.407 0.155 0.764 -2.620 0.009 ** Stage2 0.187 1.206 0.220 0.783 1.857 0.848 0.396 Stage3 0.597 1.817 0.206 1.214 2.719 2.900 0.004 ** Stage4 1.327 3.768 0.352 1.890 7.512 3.768 0.000 *** Purity 0.883 2.419 0.339 1.246 4.697 2.609 0.009 ** Rsquare = 0.152 (max possible = 9.92e-01 ) Likelihood ratio test p = 7.3e-11 Wald test p = 1.64e-11 Score (logrank) test p = 1.38e-12 ACSL4 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.016 1.016000e+00 0.174 0.723 1.428 0.090 0.928 Age 0.012 1.012000e+00 0.016 0.981 1.044 0.741 0.458 Gendermale 0.207 1.231000e+00 0.438 0.522 2.902 0.474 0.636 RaceWhite -1.260 2.840000e-01 0.622 0.084 0.959 -2.027 0.043 * Stage2 17.468 3.857177e+07 6199.497 0.000 Inf 0.003 0.998 Stage3 17.976 6.408998e+07 6199.497 0.000 Inf 0.003 0.998 Stage4 20.080 5.253455e+08 6199.497 0.000 Inf 0.003 0.997 Purity 0.249 1.283000e+00 0.981 0.187 8.778 0.254 0.800 Rsquare = 0.147 (max possible = 8.69e-01 ) Likelihood ratio test p = 6.12e-02 Wald test p = 5.51e-02 Score (logrank) test p = 4.56e-03 ACSL4 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.299 0.741 0.077 0.637 0.862 -3.878 0.000 *** Age 0.021 1.021 0.006 1.010 1.033 3.728 0.000 *** Gendermale -0.035 0.966 0.172 0.689 1.353 -0.203 0.839 RaceWhite -0.642 0.526 0.610 0.159 1.738 -1.053 0.292 Stage2 0.042 1.043 0.234 0.660 1.649 0.182 0.856 Stage3 0.563 1.757 0.210 1.163 2.653 2.678 0.007 ** Stage4 1.077 2.935 0.401 1.339 6.436 2.688 0.007 ** Purity 0.937 2.553 0.369 1.239 5.259 2.541 0.011 * Rsquare = 0.173 (max possible = 9.95e-01 ) Likelihood ratio test p = 2.51e-09 Wald test p = 1.57e-09 Score (logrank) test p = 3.72e-10 ACSL4 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -0.176 0.838 0.134 0.644 1.091 -1.313 0.189 Age 0.025 1.026 0.010 1.005 1.046 2.467 0.014 * Gendermale 0.138 1.148 0.208 0.764 1.724 0.665 0.506 RaceBlack 0.358 1.431 0.454 0.588 3.482 0.790 0.430 RaceWhite 0.063 1.065 0.245 0.658 1.722 0.255 0.798 Stage2 0.496 1.642 0.390 0.765 3.525 1.272 0.203 Stage3 0.964 2.622 0.366 1.280 5.372 2.634 0.008 ** Stage4 1.269 3.558 0.504 1.324 9.564 2.516 0.012 * Purity -0.618 0.539 0.386 0.253 1.149 -1.600 0.110 Rsquare = 0.075 (max possible = 9.79e-01 ) Likelihood ratio test p = 7.53e-03 Wald test p = 1.05e-02 Score (logrank) test p = 8.53e-03 ACSL4 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 -3.232 3.900000e-02 37334.923 0 Inf 0.000 1.000 Age -1.688 1.850000e-01 1936.172 0 Inf -0.001 0.999 RaceBlack 11.972 1.582887e+05 21868700.470 0 Inf 0.000 1.000 RaceWhite -27.659 0.000000e+00 22740450.585 0 Inf 0.000 1.000 Stage2 -2.789 6.100000e-02 46757.793 0 Inf 0.000 1.000 Stage3 13.612 8.158426e+05 157986.389 0 Inf 0.000 1.000 Purity 19.020 1.820629e+08 213769.249 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 2.12e-03 ACSL4 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 1.406 4.079 0.487 1.571 10.590 2.888 0.004 ** Age 0.160 1.173 0.030 1.107 1.244 5.396 0.000 *** Gendermale 0.197 1.218 0.619 0.362 4.098 0.319 0.750 RaceBlack 18.138 75341640.705 8999.062 0.000 Inf 0.002 0.998 RaceWhite 16.924 22396147.491 8999.062 0.000 Inf 0.002 0.998 Stage2 0.414 1.513 1.080 0.182 12.571 0.384 0.701 Stage3 0.469 1.599 0.863 0.295 8.674 0.544 0.586 Stage4 1.869 6.481 0.984 0.942 44.608 1.899 0.058 · Purity 3.002 20.126 1.206 1.894 213.824 2.490 0.013 * Rsquare = 0.168 (max possible = 3.47e-01 ) Likelihood ratio test p = 4.26e-12 Wald test p = 1.07e-04 Score (logrank) test p = 9.42e-12 ACSL4 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.856 2.354 0.495 0.892 6.212 1.730 0.084 · Age 0.039 1.040 0.031 0.978 1.106 1.250 0.211 Gendermale 0.192 1.212 0.789 0.258 5.686 0.243 0.808 RaceBlack -15.971 0.000 10408.861 0.000 Inf -0.002 0.999 RaceWhite 0.935 2.548 1.196 0.244 26.584 0.782 0.434 Purity 0.486 1.626 1.173 0.163 16.211 0.414 0.679 Rsquare = 0.072 (max possible = 4.51e-01 ) Likelihood ratio test p = 2.04e-01 Wald test p = 3.6e-01 Score (logrank) test p = 2.6e-01 ACSL4 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.165 1.179 0.131 0.912 1.524 1.257 0.209 Age 0.053 1.055 0.016 1.022 1.089 3.328 0.001 ** RaceBlack -0.527 0.591 0.800 0.123 2.831 -0.659 0.510 RaceWhite -0.658 0.518 0.753 0.118 2.267 -0.873 0.383 Purity 0.519 1.681 0.653 0.468 6.042 0.795 0.426 Rsquare = 0.044 (max possible = 7.81e-01 ) Likelihood ratio test p = 2.71e-02 Wald test p = 3.26e-02 Score (logrank) test p = 3.16e-02 ACSL4 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.298 1.347 0.242 0.839 2.164 1.232 0.218 Age 0.041 1.042 0.024 0.994 1.091 1.720 0.085 · RaceBlack 18.164 77377134.297 6582.052 0.000 Inf 0.003 0.998 RaceWhite 18.214 81304116.165 6582.052 0.000 Inf 0.003 0.998 Purity 0.030 1.031 1.308 0.079 13.375 0.023 0.981 Rsquare = 0.145 (max possible = 9.83e-01 ) Likelihood ratio test p = 1.48e-01 Wald test p = 2.14e-01 Score (logrank) test p = 1.46e-01 ACSL4 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ACSL4` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSL4 0.173 1.189 0.217 0.777 1.820 0.796 0.426 Age 0.040 1.041 0.019 1.003 1.080 2.120 0.034 * Gendermale 0.321 1.379 0.483 0.535 3.553 0.665 0.506 Stage3 0.280 1.323 0.499 0.498 3.520 0.561 0.575 Stage4 3.785 44.049 1.212 4.092 474.187 3.122 0.002 ** Purity 1.979 7.233 1.256 0.617 84.866 1.575 0.115 Rsquare = 0.259 (max possible = 8.72e-01 ) Likelihood ratio test p = 7.68e-04 Wald test p = 3.44e-03 Score (logrank) test p = 2.42e-09 ACSS2 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.171 1.186 0.191 0.815 1.726 0.893 0.372 Age 0.006 1.006 0.014 0.979 1.034 0.454 0.650 Gendermale 0.494 1.640 0.444 0.686 3.917 1.113 0.266 RaceBlack -0.156 0.855 12057.776 0.000 Inf 0.000 1.000 RaceWhite 16.597 16137390.393 10279.394 0.000 Inf 0.002 0.999 Purity 2.819 16.757 2.380 0.158 1776.970 1.185 0.236 Rsquare = 0.078 (max possible = 9.38e-01 ) Likelihood ratio test p = 5.21e-01 Wald test p = 8.22e-01 Score (logrank) test p = 6.68e-01 ACSS2 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.232 1.261 0.122 0.992 1.602 1.893 0.058 · Age 0.034 1.034 0.009 1.017 1.052 3.950 0.000 *** Gendermale -0.155 0.857 0.179 0.603 1.216 -0.866 0.386 RaceBlack 0.688 1.991 0.447 0.829 4.778 1.541 0.123 RaceWhite 0.022 1.022 0.358 0.506 2.064 0.061 0.951 Stage2 14.359 1721606.610 1879.192 0.000 Inf 0.008 0.994 Stage3 14.869 2866997.401 1879.192 0.000 Inf 0.008 0.994 Stage4 15.350 4640333.560 1879.192 0.000 Inf 0.008 0.993 Purity 0.117 1.124 0.341 0.576 2.193 0.343 0.732 Rsquare = 0.139 (max possible = 9.91e-01 ) Likelihood ratio test p = 4.32e-08 Wald test p = 2.43e-07 Score (logrank) test p = 7.6e-08 ACSS2 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.343 0.710 0.174 0.504 0.998 -1.969 0.049 * Age 0.036 1.036 0.008 1.021 1.052 4.734 0.000 *** Gendermale 0.043 1.044 1.007 0.145 7.507 0.042 0.966 RaceBlack -0.053 0.948 0.620 0.281 3.198 -0.085 0.932 RaceWhite -0.223 0.800 0.596 0.249 2.573 -0.374 0.709 Stage2 0.414 1.513 0.303 0.835 2.743 1.365 0.172 Stage3 1.232 3.428 0.314 1.854 6.339 3.929 0.000 *** Stage4 2.635 13.947 0.394 6.449 30.166 6.695 0.000 *** Purity 0.560 1.751 0.421 0.768 3.993 1.331 0.183 Rsquare = 0.085 (max possible = 7.85e-01 ) Likelihood ratio test p = 4.36e-13 Wald test p = 2.34e-16 Score (logrank) test p = 2.05e-22 ACSS2 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -1.015 3.620000e-01 0.263 0.217 0.606 -3.866 0.000 *** Age 0.016 1.016000e+00 0.016 0.985 1.048 1.015 0.310 RaceBlack -1.856 1.560000e-01 1.159 0.016 1.514 -1.602 0.109 RaceWhite -1.642 1.940000e-01 1.119 0.022 1.734 -1.468 0.142 Stage2 18.601 1.197443e+08 6674.890 0.000 Inf 0.003 0.998 Stage3 20.938 1.239525e+09 6674.890 0.000 Inf 0.003 0.997 Stage4 22.488 5.838794e+09 6674.890 0.000 Inf 0.003 0.997 Purity 1.204 3.333000e+00 0.872 0.603 18.425 1.380 0.168 Rsquare = 0.23 (max possible = 7.18e-01 ) Likelihood ratio test p = 1.06e-06 Wald test p = 2.6e-04 Score (logrank) test p = 1.45e-08 ACSS2 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.375 6.880000e-01 0.627 0.201 2.351 -0.597 0.550 Age 0.037 1.038000e+00 0.030 0.979 1.101 1.243 0.214 RaceBlack -3.473 3.100000e-02 1.955 0.001 1.432 -1.776 0.076 · RaceWhite -2.098 1.230000e-01 1.607 0.005 2.865 -1.305 0.192 Stage2 18.328 9.116307e+07 14843.276 0.000 Inf 0.001 0.999 Stage3 19.849 4.172057e+08 14843.276 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 2.537 1.264200e+01 2.336 0.130 1229.958 1.086 0.277 Rsquare = 0.374 (max possible = 6.68e-01 ) Likelihood ratio test p = 2.59e-04 Wald test p = 2.47e-01 Score (logrank) test p = 1.18e-14 ACSS2 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.763 0.466 0.400 0.213 1.021 -1.908 0.056 · Age 0.052 1.053 0.012 1.029 1.078 4.328 0.000 *** Gendermale -15.502 0.000 3433.436 0.000 Inf -0.005 0.996 RaceBlack -0.422 0.656 1.174 0.066 6.546 -0.359 0.719 RaceWhite 0.298 1.347 1.029 0.179 10.133 0.290 0.772 Stage2 0.379 1.461 0.374 0.701 3.042 1.012 0.311 Stage3 0.935 2.547 0.396 1.172 5.538 2.360 0.018 * Stage4 2.422 11.265 0.609 3.418 37.129 3.980 0.000 *** Purity 0.291 1.338 0.616 0.400 4.471 0.473 0.636 Rsquare = 0.077 (max possible = 6.81e-01 ) Likelihood ratio test p = 2.26e-05 Wald test p = 1.15e-05 Score (logrank) test p = 1.38e-07 ACSS2 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.580 1.786 0.392 0.828 3.850 1.479 0.139 Age 0.055 1.057 0.021 1.013 1.102 2.573 0.010 * Gendermale 0.895 2.448 1.110 0.278 21.556 0.807 0.420 RaceBlack 16.462 14104021.740 6665.882 0.000 Inf 0.002 0.998 RaceWhite 15.749 6910620.095 6665.882 0.000 Inf 0.002 0.998 Stage2 0.634 1.884 1.078 0.228 15.577 0.588 0.557 Stage3 1.597 4.937 1.059 0.619 39.368 1.507 0.132 Stage4 1.832 6.244 1.180 0.618 63.073 1.552 0.121 Purity 0.749 2.116 1.361 0.147 30.474 0.551 0.582 Rsquare = 0.117 (max possible = 6.98e-01 ) Likelihood ratio test p = 2.09e-02 Wald test p = 4.69e-02 Score (logrank) test p = 1.36e-02 ACSS2 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.173 0.841 0.218 0.549 1.289 -0.794 0.427 Age 0.013 1.013 0.010 0.993 1.034 1.302 0.193 RaceBlack 1.014 2.758 1.069 0.339 22.408 0.949 0.343 RaceWhite 0.810 2.247 1.015 0.307 16.433 0.798 0.425 Purity 0.627 1.872 0.732 0.446 7.864 0.857 0.392 Rsquare = 0.016 (max possible = 8.91e-01 ) Likelihood ratio test p = 5.84e-01 Wald test p = 6.14e-01 Score (logrank) test p = 6.05e-01 ACSS2 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.316 1.372 0.492 0.523 3.596 0.643 0.520 Age 0.014 1.014 0.023 0.970 1.060 0.631 0.528 Gendermale 0.300 1.351 0.568 0.444 4.112 0.529 0.597 RaceBlack -0.595 0.552 1.543 0.027 11.361 -0.385 0.700 RaceWhite -1.025 0.359 0.898 0.062 2.085 -1.142 0.254 Stage2 0.690 1.994 0.671 0.535 7.430 1.029 0.304 Stage3 -15.049 0.000 7008.948 0.000 Inf -0.002 0.998 Stage4 0.843 2.323 0.673 0.621 8.688 1.252 0.210 Purity 2.279 9.763 1.617 0.411 232.191 1.409 0.159 Rsquare = 0.221 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.39e-01 Wald test p = 6.07e-01 Score (logrank) test p = 4.45e-01 ACSS2 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.007 1.007 0.198 0.683 1.485 0.035 0.972 Age 0.024 1.024 0.011 1.001 1.047 2.074 0.038 * Gendermale 0.214 1.239 0.270 0.731 2.101 0.795 0.427 RaceBlack -0.413 0.661 0.828 0.130 3.352 -0.499 0.618 RaceWhite -0.440 0.644 0.778 0.140 2.956 -0.566 0.571 Stage2 0.209 1.233 0.563 0.409 3.716 0.372 0.710 Stage3 0.806 2.238 0.550 0.762 6.572 1.466 0.143 Stage4 1.884 6.580 0.555 2.218 19.522 3.396 0.001 ** Purity -0.225 0.799 0.603 0.245 2.604 -0.373 0.709 Rsquare = 0.109 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.64e-04 Wald test p = 1.62e-04 Score (logrank) test p = 2.34e-05 ACSS2 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.243 0.784 1.107 0.089 6.869 -0.220 0.826 Age 0.001 1.001 0.046 0.916 1.094 0.020 0.984 Gendermale 0.683 1.980 1.060 0.248 15.801 0.644 0.519 RaceBlack 0.526 1.692 1.701 0.060 47.468 0.309 0.757 RaceWhite -1.966 0.140 1.426 0.009 2.291 -1.379 0.168 Purity -2.244 0.106 2.239 0.001 8.529 -1.002 0.316 Rsquare = 0.132 (max possible = 5.58e-01 ) Likelihood ratio test p = 4.47e-01 Wald test p = 5.77e-01 Score (logrank) test p = 3.19e-01 ACSS2 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.007 0.993 0.188 0.687 1.435 -0.039 0.969 Age 0.010 1.010 0.014 0.982 1.038 0.677 0.499 Gendermale 0.482 1.619 0.538 0.564 4.642 0.896 0.370 RaceBlack 0.336 1.399 1.068 0.172 11.351 0.314 0.753 RaceWhite -0.078 0.925 0.447 0.385 2.220 -0.175 0.861 Stage2 0.693 2.000 0.661 0.548 7.300 1.049 0.294 Stage3 1.454 4.278 0.670 1.150 15.919 2.168 0.030 * Stage4 2.862 17.489 0.775 3.830 79.862 3.693 0.000 *** Purity 0.223 1.249 0.788 0.267 5.854 0.283 0.778 Rsquare = 0.141 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.15e-02 Wald test p = 5.33e-03 Score (logrank) test p = 4.44e-04 ACSS2 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.310 1.364 0.242 0.849 2.192 1.282 0.200 Age 0.028 1.028 0.008 1.011 1.045 3.305 0.001 ** Gendermale -0.076 0.926 0.213 0.610 1.407 -0.358 0.720 RaceBlack 0.621 1.860 0.731 0.444 7.797 0.849 0.396 RaceWhite -0.155 0.857 0.617 0.256 2.871 -0.251 0.802 Purity -1.062 0.346 0.533 0.122 0.982 -1.994 0.046 * Rsquare = 0.14 (max possible = 9.98e-01 ) Likelihood ratio test p = 2.42e-03 Wald test p = 3.41e-03 Score (logrank) test p = 3.15e-03 ACSS2 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.025 0.975 0.130 0.756 1.258 -0.194 0.846 Age 0.022 1.022 0.008 1.007 1.038 2.902 0.004 ** Gendermale -0.246 0.782 0.173 0.557 1.097 -1.426 0.154 RaceBlack 0.146 1.157 0.562 0.385 3.482 0.260 0.795 RaceWhite -0.242 0.785 0.511 0.288 2.139 -0.473 0.636 Stage2 0.623 1.864 0.545 0.641 5.421 1.144 0.253 Stage3 0.856 2.355 0.537 0.821 6.750 1.594 0.111 Stage4 1.260 3.527 0.511 1.296 9.598 2.467 0.014 * Purity -0.034 0.967 0.369 0.469 1.994 -0.091 0.928 Rsquare = 0.069 (max possible = 9.89e-01 ) Likelihood ratio test p = 5.19e-04 Wald test p = 1.37e-03 Score (logrank) test p = 1e-03 ACSS2 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.469 6.260000e-01 0.450 0.259 1.511 -1.042 0.298 Age 0.009 1.009000e+00 0.025 0.960 1.060 0.343 0.732 Gendermale -0.004 9.960000e-01 0.558 0.334 2.974 -0.007 0.994 RaceBlack 18.494 1.075757e+08 12209.822 0.000 Inf 0.002 0.999 RaceWhite 17.799 5.372344e+07 12209.822 0.000 Inf 0.001 0.999 Stage2 17.512 4.030525e+07 5358.353 0.000 Inf 0.003 0.997 Stage3 16.861 2.102448e+07 5358.353 0.000 Inf 0.003 0.997 Stage4 17.594 4.376458e+07 5358.353 0.000 Inf 0.003 0.997 Purity -1.172 3.100000e-01 1.113 0.035 2.746 -1.053 0.293 Rsquare = 0.103 (max possible = 9.17e-01 ) Likelihood ratio test p = 6.3e-01 Wald test p = 8.98e-01 Score (logrank) test p = 7.77e-01 ACSS2 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.031 1.032 0.140 0.784 1.357 0.222 0.824 Age 0.027 1.027 0.008 1.010 1.044 3.190 0.001 ** Gendermale -0.288 0.750 0.183 0.524 1.073 -1.574 0.116 RaceBlack -0.035 0.965 0.570 0.316 2.949 -0.062 0.951 RaceWhite -0.404 0.668 0.514 0.244 1.827 -0.787 0.431 Stage2 0.359 1.431 0.555 0.483 4.247 0.646 0.518 Stage3 0.720 2.055 0.542 0.711 5.940 1.330 0.184 Stage4 1.140 3.126 0.513 1.144 8.545 2.222 0.026 * Purity 0.196 1.217 0.405 0.550 2.691 0.485 0.628 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.34e-04 Wald test p = 9.45e-04 Score (logrank) test p = 7.13e-04 ACSS2 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z ACSS2 1.895 6.655000e+00 0.767 1.480000e+00 2.993100e+01 2.471 Age 0.091 1.095000e+00 0.028 1.037000e+00 1.157000e+00 3.248 Gendermale -1.435 2.380000e-01 0.740 5.600000e-02 1.016000e+00 -1.939 RaceBlack -17.357 0.000000e+00 12125.439 0.000000e+00 Inf -0.001 RaceWhite -0.619 5.390000e-01 1.166 5.500000e-02 5.292000e+00 -0.531 Stage2 16.799 1.975672e+07 0.855 3.698306e+06 1.055423e+08 19.650 Stage3 19.098 1.969236e+08 0.781 4.262311e+07 9.098097e+08 24.459 Stage4 21.048 1.383112e+09 0.929 2.239675e+08 8.541406e+09 22.659 Purity 1.207 3.344000e+00 3.724 2.000000e-03 4.948299e+03 0.324 p signif ACSS2 0.013 * Age 0.001 ** Gendermale 0.053 · RaceBlack 0.999 RaceWhite 0.596 Stage2 0.000 *** Stage3 0.000 *** Stage4 0.000 *** Purity 0.746 Rsquare = 0.366 (max possible = 6.71e-01 ) Likelihood ratio test p = 7.3e-04 Wald test p = 1.85e-321 Score (logrank) test p = 7.18e-09 ACSS2 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.269 0.764 0.173 0.544 1.072 -1.557 0.119 Age 0.034 1.035 0.008 1.018 1.052 4.086 0.000 *** Gendermale -0.071 0.932 0.184 0.650 1.336 -0.384 0.701 RaceBlack 0.263 1.301 1.059 0.163 10.355 0.248 0.804 RaceWhite 0.212 1.237 1.016 0.169 9.067 0.209 0.834 Stage2 0.171 1.186 0.346 0.602 2.337 0.494 0.621 Stage3 0.806 2.238 0.230 1.427 3.512 3.506 0.000 *** Stage4 1.732 5.649 0.216 3.697 8.634 8.002 0.000 *** Purity 0.088 1.092 0.366 0.533 2.240 0.240 0.810 Rsquare = 0.178 (max possible = 9.65e-01 ) Likelihood ratio test p = 3.38e-15 Wald test p = 2.04e-15 Score (logrank) test p = 1.12e-18 ACSS2 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.745 0.475 0.246 0.293 0.769 -3.026 0.002 ** Age 0.016 1.016 0.017 0.983 1.049 0.953 0.341 Gendermale -0.128 0.880 0.393 0.407 1.900 -0.326 0.744 RaceBlack -2.830 0.059 1.214 0.005 0.637 -2.331 0.020 * RaceWhite -3.134 0.044 1.207 0.004 0.464 -2.596 0.009 ** Stage2 -0.226 0.798 1.055 0.101 6.305 -0.214 0.830 Stage3 1.319 3.740 0.430 1.611 8.681 3.070 0.002 ** Stage4 2.600 13.461 0.522 4.843 37.419 4.984 0.000 *** Purity -0.184 0.832 0.716 0.204 3.387 -0.257 0.797 Rsquare = 0.199 (max possible = 7.58e-01 ) Likelihood ratio test p = 1.89e-07 Wald test p = 2.99e-07 Score (logrank) test p = 7.8e-12 ACSS2 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.096 1.101 0.152 0.817 1.483 0.630 0.529 Age 0.037 1.038 0.008 1.021 1.055 4.469 0.000 *** Gendermale -0.155 0.857 0.214 0.563 1.303 -0.723 0.470 RaceBlack -0.292 0.747 1.109 0.085 6.565 -0.263 0.792 RaceWhite -0.648 0.523 1.022 0.071 3.877 -0.634 0.526 Rsquare = 0.158 (max possible = 9.96e-01 ) Likelihood ratio test p = 1.06e-04 Wald test p = 3.08e-04 Score (logrank) test p = 2.34e-04 ACSS2 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.567 1.764 0.259 1.062 2.929 2.192 0.028 * Age 0.058 1.060 0.008 1.044 1.077 7.439 0.000 *** Gendermale 0.151 1.163 0.197 0.791 1.710 0.766 0.443 RaceBlack 15.400 4877603.450 2029.376 0.000 Inf 0.008 0.994 RaceWhite 15.394 4848906.422 2029.376 0.000 Inf 0.008 0.994 Purity -0.980 0.375 0.399 0.172 0.820 -2.458 0.014 * Rsquare = 0.145 (max possible = 9.07e-01 ) Likelihood ratio test p = 1.17e-13 Wald test p = 1.83e-13 Score (logrank) test p = 1.25e-14 ACSS2 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.060 0.942 0.117 0.749 1.184 -0.515 0.606 Age 0.011 1.011 0.008 0.996 1.028 1.408 0.159 Gendermale -0.153 0.858 0.226 0.551 1.337 -0.675 0.499 RaceBlack 0.907 2.478 0.490 0.948 6.476 1.851 0.064 · RaceWhite 0.000 1.000 0.237 0.629 1.591 0.001 0.999 Stage2 0.297 1.346 0.263 0.804 2.253 1.131 0.258 Stage3 0.954 2.597 0.235 1.639 4.115 4.064 0.000 *** Stage4 1.568 4.799 0.620 1.423 16.178 2.529 0.011 * Purity 0.591 1.806 0.461 0.731 4.461 1.282 0.200 Rsquare = 0.085 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.09e-03 Wald test p = 6.84e-04 Score (logrank) test p = 2.51e-04 ACSS2 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.047 0.955 0.109 0.771 1.181 -0.428 0.668 Age 0.007 1.007 0.009 0.989 1.025 0.791 0.429 Gendermale 0.002 1.002 0.173 0.715 1.406 0.014 0.989 RaceBlack 16.060 9437828.926 1897.860 0.000 Inf 0.008 0.993 RaceWhite 16.244 11341109.900 1897.860 0.000 Inf 0.009 0.993 Stage2 0.851 2.342 0.204 1.571 3.491 4.178 0.000 *** Stage3 1.019 2.770 0.218 1.806 4.247 4.670 0.000 *** Stage4 0.981 2.668 0.339 1.373 5.184 2.896 0.004 ** Purity 0.611 1.843 0.345 0.937 3.622 1.772 0.076 · Rsquare = 0.097 (max possible = 9.74e-01 ) Likelihood ratio test p = 2.22e-06 Wald test p = 2.83e-05 Score (logrank) test p = 3.19e-06 ACSS2 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.012 0.988 0.133 0.762 1.280 -0.094 0.925 Age 0.016 1.016 0.009 0.998 1.035 1.749 0.080 · Gendermale 0.436 1.547 0.193 1.059 2.261 2.256 0.024 * RaceBlack 0.010 1.010 0.606 0.308 3.315 0.016 0.987 RaceWhite -0.516 0.597 0.564 0.198 1.802 -0.915 0.360 Stage2 0.213 1.238 0.188 0.857 1.788 1.137 0.255 Stage3 0.606 1.833 0.215 1.201 2.796 2.811 0.005 ** Stage4 0.758 2.134 0.794 0.450 10.122 0.955 0.340 Purity -0.344 0.709 0.366 0.346 1.452 -0.940 0.347 Rsquare = 0.05 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.42e-02 Wald test p = 1.87e-02 Score (logrank) test p = 1.61e-02 ACSS2 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.005 0.995 0.302 0.551 1.798 -0.016 0.987 Age 0.020 1.020 0.016 0.989 1.053 1.263 0.206 Gendermale -0.177 0.838 0.330 0.439 1.600 -0.536 0.592 RaceBlack 0.134 1.143 1.532 0.057 23.045 0.087 0.930 RaceWhite -0.507 0.602 1.046 0.078 4.676 -0.485 0.628 Stage2 -0.234 0.791 0.469 0.316 1.983 -0.500 0.617 Stage3 -0.103 0.902 0.422 0.394 2.063 -0.245 0.807 Stage4 -0.151 0.859 0.477 0.337 2.189 -0.318 0.751 Purity -0.752 0.471 0.557 0.158 1.403 -1.352 0.176 Rsquare = 0.06 (max possible = 9.98e-01 ) Likelihood ratio test p = 8.11e-01 Wald test p = 7.9e-01 Score (logrank) test p = 7.83e-01 ACSS2 in OV (n=303): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.263 1.301 0.163 0.946 1.791 1.618 0.106 Age 0.040 1.041 0.008 1.024 1.058 4.729 0.000 *** RaceBlack 0.039 1.039 0.579 0.334 3.233 0.067 0.947 RaceWhite -0.089 0.915 0.516 0.333 2.517 -0.172 0.863 Purity -0.604 0.547 0.668 0.148 2.024 -0.904 0.366 Rsquare = 0.091 (max possible = 9.97e-01 ) Likelihood ratio test p = 3.68e-04 Wald test p = 3.1e-04 Score (logrank) test p = 2.6e-04 ACSS2 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.020 0.980 0.173 0.699 1.375 -0.115 0.908 Age 0.022 1.022 0.011 1.001 1.044 2.019 0.043 * Gendermale -0.209 0.812 0.223 0.524 1.256 -0.937 0.349 RaceBlack -0.023 0.977 0.738 0.230 4.149 -0.031 0.975 RaceWhite 0.361 1.435 0.474 0.567 3.631 0.761 0.446 Stage2 0.634 1.885 0.446 0.787 4.516 1.422 0.155 Stage3 -0.239 0.787 1.092 0.093 6.686 -0.219 0.826 Stage4 0.256 1.292 0.840 0.249 6.707 0.305 0.761 Purity -0.666 0.514 0.410 0.230 1.149 -1.622 0.105 Rsquare = 0.089 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.3e-02 Wald test p = 1.19e-01 Score (logrank) test p = 1.15e-01 ACSS2 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 1.065 2.900 0.595 0.903 9.306 1.789 0.074 · Age 0.060 1.062 0.036 0.990 1.139 1.671 0.095 · Gendermale 1.865 6.453 1.033 0.853 48.830 1.806 0.071 · RaceBlack -0.522 0.594 30774.851 0.000 Inf 0.000 1.000 RaceWhite 17.989 64929909.911 26055.559 0.000 Inf 0.001 0.999 Purity 6.243 514.560 3.312 0.780 339412.915 1.885 0.059 · Rsquare = 0.07 (max possible = 3.07e-01 ) Likelihood ratio test p = 6.43e-02 Wald test p = 3.29e-01 Score (logrank) test p = 2.13e-01 ACSS2 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 1.812 6.120 0.740 1.435 26.104 2.448 0.014 * Age 0.023 1.023 0.061 0.908 1.153 0.379 0.705 RaceBlack 15.652 6271775.570 7055.851 0.000 Inf 0.002 0.998 RaceWhite 16.343 12527245.693 7055.850 0.000 Inf 0.002 0.998 Purity 1.172 3.228 1.462 0.184 56.663 0.801 0.423 Rsquare = 0.02 (max possible = 1.83e-01 ) Likelihood ratio test p = 1.46e-01 Wald test p = 1.12e-01 Score (logrank) test p = 1.17e-01 ACSS2 in READ (n=166): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -1.462 0.232 0.620 0.069 0.781 -2.359 0.018 * Age 0.146 1.157 0.052 1.044 1.282 2.788 0.005 ** Gendermale -0.209 0.812 0.764 0.182 3.630 -0.273 0.785 RaceBlack 14.397 1788385.626 7384.907 0.000 Inf 0.002 0.998 RaceWhite 12.529 276268.938 7384.907 0.000 Inf 0.002 0.999 Stage2 -1.782 0.168 1.302 0.013 2.160 -1.369 0.171 Stage3 -0.374 0.688 0.877 0.123 3.836 -0.427 0.670 Stage4 0.207 1.230 0.994 0.175 8.632 0.208 0.835 Purity 0.618 1.854 1.403 0.119 29.004 0.440 0.660 Rsquare = 0.27 (max possible = 7.22e-01 ) Likelihood ratio test p = 4.35e-03 Wald test p = 8.44e-02 Score (logrank) test p = 1.02e-02 ACSS2 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.084 0.919 0.167 0.663 1.275 -0.503 0.615 Age 0.022 1.023 0.008 1.006 1.039 2.686 0.007 ** Gendermale -0.015 0.985 0.222 0.637 1.523 -0.069 0.945 RaceBlack -0.157 0.855 1.088 0.101 7.216 -0.144 0.886 RaceWhite -0.493 0.611 1.024 0.082 4.544 -0.481 0.630 Purity 0.971 2.642 0.574 0.858 8.136 1.693 0.091 · Rsquare = 0.044 (max possible = 9.75e-01 ) Likelihood ratio test p = 1.1e-01 Wald test p = 1.44e-01 Score (logrank) test p = 1.46e-01 ACSS2 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.068 0.935 0.101 0.766 1.140 -0.666 0.505 Age 0.018 1.018 0.005 1.008 1.029 3.463 0.001 ** Gendermale -0.061 0.941 0.158 0.690 1.282 -0.387 0.699 RaceWhite -1.260 0.284 0.403 0.129 0.625 -3.128 0.002 ** Stage2 0.277 1.319 0.218 0.860 2.023 1.268 0.205 Stage3 0.618 1.855 0.204 1.243 2.768 3.025 0.002 ** Stage4 1.346 3.841 0.351 1.929 7.650 3.829 0.000 *** Purity 1.030 2.802 0.341 1.437 5.464 3.024 0.002 ** Rsquare = 0.124 (max possible = 9.92e-01 ) Likelihood ratio test p = 1.83e-08 Wald test p = 1e-08 Score (logrank) test p = 1.2e-09 ACSS2 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.138 8.710000e-01 0.355 0.435 1.746 -0.388 0.698 Age 0.011 1.011000e+00 0.016 0.980 1.044 0.697 0.486 Gendermale 0.210 1.233000e+00 0.436 0.524 2.900 0.481 0.631 RaceWhite -1.252 2.860000e-01 0.619 0.085 0.961 -2.024 0.043 * Stage2 17.485 3.922596e+07 6197.888 0.000 Inf 0.003 0.998 Stage3 17.978 6.425419e+07 6197.888 0.000 Inf 0.003 0.998 Stage4 20.086 5.289760e+08 6197.888 0.000 Inf 0.003 0.997 Purity 0.324 1.383000e+00 0.956 0.212 9.011 0.339 0.734 Rsquare = 0.148 (max possible = 8.69e-01 ) Likelihood ratio test p = 5.84e-02 Wald test p = 5.35e-02 Score (logrank) test p = 4.41e-03 ACSS2 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.052 0.949 0.106 0.771 1.169 -0.489 0.625 Age 0.020 1.020 0.006 1.009 1.032 3.593 0.000 *** Gendermale -0.068 0.934 0.173 0.665 1.312 -0.394 0.694 RaceWhite -1.034 0.355 0.601 0.109 1.155 -1.721 0.085 · Stage2 0.154 1.166 0.230 0.743 1.831 0.667 0.504 Stage3 0.569 1.766 0.209 1.172 2.661 2.719 0.007 ** Stage4 1.130 3.095 0.400 1.415 6.772 2.828 0.005 ** Purity 1.151 3.162 0.370 1.530 6.536 3.108 0.002 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 9.93e-07 Wald test p = 1.58e-06 Score (logrank) test p = 6.13e-07 ACSS2 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.107 0.899 0.125 0.703 1.149 -0.851 0.395 Age 0.028 1.028 0.010 1.007 1.049 2.671 0.008 ** Gendermale 0.149 1.160 0.210 0.769 1.750 0.709 0.478 RaceBlack 0.348 1.416 0.458 0.577 3.476 0.760 0.448 RaceWhite 0.125 1.133 0.247 0.698 1.837 0.505 0.614 Stage2 0.524 1.689 0.392 0.783 3.644 1.336 0.182 Stage3 0.928 2.530 0.364 1.240 5.158 2.553 0.011 * Stage4 1.313 3.717 0.504 1.384 9.978 2.606 0.009 ** Purity -0.516 0.597 0.381 0.283 1.260 -1.354 0.176 Rsquare = 0.072 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.07e-02 Wald test p = 1.38e-02 Score (logrank) test p = 1.1e-02 ACSS2 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 5.795 328.682 46862.516 0 Inf 0.000 1.000 Age -1.609 0.200 1692.289 0 Inf -0.001 0.999 RaceBlack 2.618 13.706 17409258.671 0 Inf 0.000 1.000 RaceWhite -47.382 0.000 17544511.781 0 Inf 0.000 1.000 Stage2 -0.282 0.754 41020.884 0 Inf 0.000 1.000 Stage3 16.310 12115514.525 126516.350 0 Inf 0.000 1.000 Purity 4.717 111.794 200519.497 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.3e-03 ACSS2 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.555 1.741 0.792 0.369 8.217 0.701 0.484 Age 0.149 1.160 0.028 1.098 1.226 5.271 0.000 *** Gendermale -0.050 0.951 0.620 0.282 3.209 -0.081 0.936 RaceBlack 17.160 28350709.605 6389.819 0.000 Inf 0.003 0.998 RaceWhite 17.157 28253012.455 6389.819 0.000 Inf 0.003 0.998 Stage2 0.039 1.039 1.136 0.112 9.635 0.034 0.973 Stage3 0.441 1.554 0.900 0.266 9.064 0.490 0.624 Stage4 1.858 6.412 1.008 0.890 46.194 1.844 0.065 · Purity 2.190 8.933 1.056 1.127 70.841 2.073 0.038 * Rsquare = 0.15 (max possible = 3.47e-01 ) Likelihood ratio test p = 2.03e-10 Wald test p = 3.38e-04 Score (logrank) test p = 9.06e-11 ACSS2 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.467 1.594 0.566 0.525 4.838 0.824 0.410 Age 0.042 1.043 0.032 0.980 1.111 1.321 0.186 Gendermale -0.138 0.871 0.719 0.213 3.566 -0.192 0.848 RaceBlack -16.578 0.000 10722.050 0.000 Inf -0.002 0.999 RaceWhite 0.507 1.660 1.095 0.194 14.194 0.463 0.644 Purity 0.226 1.254 1.120 0.140 11.262 0.202 0.840 Rsquare = 0.05 (max possible = 4.51e-01 ) Likelihood ratio test p = 4.49e-01 Wald test p = 5.43e-01 Score (logrank) test p = 4.41e-01 ACSS2 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.230 1.258 0.240 0.786 2.015 0.956 0.339 Age 0.048 1.049 0.016 1.017 1.083 2.995 0.003 ** RaceBlack -0.441 0.644 0.796 0.135 3.065 -0.554 0.580 RaceWhite -0.630 0.533 0.757 0.121 2.351 -0.831 0.406 Purity 0.426 1.531 0.649 0.429 5.466 0.656 0.512 Rsquare = 0.041 (max possible = 7.81e-01 ) Likelihood ratio test p = 3.57e-02 Wald test p = 4.63e-02 Score (logrank) test p = 4.33e-02 ACSS2 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 0.107 1.113 0.217 0.728 1.703 0.494 0.621 Age 0.048 1.049 0.026 0.997 1.103 1.859 0.063 · RaceBlack 17.553 41996724.291 6498.806 0.000 Inf 0.003 0.998 RaceWhite 17.806 54081988.297 6498.806 0.000 Inf 0.003 0.998 Purity -1.007 0.365 1.098 0.042 3.140 -0.918 0.359 Rsquare = 0.123 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.34e-01 Wald test p = 3.3e-01 Score (logrank) test p = 2.43e-01 ACSS2 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ACSS2` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ACSS2 -0.095 0.910 0.563 0.302 2.741 -0.168 0.866 Age 0.040 1.041 0.019 1.003 1.081 2.107 0.035 * Gendermale 0.267 1.307 0.483 0.507 3.370 0.553 0.580 Stage3 0.317 1.373 0.544 0.473 3.988 0.583 0.560 Stage4 3.774 43.558 1.219 3.991 475.352 3.095 0.002 ** Purity 1.988 7.301 1.254 0.625 85.238 1.585 0.113 Rsquare = 0.253 (max possible = 8.72e-01 ) Likelihood ratio test p = 9.96e-04 Wald test p = 3.63e-03 Score (logrank) test p = 2.62e-09 ELOVL1 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 1.288 3.626 0.310 1.974 6.662 4.152 0.000 *** Age 0.040 1.040 0.016 1.009 1.073 2.511 0.012 * Gendermale 0.814 2.257 0.428 0.976 5.218 1.904 0.057 · RaceBlack -0.696 0.499 14399.990 0.000 Inf 0.000 1.000 RaceWhite 15.425 5002301.107 12510.989 0.000 Inf 0.001 0.999 Purity 1.671 5.320 2.064 0.093 303.840 0.810 0.418 Rsquare = 0.319 (max possible = 9.38e-01 ) Likelihood ratio test p = 4e-04 Wald test p = 3.59e-03 Score (logrank) test p = 1.89e-03 ELOVL1 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.098 0.907 0.136 0.694 1.185 -0.718 0.473 Age 0.034 1.035 0.009 1.017 1.053 3.950 0.000 *** Gendermale -0.159 0.853 0.179 0.601 1.211 -0.888 0.375 RaceBlack 0.712 2.037 0.446 0.850 4.882 1.596 0.111 RaceWhite 0.106 1.112 0.355 0.555 2.230 0.299 0.765 Stage2 14.405 1803656.923 1868.571 0.000 Inf 0.008 0.994 Stage3 14.828 2753295.096 1868.571 0.000 Inf 0.008 0.994 Stage4 15.392 4836989.024 1868.571 0.000 Inf 0.008 0.993 Purity 0.178 1.195 0.341 0.612 2.333 0.521 0.602 Rsquare = 0.131 (max possible = 9.91e-01 ) Likelihood ratio test p = 1.62e-07 Wald test p = 1e-06 Score (logrank) test p = 2.74e-07 ELOVL1 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.718 2.051 0.192 1.406 2.990 3.733 0.000 *** Age 0.039 1.040 0.008 1.024 1.055 5.142 0.000 *** Gendermale 0.116 1.123 1.008 0.156 8.106 0.115 0.908 RaceBlack -0.171 0.843 0.622 0.249 2.849 -0.276 0.783 RaceWhite -0.327 0.721 0.597 0.224 2.323 -0.549 0.583 Stage2 0.450 1.568 0.304 0.863 2.846 1.477 0.140 Stage3 1.294 3.646 0.315 1.968 6.754 4.112 0.000 *** Stage4 2.632 13.904 0.390 6.476 29.853 6.752 0.000 *** Purity 0.538 1.713 0.432 0.735 3.995 1.246 0.213 Rsquare = 0.095 (max possible = 7.85e-01 ) Likelihood ratio test p = 5.61e-15 Wald test p = 1.3e-18 Score (logrank) test p = 1.47e-24 ELOVL1 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 1.071 2.918000e+00 0.366 1.425 5.975 2.928 0.003 ** Age 0.008 1.009000e+00 0.018 0.973 1.045 0.465 0.642 RaceBlack -1.596 2.030000e-01 1.154 0.021 1.946 -1.383 0.167 RaceWhite -1.791 1.670000e-01 1.155 0.017 1.602 -1.552 0.121 Stage2 18.624 1.225575e+08 6338.572 0.000 Inf 0.003 0.998 Stage3 20.322 6.695790e+08 6338.572 0.000 Inf 0.003 0.997 Stage4 21.301 1.781689e+09 6338.572 0.000 Inf 0.003 0.997 Purity 1.136 3.115000e+00 0.989 0.449 21.626 1.149 0.250 Rsquare = 0.204 (max possible = 7.18e-01 ) Likelihood ratio test p = 1.05e-05 Wald test p = 5.7e-04 Score (logrank) test p = 1.05e-07 ELOVL1 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.013 1.013000e+00 0.907 0.171 5.989 0.014 0.989 Age 0.032 1.032000e+00 0.031 0.971 1.097 1.026 0.305 RaceBlack -3.064 4.700000e-02 1.798 0.001 1.583 -1.704 0.088 · RaceWhite -1.721 1.790000e-01 1.455 0.010 3.096 -1.183 0.237 Stage2 18.134 7.507363e+07 15217.985 0.000 Inf 0.001 0.999 Stage3 19.758 3.808376e+08 15217.985 0.000 Inf 0.001 0.999 Stage4 52.566 6.745659e+22 1931345.390 0.000 Inf 0.000 1.000 Purity 3.030 2.069500e+01 2.302 0.227 1885.920 1.316 0.188 Rsquare = 0.37 (max possible = 6.68e-01 ) Likelihood ratio test p = 6.38e-04 Wald test p = 1e+00 Score (logrank) test p = 4.16e-14 ELOVL1 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.467 1.595 0.429 0.688 3.699 1.088 0.276 Age 0.051 1.052 0.012 1.027 1.077 4.218 0.000 *** Gendermale -15.390 0.000 3459.980 0.000 Inf -0.004 0.996 RaceBlack -0.479 0.620 1.174 0.062 6.181 -0.408 0.683 RaceWhite 0.195 1.216 1.032 0.161 9.189 0.189 0.850 Stage2 0.404 1.498 0.382 0.709 3.167 1.059 0.290 Stage3 0.929 2.533 0.399 1.160 5.532 2.332 0.020 * Stage4 2.278 9.762 0.604 2.988 31.898 3.772 0.000 *** Purity 0.210 1.234 0.627 0.361 4.219 0.335 0.738 Rsquare = 0.072 (max possible = 6.81e-01 ) Likelihood ratio test p = 6.48e-05 Wald test p = 1.57e-05 Score (logrank) test p = 2.5e-07 ELOVL1 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.439 1.550 0.481 0.604 3.977 0.912 0.362 Age 0.055 1.057 0.022 1.013 1.102 2.549 0.011 * Gendermale 1.083 2.953 1.118 0.330 26.415 0.968 0.333 RaceBlack 16.625 16603125.370 6844.521 0.000 Inf 0.002 0.998 RaceWhite 15.957 8514526.491 6844.521 0.000 Inf 0.002 0.998 Stage2 0.753 2.123 1.072 0.260 17.358 0.702 0.483 Stage3 1.664 5.279 1.063 0.658 42.366 1.566 0.117 Stage4 2.141 8.507 1.174 0.852 84.959 1.823 0.068 · Purity 1.319 3.738 1.393 0.244 57.323 0.947 0.344 Rsquare = 0.11 (max possible = 6.98e-01 ) Likelihood ratio test p = 3.2e-02 Wald test p = 5.67e-02 Score (logrank) test p = 1.93e-02 ELOVL1 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.617 1.853 0.298 1.034 3.321 2.073 0.038 * Age 0.009 1.010 0.010 0.990 1.029 0.949 0.343 RaceBlack 1.003 2.726 1.068 0.336 22.109 0.939 0.348 RaceWhite 0.737 2.089 1.016 0.285 15.312 0.725 0.469 Purity 0.537 1.710 0.735 0.405 7.226 0.730 0.466 Rsquare = 0.032 (max possible = 8.91e-01 ) Likelihood ratio test p = 1.9e-01 Wald test p = 2.01e-01 Score (logrank) test p = 1.96e-01 ELOVL1 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.151 0.860 0.469 0.343 2.156 -0.322 0.747 Age 0.018 1.018 0.022 0.976 1.062 0.844 0.399 Gendermale 0.217 1.243 0.570 0.407 3.799 0.381 0.703 RaceBlack -0.341 0.711 1.488 0.038 13.140 -0.229 0.819 RaceWhite -1.083 0.339 0.891 0.059 1.941 -1.215 0.224 Stage2 0.666 1.946 0.672 0.522 7.256 0.991 0.322 Stage3 -15.741 0.000 6942.249 0.000 Inf -0.002 0.998 Stage4 0.776 2.172 0.689 0.563 8.383 1.126 0.260 Purity 1.991 7.326 1.574 0.335 160.054 1.266 0.206 Rsquare = 0.214 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.7e-01 Wald test p = 6.45e-01 Score (logrank) test p = 4.8e-01 ELOVL1 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.443 0.642 0.297 0.359 1.149 -1.493 0.135 Age 0.023 1.023 0.012 1.000 1.047 1.954 0.051 · Gendermale 0.192 1.212 0.269 0.715 2.053 0.714 0.475 RaceBlack -0.568 0.567 0.833 0.111 2.899 -0.682 0.495 RaceWhite -0.598 0.550 0.782 0.119 2.544 -0.765 0.444 Stage2 0.156 1.169 0.564 0.387 3.532 0.276 0.782 Stage3 0.864 2.373 0.550 0.807 6.977 1.571 0.116 Stage4 1.908 6.737 0.553 2.280 19.904 3.451 0.001 ** Purity -0.177 0.837 0.598 0.259 2.703 -0.297 0.767 Rsquare = 0.117 (max possible = 9.04e-01 ) Likelihood ratio test p = 1.9e-04 Wald test p = 7.94e-05 Score (logrank) test p = 1.02e-05 ELOVL1 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 3.350 28.492 1.981 0.586 1384.323 1.691 0.091 · Age -0.025 0.976 0.056 0.874 1.089 -0.442 0.659 Gendermale 0.902 2.464 1.071 0.302 20.104 0.842 0.400 RaceBlack 0.636 1.890 1.690 0.069 51.912 0.376 0.707 RaceWhite -3.333 0.036 1.709 0.001 1.017 -1.950 0.051 · Purity -1.822 0.162 2.371 0.002 16.847 -0.769 0.442 Rsquare = 0.208 (max possible = 5.58e-01 ) Likelihood ratio test p = 1.44e-01 Wald test p = 3.83e-01 Score (logrank) test p = 2.11e-01 ELOVL1 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.047 0.954 0.274 0.557 1.633 -0.172 0.863 Age 0.010 1.010 0.014 0.982 1.038 0.692 0.489 Gendermale 0.483 1.621 0.538 0.565 4.649 0.898 0.369 RaceBlack 0.358 1.430 1.075 0.174 11.764 0.333 0.739 RaceWhite -0.075 0.928 0.447 0.387 2.227 -0.168 0.867 Stage2 0.677 1.968 0.664 0.536 7.226 1.020 0.308 Stage3 1.438 4.210 0.677 1.117 15.872 2.123 0.034 * Stage4 2.853 17.345 0.776 3.789 79.406 3.676 0.000 *** Purity 0.218 1.243 0.768 0.276 5.605 0.283 0.777 Rsquare = 0.141 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.14e-02 Wald test p = 5.21e-03 Score (logrank) test p = 4.36e-04 ELOVL1 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.097 0.908 0.220 0.590 1.396 -0.441 0.660 Age 0.030 1.031 0.008 1.014 1.048 3.607 0.000 *** Gendermale -0.093 0.911 0.213 0.600 1.383 -0.438 0.661 RaceBlack 0.576 1.779 0.733 0.423 7.489 0.786 0.432 RaceWhite -0.205 0.815 0.619 0.242 2.740 -0.331 0.740 Purity -1.179 0.307 0.573 0.100 0.945 -2.058 0.040 * Rsquare = 0.13 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.44e-03 Wald test p = 6.7e-03 Score (logrank) test p = 5.8e-03 ELOVL1 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.082 1.085 0.158 0.796 1.479 0.516 0.606 Age 0.022 1.022 0.008 1.007 1.038 2.914 0.004 ** Gendermale -0.241 0.786 0.172 0.561 1.102 -1.395 0.163 RaceBlack 0.123 1.131 0.559 0.378 3.383 0.220 0.826 RaceWhite -0.258 0.773 0.511 0.284 2.105 -0.504 0.614 Stage2 0.610 1.841 0.544 0.634 5.344 1.122 0.262 Stage3 0.859 2.362 0.537 0.825 6.762 1.601 0.109 Stage4 1.262 3.531 0.510 1.300 9.595 2.474 0.013 * Purity -0.026 0.975 0.366 0.475 1.999 -0.070 0.944 Rsquare = 0.07 (max possible = 9.89e-01 ) Likelihood ratio test p = 4.75e-04 Wald test p = 1.25e-03 Score (logrank) test p = 9.1e-04 ELOVL1 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 1.068 2.909 0.614 0.872 9.701 1.738 0.082 · Age 0.002 1.002 0.025 0.954 1.052 0.077 0.938 Gendermale -0.010 0.991 0.553 0.335 2.925 -0.017 0.986 RaceBlack 18.024 67283583.145 12514.549 0.000 Inf 0.001 0.999 RaceWhite 17.461 38301504.842 12514.549 0.000 Inf 0.001 0.999 Stage2 17.724 49820743.033 5448.410 0.000 Inf 0.003 0.997 Stage3 17.047 25327456.305 5448.410 0.000 Inf 0.003 0.998 Stage4 17.674 47383832.368 5448.410 0.000 Inf 0.003 0.997 Purity -1.342 0.261 1.098 0.030 2.247 -1.222 0.222 Rsquare = 0.132 (max possible = 9.17e-01 ) Likelihood ratio test p = 4.22e-01 Wald test p = 7.12e-01 Score (logrank) test p = 5.59e-01 ELOVL1 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.027 1.028 0.173 0.733 1.441 0.159 0.874 Age 0.027 1.027 0.008 1.010 1.045 3.192 0.001 ** Gendermale -0.282 0.754 0.183 0.526 1.080 -1.539 0.124 RaceBlack -0.020 0.980 0.564 0.324 2.962 -0.035 0.972 RaceWhite -0.400 0.670 0.513 0.245 1.832 -0.780 0.436 Stage2 0.362 1.437 0.554 0.485 4.258 0.654 0.513 Stage3 0.728 2.072 0.541 0.718 5.980 1.346 0.178 Stage4 1.149 3.154 0.512 1.156 8.602 2.244 0.025 * Purity 0.217 1.243 0.403 0.564 2.738 0.539 0.590 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.37e-04 Wald test p = 9.41e-04 Score (logrank) test p = 7.11e-04 ELOVL1 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z ELOVL1 5.649 2.839050e+02 1.241 2.491900e+01 3.234627e+03 4.550 Age 0.059 1.060000e+00 0.028 1.003000e+00 1.121000e+00 2.072 Gendermale -1.071 3.430000e-01 0.787 7.300000e-02 1.602000e+00 -1.361 RaceBlack -18.565 0.000000e+00 11944.443 0.000000e+00 Inf -0.002 RaceWhite -2.189 1.120000e-01 1.220 1.000000e-02 1.224000e+00 -1.794 Stage2 16.888 2.160621e+07 0.880 3.850423e+06 1.212408e+08 19.191 Stage3 21.001 1.320231e+09 0.785 2.833526e+08 6.151377e+09 26.748 Stage4 21.564 2.318258e+09 0.980 3.395236e+08 1.582901e+10 22.001 Purity 7.754 2.330815e+03 4.477 3.600000e-01 1.509028e+07 1.732 p signif ELOVL1 0.000 *** Age 0.038 * Gendermale 0.173 RaceBlack 0.999 RaceWhite 0.073 · Stage2 0.000 *** Stage3 0.000 *** Stage4 0.000 *** Purity 0.083 · Rsquare = 0.446 (max possible = 6.71e-01 ) Likelihood ratio test p = 2.4e-05 Wald test p = 0e+00 Score (logrank) test p = 2.13e-09 ELOVL1 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.457 0.633 0.209 0.420 0.954 -2.185 0.029 * Age 0.033 1.033 0.008 1.017 1.051 3.912 0.000 *** Gendermale -0.171 0.843 0.189 0.582 1.220 -0.906 0.365 RaceBlack 0.111 1.118 1.056 0.141 8.859 0.105 0.916 RaceWhite 0.123 1.131 1.014 0.155 8.253 0.121 0.904 Stage2 0.210 1.233 0.345 0.627 2.425 0.608 0.543 Stage3 0.818 2.265 0.230 1.443 3.556 3.553 0.000 *** Stage4 1.787 5.973 0.216 3.907 9.129 8.255 0.000 *** Purity -0.088 0.916 0.366 0.447 1.876 -0.241 0.810 Rsquare = 0.182 (max possible = 9.65e-01 ) Likelihood ratio test p = 1.29e-15 Wald test p = 1.3e-15 Score (logrank) test p = 5.14e-19 ELOVL1 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.533 1.704 0.437 0.723 4.014 1.219 0.223 Age 0.013 1.013 0.016 0.982 1.046 0.825 0.409 Gendermale -0.401 0.670 0.392 0.310 1.444 -1.023 0.306 RaceBlack -1.857 0.156 1.203 0.015 1.651 -1.543 0.123 RaceWhite -1.973 0.139 1.179 0.014 1.403 -1.673 0.094 · Stage2 -0.432 0.649 1.053 0.082 5.117 -0.410 0.682 Stage3 1.644 5.174 0.424 2.252 11.888 3.873 0.000 *** Stage4 2.678 14.554 0.510 5.354 39.564 5.248 0.000 *** Purity -0.137 0.872 0.764 0.195 3.901 -0.179 0.858 Rsquare = 0.169 (max possible = 7.58e-01 ) Likelihood ratio test p = 6.05e-06 Wald test p = 1.86e-06 Score (logrank) test p = 3.34e-10 ELOVL1 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.771 2.163 0.257 1.307 3.580 3.000 0.003 ** Age 0.037 1.037 0.008 1.021 1.054 4.639 0.000 *** Gendermale -0.163 0.850 0.213 0.560 1.290 -0.763 0.445 RaceBlack -0.365 0.694 1.105 0.080 6.053 -0.330 0.741 RaceWhite -0.633 0.531 1.018 0.072 3.907 -0.621 0.534 Rsquare = 0.206 (max possible = 9.96e-01 ) Likelihood ratio test p = 2.06e-06 Wald test p = 5.18e-06 Score (logrank) test p = 3.06e-06 ELOVL1 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.318 1.375 0.112 1.103 1.714 2.834 0.005 ** Age 0.063 1.065 0.008 1.049 1.082 8.071 0.000 *** Gendermale 0.098 1.103 0.196 0.751 1.618 0.499 0.618 RaceBlack 16.574 15781118.812 2880.495 0.000 Inf 0.006 0.995 RaceWhite 16.624 16584491.131 2880.495 0.000 Inf 0.006 0.995 Purity -0.446 0.640 0.464 0.258 1.590 -0.960 0.337 Rsquare = 0.151 (max possible = 9.07e-01 ) Likelihood ratio test p = 2.44e-14 Wald test p = 9.47e-14 Score (logrank) test p = 3.64e-15 ELOVL1 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.530 1.699 0.149 1.268 2.276 3.548 0.000 *** Age 0.015 1.015 0.008 0.998 1.031 1.767 0.077 · Gendermale 0.015 1.015 0.231 0.645 1.598 0.064 0.949 RaceBlack 0.855 2.351 0.493 0.895 6.177 1.735 0.083 · RaceWhite 0.035 1.036 0.239 0.648 1.656 0.147 0.883 Stage2 0.197 1.218 0.264 0.726 2.043 0.747 0.455 Stage3 0.800 2.225 0.242 1.385 3.575 3.306 0.001 ** Stage4 1.684 5.386 0.622 1.591 18.233 2.706 0.007 ** Purity 0.690 1.995 0.470 0.793 5.016 1.467 0.142 Rsquare = 0.12 (max possible = 9.66e-01 ) Likelihood ratio test p = 8.99e-06 Wald test p = 4.3e-06 Score (logrank) test p = 1.59e-06 ELOVL1 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.041 1.042 0.172 0.745 1.459 0.242 0.809 Age 0.007 1.007 0.009 0.989 1.025 0.765 0.444 Gendermale 0.022 1.023 0.170 0.733 1.427 0.131 0.895 RaceBlack 16.096 9780779.997 1886.503 0.000 Inf 0.009 0.993 RaceWhite 16.267 11600980.899 1886.503 0.000 Inf 0.009 0.993 Stage2 0.862 2.368 0.201 1.596 3.513 4.280 0.000 *** Stage3 1.010 2.745 0.219 1.788 4.212 4.619 0.000 *** Stage4 1.011 2.747 0.335 1.426 5.293 3.019 0.003 ** Purity 0.590 1.803 0.343 0.920 3.534 1.718 0.086 · Rsquare = 0.097 (max possible = 9.74e-01 ) Likelihood ratio test p = 2.34e-06 Wald test p = 3e-05 Score (logrank) test p = 3.47e-06 ELOVL1 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.224 1.252 0.169 0.898 1.744 1.327 0.185 Age 0.015 1.015 0.009 0.997 1.034 1.605 0.109 Gendermale 0.435 1.546 0.193 1.059 2.257 2.255 0.024 * RaceBlack 0.082 1.085 0.614 0.326 3.615 0.133 0.894 RaceWhite -0.449 0.639 0.570 0.209 1.953 -0.786 0.432 Stage2 0.203 1.225 0.187 0.850 1.767 1.087 0.277 Stage3 0.552 1.737 0.218 1.132 2.663 2.530 0.011 * Stage4 0.788 2.198 0.801 0.457 10.567 0.983 0.326 Purity -0.340 0.712 0.365 0.348 1.457 -0.930 0.353 Rsquare = 0.055 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.33e-02 Wald test p = 9.31e-03 Score (logrank) test p = 8.04e-03 ELOVL1 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.656 1.927 0.255 1.169 3.178 2.572 0.010 * Age 0.023 1.024 0.016 0.992 1.056 1.444 0.149 Gendermale -0.371 0.690 0.338 0.356 1.338 -1.098 0.272 RaceBlack -0.712 0.491 1.568 0.023 10.601 -0.454 0.650 RaceWhite -1.284 0.277 1.098 0.032 2.381 -1.169 0.242 Stage2 -0.238 0.788 0.471 0.313 1.983 -0.506 0.613 Stage3 -0.029 0.971 0.421 0.426 2.215 -0.069 0.945 Stage4 -0.021 0.980 0.477 0.384 2.497 -0.043 0.966 Purity -0.654 0.520 0.570 0.170 1.587 -1.149 0.251 Rsquare = 0.131 (max possible = 9.98e-01 ) Likelihood ratio test p = 2.15e-01 Wald test p = 2.16e-01 Score (logrank) test p = 2.18e-01 ELOVL1 in OV (n=303): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.111 0.895 0.157 0.658 1.218 -0.705 0.481 Age 0.035 1.035 0.008 1.019 1.052 4.186 0.000 *** RaceBlack -0.060 0.941 0.577 0.304 2.917 -0.105 0.917 RaceWhite -0.145 0.865 0.515 0.315 2.374 -0.282 0.778 Purity -0.691 0.501 0.696 0.128 1.959 -0.994 0.320 Rsquare = 0.083 (max possible = 9.97e-01 ) Likelihood ratio test p = 9.31e-04 Wald test p = 7.73e-04 Score (logrank) test p = 6.36e-04 ELOVL1 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.365 1.440 0.199 0.974 2.128 1.830 0.067 · Age 0.022 1.022 0.011 1.001 1.044 2.020 0.043 * Gendermale -0.211 0.810 0.217 0.529 1.239 -0.972 0.331 RaceBlack -0.018 0.983 0.737 0.232 4.168 -0.024 0.981 RaceWhite 0.402 1.494 0.475 0.589 3.792 0.845 0.398 Stage2 0.484 1.623 0.438 0.687 3.831 1.105 0.269 Stage3 -0.160 0.853 1.092 0.100 7.249 -0.146 0.884 Stage4 0.025 1.025 0.828 0.202 5.196 0.030 0.976 Purity -0.573 0.564 0.415 0.250 1.273 -1.380 0.168 Rsquare = 0.108 (max possible = 9.91e-01 ) Likelihood ratio test p = 2.65e-02 Wald test p = 4.79e-02 Score (logrank) test p = 4.56e-02 ELOVL1 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.225 0.799 0.824 0.159 4.012 -0.273 0.785 Age 0.038 1.038 0.028 0.982 1.098 1.323 0.186 Gendermale 1.463 4.319 0.924 0.706 26.420 1.583 0.113 RaceBlack -0.219 0.803 19479.963 0.000 Inf 0.000 1.000 RaceWhite 17.237 30629283.703 15547.831 0.000 Inf 0.001 0.999 Purity 5.382 217.414 3.487 0.234 202140.055 1.543 0.123 Rsquare = 0.055 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.58e-01 Wald test p = 4.17e-01 Score (logrank) test p = 3.1e-01 ELOVL1 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.103 1.108 0.645 0.313 3.922 0.159 0.874 Age 0.010 1.010 0.058 0.902 1.131 0.179 0.858 RaceBlack 15.070 3504792.583 6691.175 0.000 Inf 0.002 0.998 RaceWhite 16.302 12014384.681 6691.175 0.000 Inf 0.002 0.998 Purity 1.127 3.086 1.420 0.191 49.863 0.794 0.427 Rsquare = 0.007 (max possible = 1.83e-01 ) Likelihood ratio test p = 7.41e-01 Wald test p = 8.63e-01 Score (logrank) test p = 8.11e-01 ELOVL1 in READ (n=166): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.144 0.866 0.772 0.191 3.931 -0.187 0.852 Age 0.110 1.116 0.044 1.024 1.216 2.500 0.012 * Gendermale -0.340 0.712 0.688 0.185 2.739 -0.495 0.621 RaceBlack 13.423 675375.462 10703.645 0.000 Inf 0.001 0.999 RaceWhite 12.427 249450.882 10703.645 0.000 Inf 0.001 0.999 Stage2 -1.896 0.150 1.276 0.012 1.831 -1.486 0.137 Stage3 -0.546 0.579 0.967 0.087 3.857 -0.565 0.572 Stage4 -0.196 0.822 0.991 0.118 5.730 -0.198 0.843 Purity 0.067 1.069 1.371 0.073 15.697 0.049 0.961 Rsquare = 0.21 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.66e-02 Wald test p = 2.24e-01 Score (logrank) test p = 3.96e-02 ELOVL1 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.134 1.144 0.201 0.772 1.695 0.669 0.503 Age 0.022 1.022 0.008 1.006 1.039 2.632 0.008 ** Gendermale 0.000 1.000 0.223 0.647 1.548 0.002 0.999 RaceBlack -0.122 0.885 1.086 0.105 7.439 -0.112 0.911 RaceWhite -0.481 0.618 1.023 0.083 4.589 -0.470 0.638 Purity 1.001 2.722 0.580 0.873 8.484 1.726 0.084 · Rsquare = 0.044 (max possible = 9.75e-01 ) Likelihood ratio test p = 1.03e-01 Wald test p = 1.35e-01 Score (logrank) test p = 1.36e-01 ELOVL1 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.035 1.036 0.119 0.820 1.309 0.296 0.767 Age 0.018 1.018 0.005 1.008 1.029 3.521 0.000 *** Gendermale -0.048 0.953 0.157 0.700 1.298 -0.305 0.760 RaceWhite -1.275 0.279 0.403 0.127 0.616 -3.162 0.002 ** Stage2 0.273 1.314 0.218 0.857 2.016 1.252 0.210 Stage3 0.610 1.840 0.204 1.234 2.745 2.989 0.003 ** Stage4 1.347 3.847 0.352 1.930 7.668 3.829 0.000 *** Purity 1.032 2.806 0.343 1.433 5.496 3.009 0.003 ** Rsquare = 0.124 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.15e-08 Wald test p = 1.23e-08 Score (logrank) test p = 1.43e-09 ELOVL1 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.022 9.780000e-01 0.382 0.463 2.066 -0.059 0.953 Age 0.012 1.012000e+00 0.016 0.980 1.045 0.739 0.460 Gendermale 0.219 1.245000e+00 0.448 0.518 2.994 0.490 0.624 RaceWhite -1.279 2.780000e-01 0.669 0.075 1.033 -1.911 0.056 · Stage2 17.468 3.856844e+07 6197.461 0.000 Inf 0.003 0.998 Stage3 17.967 6.355847e+07 6197.461 0.000 Inf 0.003 0.998 Stage4 20.100 5.360585e+08 6197.461 0.000 Inf 0.003 0.997 Purity 0.246 1.279000e+00 1.052 0.163 10.057 0.234 0.815 Rsquare = 0.147 (max possible = 8.69e-01 ) Likelihood ratio test p = 6.13e-02 Wald test p = 5.52e-02 Score (logrank) test p = 4.58e-03 ELOVL1 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.007 0.993 0.129 0.772 1.278 -0.054 0.957 Age 0.021 1.021 0.006 1.010 1.032 3.652 0.000 *** Gendermale -0.059 0.943 0.172 0.672 1.322 -0.341 0.733 RaceWhite -1.058 0.347 0.600 0.107 1.126 -1.762 0.078 · Stage2 0.152 1.164 0.230 0.741 1.829 0.661 0.509 Stage3 0.563 1.756 0.209 1.166 2.645 2.695 0.007 ** Stage4 1.134 3.109 0.400 1.420 6.805 2.837 0.005 ** Purity 1.142 3.132 0.372 1.512 6.489 3.072 0.002 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.1e-06 Wald test p = 1.7e-06 Score (logrank) test p = 6.48e-07 ELOVL1 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 -0.366 0.694 0.186 0.482 0.998 -1.970 0.049 * Age 0.027 1.028 0.010 1.008 1.048 2.711 0.007 ** Gendermale 0.122 1.129 0.208 0.752 1.697 0.586 0.558 RaceBlack 0.335 1.398 0.450 0.579 3.376 0.744 0.457 RaceWhite 0.213 1.238 0.251 0.757 2.026 0.850 0.396 Stage2 0.549 1.732 0.392 0.803 3.737 1.399 0.162 Stage3 0.942 2.564 0.364 1.256 5.236 2.585 0.010 * Stage4 1.347 3.845 0.502 1.438 10.279 2.685 0.007 ** Purity -0.515 0.598 0.377 0.285 1.251 -1.366 0.172 Rsquare = 0.082 (max possible = 9.79e-01 ) Likelihood ratio test p = 3.32e-03 Wald test p = 4.92e-03 Score (logrank) test p = 3.96e-03 ELOVL1 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 2.982 19.732 22463.181 0 Inf 0.000 1.000 Age -1.570 0.208 1887.946 0 Inf -0.001 0.999 RaceBlack 0.980 2.665 17276624.453 0 Inf 0.000 1.000 RaceWhite -39.172 0.000 17963116.985 0 Inf 0.000 1.000 Stage2 -1.558 0.211 41542.252 0 Inf 0.000 1.000 Stage3 13.557 772088.665 141054.708 0 Inf 0.000 1.000 Purity 3.996 54.400 223034.239 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 2.52e-03 ELOVL1 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.390 1.477 0.430 0.635 3.435 0.907 0.365 Age 0.144 1.155 0.028 1.094 1.220 5.179 0.000 *** Gendermale -0.168 0.845 0.653 0.235 3.038 -0.258 0.797 RaceBlack 16.828 20330803.669 6779.470 0.000 Inf 0.002 0.998 RaceWhite 16.877 21351467.430 6779.470 0.000 Inf 0.002 0.998 Stage2 0.047 1.048 1.104 0.120 9.131 0.043 0.966 Stage3 0.284 1.329 0.856 0.248 7.118 0.332 0.740 Stage4 1.726 5.616 0.987 0.811 38.875 1.748 0.080 · Purity 2.025 7.579 1.111 0.859 66.875 1.823 0.068 · Rsquare = 0.151 (max possible = 3.47e-01 ) Likelihood ratio test p = 1.75e-10 Wald test p = 1.66e-04 Score (logrank) test p = 3.63e-11 ELOVL1 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.053 1.055 0.941 0.167 6.670 0.057 0.955 Age 0.049 1.051 0.031 0.988 1.117 1.572 0.116 Gendermale -0.183 0.833 0.736 0.197 3.523 -0.248 0.804 RaceBlack -16.570 0.000 10092.528 0.000 Inf -0.002 0.999 RaceWhite 0.518 1.678 1.137 0.181 15.587 0.455 0.649 Purity 0.385 1.469 1.095 0.172 12.577 0.351 0.725 Rsquare = 0.044 (max possible = 4.51e-01 ) Likelihood ratio test p = 5.31e-01 Wald test p = 6.66e-01 Score (logrank) test p = 5.75e-01 ELOVL1 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.202 1.224 0.257 0.741 2.024 0.789 0.430 Age 0.050 1.051 0.016 1.019 1.085 3.150 0.002 ** RaceBlack -0.450 0.637 0.797 0.134 3.037 -0.565 0.572 RaceWhite -0.539 0.583 0.746 0.135 2.519 -0.722 0.470 Purity 0.442 1.556 0.647 0.438 5.529 0.684 0.494 Rsquare = 0.04 (max possible = 7.81e-01 ) Likelihood ratio test p = 3.95e-02 Wald test p = 4.85e-02 Score (logrank) test p = 4.88e-02 ELOVL1 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.115 1.122 0.357 0.557 2.259 0.322 0.748 Age 0.041 1.042 0.025 0.991 1.095 1.603 0.109 RaceBlack 17.599 43969505.570 6480.505 0.000 Inf 0.003 0.998 RaceWhite 17.874 57904403.666 6480.505 0.000 Inf 0.003 0.998 Purity -0.720 0.487 1.152 0.051 4.656 -0.625 0.532 Rsquare = 0.121 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.45e-01 Wald test p = 3.51e-01 Score (logrank) test p = 2.57e-01 ELOVL1 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ELOVL1` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL1 0.839 2.313 0.376 1.108 4.831 2.232 0.026 * Age 0.045 1.046 0.019 1.007 1.086 2.295 0.022 * Gendermale 0.301 1.351 0.468 0.540 3.380 0.642 0.521 Stage3 0.045 1.046 0.500 0.392 2.786 0.089 0.929 Stage4 3.866 47.770 1.224 4.336 526.306 3.158 0.002 ** Purity 2.000 7.389 1.253 0.634 86.081 1.597 0.110 Rsquare = 0.302 (max possible = 8.72e-01 ) Likelihood ratio test p = 1.09e-04 Wald test p = 7.59e-04 Score (logrank) test p = 3.37e-10 ELOVL2 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.095 0.910 0.319 0.487 1.699 -0.297 0.767 Age 0.004 1.004 0.014 0.978 1.031 0.315 0.753 Gendermale 0.374 1.454 0.417 0.642 3.291 0.898 0.369 RaceBlack 0.070 1.073 11964.629 0.000 Inf 0.000 1.000 RaceWhite 16.948 22940084.169 10187.961 0.000 Inf 0.002 0.999 Purity 2.992 19.921 2.315 0.213 1861.821 1.292 0.196 Rsquare = 0.068 (max possible = 9.38e-01 ) Likelihood ratio test p = 6.12e-01 Wald test p = 8.95e-01 Score (logrank) test p = 7.55e-01 ELOVL2 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.080 0.923 0.146 0.694 1.229 -0.548 0.584 Age 0.034 1.034 0.009 1.017 1.052 3.927 0.000 *** Gendermale -0.187 0.829 0.181 0.582 1.181 -1.037 0.300 RaceBlack 0.737 2.089 0.449 0.867 5.034 1.642 0.101 RaceWhite 0.123 1.131 0.355 0.564 2.267 0.347 0.728 Stage2 14.493 1969817.228 1866.234 0.000 Inf 0.008 0.994 Stage3 14.925 3032747.300 1866.234 0.000 Inf 0.008 0.994 Stage4 15.467 5212146.959 1866.234 0.000 Inf 0.008 0.993 Purity 0.111 1.118 0.343 0.570 2.190 0.324 0.746 Rsquare = 0.131 (max possible = 9.91e-01 ) Likelihood ratio test p = 1.77e-07 Wald test p = 1.09e-06 Score (logrank) test p = 2.95e-07 ELOVL2 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.111 0.895 0.047 0.816 0.980 -2.382 0.017 * Age 0.037 1.037 0.008 1.022 1.053 4.862 0.000 *** Gendermale 0.129 1.138 1.007 0.158 8.195 0.128 0.898 RaceBlack -0.030 0.971 0.619 0.289 3.262 -0.048 0.961 RaceWhite -0.182 0.834 0.596 0.259 2.682 -0.305 0.761 Stage2 0.381 1.464 0.304 0.806 2.658 1.253 0.210 Stage3 1.194 3.299 0.313 1.787 6.090 3.817 0.000 *** Stage4 2.270 9.683 0.400 4.419 21.218 5.672 0.000 *** Purity 0.647 1.909 0.427 0.827 4.408 1.515 0.130 Rsquare = 0.087 (max possible = 7.85e-01 ) Likelihood ratio test p = 1.71e-13 Wald test p = 6.53e-17 Score (logrank) test p = 4.18e-23 ELOVL2 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.237 7.890000e-01 0.165 0.571 1.092 -1.431 0.153 Age 0.015 1.015000e+00 0.018 0.981 1.051 0.847 0.397 RaceBlack -0.958 3.840000e-01 1.152 0.040 3.670 -0.831 0.406 RaceWhite -1.341 2.620000e-01 1.173 0.026 2.608 -1.143 0.253 Stage2 18.576 1.167588e+08 6442.743 0.000 Inf 0.003 0.998 Stage3 20.107 5.397344e+08 6442.743 0.000 Inf 0.003 0.998 Stage4 21.372 1.913873e+09 6442.743 0.000 Inf 0.003 0.997 Purity 1.330 3.782000e+00 1.046 0.487 29.353 1.272 0.203 Rsquare = 0.168 (max possible = 7.18e-01 ) Likelihood ratio test p = 2.09e-04 Wald test p = 2.59e-03 Score (logrank) test p = 1.57e-06 ELOVL2 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.293 1.340000e+00 0.596 0.416 4.311 0.491 0.624 Age 0.034 1.034000e+00 0.028 0.978 1.094 1.188 0.235 RaceBlack -3.116 4.400000e-02 1.802 0.001 1.516 -1.729 0.084 · RaceWhite -1.767 1.710000e-01 1.452 0.010 2.940 -1.217 0.224 Stage2 18.019 6.692989e+07 15087.134 0.000 Inf 0.001 0.999 Stage3 19.684 3.535688e+08 15087.134 0.000 Inf 0.001 0.999 Stage4 52.504 6.341946e+22 1880027.221 0.000 Inf 0.000 1.000 Purity 3.082 2.180600e+01 2.271 0.254 1869.860 1.357 0.175 Rsquare = 0.372 (max possible = 6.68e-01 ) Likelihood ratio test p = 5.9e-04 Wald test p = 1e+00 Score (logrank) test p = 3.83e-14 ELOVL2 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.050 0.951 0.072 0.825 1.096 -0.698 0.485 Age 0.048 1.049 0.012 1.025 1.074 4.033 0.000 *** Gendermale -15.465 0.000 3468.467 0.000 Inf -0.004 0.996 RaceBlack -0.324 0.723 1.184 0.071 7.357 -0.274 0.784 RaceWhite 0.328 1.388 1.038 0.181 10.617 0.316 0.752 Stage2 0.330 1.390 0.374 0.668 2.894 0.881 0.378 Stage3 0.838 2.311 0.394 1.067 5.006 2.123 0.034 * Stage4 2.059 7.837 0.605 2.394 25.648 3.403 0.001 ** Purity 0.369 1.447 0.618 0.430 4.863 0.597 0.550 Rsquare = 0.071 (max possible = 6.81e-01 ) Likelihood ratio test p = 8.57e-05 Wald test p = 1.49e-05 Score (logrank) test p = 2.61e-07 ELOVL2 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.193 0.824 0.111 0.663 1.025 -1.737 0.082 · Age 0.047 1.048 0.021 1.006 1.093 2.230 0.026 * Gendermale 1.507 4.513 1.143 0.480 42.395 1.319 0.187 RaceBlack 15.825 7460901.455 6176.002 0.000 Inf 0.003 0.998 RaceWhite 15.458 5165481.468 6176.002 0.000 Inf 0.003 0.998 Stage2 0.953 2.594 1.085 0.309 21.774 0.878 0.380 Stage3 1.922 6.835 1.076 0.829 56.340 1.786 0.074 · Stage4 1.831 6.238 1.167 0.634 61.422 1.569 0.117 Purity 1.295 3.652 1.364 0.252 52.923 0.950 0.342 Rsquare = 0.123 (max possible = 6.98e-01 ) Likelihood ratio test p = 1.43e-02 Wald test p = 3.65e-02 Score (logrank) test p = 1.27e-02 ELOVL2 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.279 1.322 0.205 0.884 1.977 1.360 0.174 Age 0.011 1.011 0.010 0.991 1.031 1.059 0.290 RaceBlack 1.286 3.620 1.099 0.420 31.184 1.171 0.242 RaceWhite 1.058 2.881 1.045 0.372 22.335 1.012 0.311 Purity 0.720 2.054 0.742 0.480 8.788 0.970 0.332 Rsquare = 0.021 (max possible = 8.91e-01 ) Likelihood ratio test p = 4.5e-01 Wald test p = 4.78e-01 Score (logrank) test p = 4.74e-01 ELOVL2 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.048 0.953 0.243 0.592 1.533 -0.199 0.842 Age 0.020 1.020 0.025 0.972 1.070 0.809 0.419 Gendermale 0.236 1.266 0.569 0.415 3.862 0.415 0.678 RaceBlack -0.160 0.853 1.768 0.027 27.264 -0.090 0.928 RaceWhite -0.973 0.378 1.024 0.051 2.813 -0.950 0.342 Stage2 0.709 2.032 0.715 0.501 8.244 0.992 0.321 Stage3 -15.703 0.000 6951.821 0.000 Inf -0.002 0.998 Stage4 0.753 2.124 0.753 0.486 9.286 1.001 0.317 Purity 2.005 7.426 1.563 0.347 158.824 1.283 0.199 Rsquare = 0.212 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.76e-01 Wald test p = 6.56e-01 Score (logrank) test p = 4.87e-01 ELOVL2 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.566 1.762 0.378 0.840 3.696 1.499 0.134 Age 0.027 1.027 0.012 1.004 1.051 2.258 0.024 * Gendermale 0.237 1.268 0.271 0.745 2.158 0.874 0.382 RaceBlack -0.556 0.574 0.828 0.113 2.908 -0.671 0.502 RaceWhite -0.543 0.581 0.775 0.127 2.651 -0.701 0.483 Stage2 0.187 1.206 0.563 0.400 3.633 0.333 0.739 Stage3 0.834 2.302 0.550 0.783 6.769 1.515 0.130 Stage4 1.908 6.741 0.554 2.276 19.966 3.444 0.001 ** Purity -0.038 0.962 0.605 0.294 3.153 -0.063 0.949 Rsquare = 0.116 (max possible = 9.04e-01 ) Likelihood ratio test p = 2.26e-04 Wald test p = 8.27e-05 Score (logrank) test p = 1.2e-05 ELOVL2 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.066 0.936 1.132 0.102 8.613 -0.058 0.953 Age -0.004 0.996 0.042 0.918 1.082 -0.087 0.930 Gendermale 0.652 1.918 1.058 0.241 15.266 0.616 0.538 RaceBlack 0.372 1.450 1.586 0.065 32.485 0.234 0.815 RaceWhite -2.091 0.124 1.365 0.009 1.792 -1.533 0.125 Purity -2.046 0.129 2.116 0.002 8.180 -0.967 0.334 Rsquare = 0.131 (max possible = 5.58e-01 ) Likelihood ratio test p = 4.52e-01 Wald test p = 5.97e-01 Score (logrank) test p = 3.38e-01 ELOVL2 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.033 0.967 0.210 0.641 1.460 -0.157 0.875 Age 0.009 1.009 0.014 0.981 1.038 0.637 0.524 Gendermale 0.470 1.600 0.542 0.553 4.630 0.866 0.386 RaceBlack 0.315 1.370 1.076 0.166 11.297 0.293 0.770 RaceWhite -0.080 0.923 0.446 0.385 2.214 -0.179 0.858 Stage2 0.708 2.029 0.657 0.560 7.354 1.077 0.281 Stage3 1.459 4.301 0.671 1.156 16.006 2.176 0.030 * Stage4 2.862 17.504 0.774 3.840 79.786 3.699 0.000 *** Purity 0.192 1.212 0.782 0.262 5.608 0.246 0.806 Rsquare = 0.141 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.14e-02 Wald test p = 5.28e-03 Score (logrank) test p = 4.38e-04 ELOVL2 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.032 1.033 0.066 0.907 1.176 0.488 0.626 Age 0.029 1.029 0.009 1.012 1.046 3.344 0.001 ** Gendermale -0.071 0.931 0.218 0.607 1.429 -0.326 0.744 RaceBlack 0.524 1.688 0.725 0.408 6.994 0.722 0.470 RaceWhite -0.253 0.776 0.614 0.233 2.585 -0.413 0.680 Purity -1.139 0.320 0.544 0.110 0.929 -2.095 0.036 * Rsquare = 0.131 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.36e-03 Wald test p = 6.67e-03 Score (logrank) test p = 5.79e-03 ELOVL2 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.156 0.855 0.147 0.641 1.141 -1.062 0.288 Age 0.023 1.023 0.008 1.008 1.038 2.952 0.003 ** Gendermale -0.250 0.779 0.172 0.556 1.090 -1.456 0.145 RaceBlack 0.154 1.167 0.559 0.390 3.493 0.276 0.782 RaceWhite -0.243 0.784 0.511 0.288 2.135 -0.475 0.635 Stage2 0.624 1.867 0.544 0.643 5.420 1.149 0.251 Stage3 0.837 2.309 0.537 0.806 6.613 1.559 0.119 Stage4 1.276 3.584 0.510 1.318 9.747 2.501 0.012 * Purity -0.066 0.936 0.365 0.457 1.916 -0.180 0.857 Rsquare = 0.072 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.29e-04 Wald test p = 9.88e-04 Score (logrank) test p = 7.41e-04 ELOVL2 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.268 1.307000e+00 0.336 0.677 2.524 0.798 0.425 Age 0.007 1.007000e+00 0.026 0.958 1.059 0.283 0.777 Gendermale -0.290 7.480000e-01 0.566 0.247 2.267 -0.513 0.608 RaceBlack 19.525 3.017900e+08 12097.890 0.000 Inf 0.002 0.999 RaceWhite 18.540 1.127014e+08 12097.890 0.000 Inf 0.002 0.999 Stage2 17.281 3.200156e+07 5295.049 0.000 Inf 0.003 0.997 Stage3 16.622 1.654870e+07 5295.049 0.000 Inf 0.003 0.997 Stage4 17.485 3.922872e+07 5295.049 0.000 Inf 0.003 0.997 Purity -1.765 1.710000e-01 1.118 0.019 1.532 -1.578 0.114 Rsquare = 0.095 (max possible = 9.17e-01 ) Likelihood ratio test p = 6.88e-01 Wald test p = 9.31e-01 Score (logrank) test p = 8.27e-01 ELOVL2 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.247 0.781 0.170 0.560 1.091 -1.448 0.148 Age 0.027 1.027 0.008 1.011 1.044 3.227 0.001 ** Gendermale -0.296 0.744 0.183 0.520 1.064 -1.618 0.106 RaceBlack 0.054 1.055 0.567 0.347 3.206 0.095 0.924 RaceWhite -0.368 0.692 0.513 0.253 1.892 -0.717 0.473 Stage2 0.381 1.464 0.554 0.494 4.332 0.688 0.492 Stage3 0.717 2.049 0.541 0.710 5.915 1.326 0.185 Stage4 1.191 3.289 0.513 1.204 8.987 2.322 0.020 * Purity 0.152 1.164 0.405 0.526 2.574 0.375 0.708 Rsquare = 0.091 (max possible = 9.89e-01 ) Likelihood ratio test p = 1.36e-04 Wald test p = 4.36e-04 Score (logrank) test p = 3.4e-04 ELOVL2 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ELOVL2 -3.432 3.200000e-02 1.538 2.000000e-03 6.580000e-01 -2.232 0.026 Age 0.088 1.092000e+00 0.030 1.029000e+00 1.158000e+00 2.907 0.004 Gendermale -0.983 3.740000e-01 0.739 8.800000e-02 1.593000e+00 -1.330 0.183 RaceBlack -19.503 0.000000e+00 6126.622 0.000000e+00 Inf -0.003 0.997 RaceWhite -4.303 1.400000e-02 1.182 1.000000e-03 1.370000e-01 -3.640 0.000 Stage2 18.102 7.270754e+07 0.858 1.353769e+07 3.904940e+08 21.106 0.000 Stage3 19.016 1.813379e+08 0.778 3.948140e+07 8.328841e+08 24.447 0.000 Stage4 21.319 1.813739e+09 0.924 2.964988e+08 1.109499e+10 23.071 0.000 Purity -3.383 3.400000e-02 3.792 0.000000e+00 5.741800e+01 -0.892 0.372 signif ELOVL2 * Age ** Gendermale RaceBlack RaceWhite *** Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.369 (max possible = 6.71e-01 ) Likelihood ratio test p = 6.52e-04 Wald test p = 0e+00 Score (logrank) test p = 9.24e-09 ELOVL2 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.058 1.060 0.110 0.855 1.315 0.533 0.594 Age 0.035 1.036 0.008 1.019 1.053 4.178 0.000 *** Gendermale -0.074 0.929 0.184 0.647 1.333 -0.401 0.689 RaceBlack 0.209 1.232 1.056 0.156 9.751 0.198 0.843 RaceWhite 0.139 1.149 1.014 0.157 8.385 0.137 0.891 Stage2 0.212 1.236 0.344 0.629 2.428 0.616 0.538 Stage3 0.815 2.259 0.230 1.440 3.544 3.546 0.000 *** Stage4 1.753 5.774 0.216 3.781 8.818 8.116 0.000 *** Purity 0.029 1.030 0.373 0.495 2.141 0.078 0.937 Rsquare = 0.174 (max possible = 9.65e-01 ) Likelihood ratio test p = 9.12e-15 Wald test p = 9.65e-15 Score (logrank) test p = 5.08e-18 ELOVL2 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.818 2.265 0.217 1.480 3.468 3.764 0.000 *** Age 0.011 1.011 0.016 0.979 1.044 0.656 0.512 Gendermale -0.157 0.855 0.417 0.377 1.937 -0.376 0.707 RaceBlack -1.956 0.141 1.206 0.013 1.502 -1.622 0.105 RaceWhite -1.680 0.186 1.211 0.017 2.002 -1.387 0.165 Stage2 -0.377 0.686 1.055 0.087 5.417 -0.358 0.720 Stage3 1.457 4.294 0.449 1.780 10.359 3.243 0.001 ** Stage4 2.770 15.959 0.524 5.709 44.610 5.282 0.000 *** Purity -0.820 0.440 0.771 0.097 1.996 -1.064 0.288 Rsquare = 0.208 (max possible = 7.58e-01 ) Likelihood ratio test p = 6.39e-08 Wald test p = 3.35e-09 Score (logrank) test p = 9.88e-15 ELOVL2 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.169 0.845 0.239 0.529 1.350 -0.705 0.481 Age 0.039 1.040 0.008 1.023 1.057 4.696 0.000 *** Gendermale -0.126 0.882 0.212 0.582 1.336 -0.594 0.552 RaceBlack -0.344 0.709 1.106 0.081 6.191 -0.311 0.756 RaceWhite -0.672 0.511 1.019 0.069 3.761 -0.660 0.509 Rsquare = 0.159 (max possible = 9.96e-01 ) Likelihood ratio test p = 1e-04 Wald test p = 3.7e-04 Score (logrank) test p = 2.63e-04 ELOVL2 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.265 1.303 0.074 1.126 1.507 3.557 0.000 *** Age 0.064 1.066 0.008 1.049 1.082 8.121 0.000 *** Gendermale 0.117 1.124 0.195 0.767 1.647 0.599 0.549 RaceBlack 15.429 5022244.459 1957.350 0.000 Inf 0.008 0.994 RaceWhite 15.430 5025046.498 1957.350 0.000 Inf 0.008 0.994 Purity -0.732 0.481 0.419 0.212 1.092 -1.749 0.080 · Rsquare = 0.16 (max possible = 9.07e-01 ) Likelihood ratio test p = 2.46e-15 Wald test p = 5.43e-15 Score (logrank) test p = 3.07e-16 ELOVL2 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.025 1.025 0.065 0.902 1.165 0.377 0.706 Age 0.011 1.011 0.008 0.995 1.027 1.351 0.177 Gendermale -0.137 0.872 0.226 0.560 1.357 -0.608 0.543 RaceBlack 0.898 2.454 0.490 0.939 6.416 1.831 0.067 · RaceWhite 0.020 1.020 0.241 0.636 1.636 0.081 0.935 Stage2 0.321 1.378 0.262 0.825 2.302 1.225 0.221 Stage3 0.951 2.588 0.234 1.635 4.098 4.058 0.000 *** Stage4 1.607 4.986 0.620 1.480 16.801 2.592 0.010 * Purity 0.574 1.776 0.459 0.722 4.368 1.251 0.211 Rsquare = 0.085 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.14e-03 Wald test p = 6.86e-04 Score (logrank) test p = 2.63e-04 ELOVL2 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.170 1.185 0.108 0.958 1.465 1.568 0.117 Age 0.008 1.008 0.009 0.990 1.026 0.870 0.384 Gendermale -0.009 0.991 0.170 0.710 1.385 -0.051 0.960 RaceBlack 16.071 9543849.766 1916.250 0.000 Inf 0.008 0.993 RaceWhite 16.221 11085030.969 1916.250 0.000 Inf 0.008 0.993 Stage2 0.856 2.353 0.201 1.587 3.489 4.256 0.000 *** Stage3 1.009 2.744 0.218 1.790 4.206 4.631 0.000 *** Stage4 0.948 2.581 0.338 1.332 5.002 2.808 0.005 ** Purity 0.584 1.793 0.343 0.915 3.514 1.700 0.089 · Rsquare = 0.101 (max possible = 9.74e-01 ) Likelihood ratio test p = 9.2e-07 Wald test p = 1.03e-05 Score (logrank) test p = 1.04e-06 ELOVL2 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.063 0.939 0.079 0.805 1.095 -0.807 0.420 Age 0.017 1.017 0.009 0.999 1.036 1.815 0.070 · Gendermale 0.424 1.529 0.194 1.045 2.235 2.189 0.029 * RaceBlack 0.013 1.014 0.605 0.310 3.316 0.022 0.982 RaceWhite -0.524 0.592 0.562 0.197 1.782 -0.932 0.351 Stage2 0.217 1.243 0.187 0.862 1.791 1.163 0.245 Stage3 0.590 1.804 0.215 1.184 2.749 2.748 0.006 ** Stage4 0.733 2.081 0.794 0.439 9.859 0.923 0.356 Purity -0.295 0.744 0.370 0.360 1.538 -0.798 0.425 Rsquare = 0.052 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.93e-02 Wald test p = 1.49e-02 Score (logrank) test p = 1.28e-02 ELOVL2 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.044 0.957 0.118 0.760 1.205 -0.374 0.709 Age 0.020 1.020 0.016 0.989 1.052 1.259 0.208 Gendermale -0.202 0.817 0.334 0.424 1.574 -0.603 0.546 RaceBlack 0.188 1.206 1.537 0.059 24.549 0.122 0.903 RaceWhite -0.490 0.613 1.047 0.079 4.765 -0.468 0.640 Stage2 -0.249 0.780 0.469 0.311 1.953 -0.531 0.595 Stage3 -0.104 0.901 0.418 0.397 2.045 -0.250 0.803 Stage4 -0.152 0.859 0.476 0.338 2.184 -0.320 0.749 Purity -0.789 0.454 0.560 0.152 1.361 -1.410 0.159 Rsquare = 0.062 (max possible = 9.98e-01 ) Likelihood ratio test p = 7.98e-01 Wald test p = 7.8e-01 Score (logrank) test p = 7.74e-01 ELOVL2 in OV (n=303): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.027 1.027 0.104 0.838 1.260 0.260 0.795 Age 0.036 1.036 0.008 1.020 1.053 4.380 0.000 *** RaceBlack -0.058 0.944 0.577 0.305 2.924 -0.100 0.920 RaceWhite -0.162 0.851 0.516 0.310 2.337 -0.314 0.754 Purity -0.579 0.560 0.679 0.148 2.119 -0.854 0.393 Rsquare = 0.082 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.12e-03 Wald test p = 9.88e-04 Score (logrank) test p = 8.21e-04 ELOVL2 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.332 0.718 0.196 0.489 1.054 -1.693 0.091 · Age 0.020 1.021 0.011 0.999 1.043 1.886 0.059 · Gendermale -0.207 0.813 0.216 0.532 1.242 -0.958 0.338 RaceBlack 0.200 1.221 0.746 0.283 5.274 0.268 0.789 RaceWhite 0.468 1.596 0.477 0.627 4.066 0.980 0.327 Stage2 0.563 1.755 0.436 0.747 4.126 1.290 0.197 Stage3 -0.341 0.711 1.092 0.084 6.041 -0.313 0.755 Stage4 0.045 1.046 0.829 0.206 5.312 0.054 0.957 Purity -0.662 0.516 0.416 0.228 1.167 -1.590 0.112 Rsquare = 0.106 (max possible = 9.91e-01 ) Likelihood ratio test p = 3.04e-02 Wald test p = 6.1e-02 Score (logrank) test p = 5.42e-02 ELOVL2 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.781 2.183 0.430 0.939 5.073 1.814 0.070 · Age 0.033 1.033 0.028 0.977 1.092 1.152 0.249 Gendermale 1.337 3.809 0.919 0.629 23.055 1.456 0.145 RaceBlack -0.407 0.666 21095.106 0.000 Inf 0.000 1.000 RaceWhite 17.078 26111268.793 17647.158 0.000 Inf 0.001 0.999 Purity 5.135 169.932 3.670 0.128 225818.917 1.399 0.162 Rsquare = 0.075 (max possible = 3.07e-01 ) Likelihood ratio test p = 4.63e-02 Wald test p = 1.71e-01 Score (logrank) test p = 7.16e-02 ELOVL2 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.604 0.547 0.285 0.313 0.955 -2.121 0.034 * Age 0.010 1.010 0.059 0.899 1.135 0.172 0.863 RaceBlack 15.380 4782566.997 7318.474 0.000 Inf 0.002 0.998 RaceWhite 15.846 7619459.183 7318.474 0.000 Inf 0.002 0.998 Purity 1.146 3.145 1.416 0.196 50.487 0.809 0.418 Rsquare = 0.019 (max possible = 1.83e-01 ) Likelihood ratio test p = 1.77e-01 Wald test p = 2.67e-01 Score (logrank) test p = 1.94e-01 ELOVL2 in READ (n=166): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 3.045 21.002 1.878 0.529 833.929 1.621 0.105 Age 0.137 1.147 0.050 1.040 1.264 2.759 0.006 ** Gendermale -0.500 0.607 0.724 0.147 2.507 -0.691 0.490 RaceBlack 12.573 288714.486 10677.500 0.000 Inf 0.001 0.999 RaceWhite 11.490 97752.083 10677.500 0.000 Inf 0.001 0.999 Stage2 -2.461 0.085 1.396 0.006 1.317 -1.763 0.078 · Stage3 -0.891 0.410 0.968 0.062 2.733 -0.921 0.357 Stage4 -0.419 0.658 0.980 0.096 4.491 -0.428 0.669 Purity 0.788 2.199 1.461 0.126 38.523 0.539 0.590 Rsquare = 0.235 (max possible = 7.22e-01 ) Likelihood ratio test p = 1.58e-02 Wald test p = 1.93e-01 Score (logrank) test p = 3.37e-02 ELOVL2 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.121 1.129 0.076 0.973 1.309 1.601 0.109 Age 0.022 1.023 0.008 1.006 1.039 2.711 0.007 ** Gendermale 0.003 1.003 0.223 0.648 1.552 0.014 0.989 RaceBlack -0.112 0.894 1.089 0.106 7.563 -0.103 0.918 RaceWhite -0.369 0.692 1.025 0.093 5.161 -0.359 0.719 Purity 0.689 1.991 0.593 0.623 6.361 1.162 0.245 Rsquare = 0.053 (max possible = 9.75e-01 ) Likelihood ratio test p = 4.95e-02 Wald test p = 6.01e-02 Score (logrank) test p = 6.15e-02 ELOVL2 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.003 0.997 0.040 0.921 1.079 -0.083 0.934 Age 0.018 1.019 0.005 1.008 1.029 3.523 0.000 *** Gendermale -0.051 0.951 0.157 0.698 1.294 -0.321 0.748 RaceWhite -1.286 0.276 0.401 0.126 0.607 -3.203 0.001 ** Stage2 0.272 1.313 0.221 0.851 2.026 1.229 0.219 Stage3 0.610 1.840 0.205 1.232 2.747 2.980 0.003 ** Stage4 1.351 3.859 0.352 1.937 7.689 3.840 0.000 *** Purity 1.023 2.782 0.343 1.420 5.452 2.981 0.003 ** Rsquare = 0.123 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.23e-08 Wald test p = 1.21e-08 Score (logrank) test p = 1.42e-09 ELOVL2 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.155 1.167000e+00 0.099 0.961 1.418 1.558 0.119 Age 0.013 1.013000e+00 0.016 0.981 1.045 0.788 0.431 Gendermale 0.216 1.241000e+00 0.433 0.531 2.902 0.499 0.618 RaceWhite -1.427 2.400000e-01 0.644 0.068 0.847 -2.217 0.027 * Stage2 17.944 6.207787e+07 6220.183 0.000 Inf 0.003 0.998 Stage3 18.422 1.000836e+08 6220.183 0.000 Inf 0.003 0.998 Stage4 20.633 9.135783e+08 6220.183 0.000 Inf 0.003 0.997 Purity -0.589 5.550000e-01 1.085 0.066 4.656 -0.543 0.587 Rsquare = 0.168 (max possible = 8.69e-01 ) Likelihood ratio test p = 2.7e-02 Wald test p = 2.42e-02 Score (logrank) test p = 1.46e-03 ELOVL2 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.020 0.981 0.044 0.899 1.070 -0.440 0.660 Age 0.020 1.021 0.006 1.009 1.032 3.593 0.000 *** Gendermale -0.063 0.939 0.173 0.669 1.317 -0.367 0.714 RaceWhite -1.066 0.344 0.600 0.106 1.116 -1.777 0.076 · Stage2 0.134 1.143 0.234 0.722 1.809 0.570 0.568 Stage3 0.556 1.744 0.209 1.157 2.629 2.654 0.008 ** Stage4 1.135 3.110 0.400 1.421 6.808 2.839 0.005 ** Purity 1.162 3.198 0.373 1.539 6.643 3.116 0.002 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.01e-06 Wald test p = 1.74e-06 Score (logrank) test p = 6.62e-07 ELOVL2 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.307 1.359 0.113 1.089 1.696 2.710 0.007 ** Age 0.027 1.028 0.010 1.007 1.048 2.678 0.007 ** Gendermale 0.093 1.098 0.209 0.729 1.652 0.447 0.655 RaceBlack 0.301 1.351 0.448 0.562 3.250 0.672 0.502 RaceWhite 0.049 1.050 0.246 0.649 1.699 0.198 0.843 Stage2 0.639 1.894 0.399 0.866 4.144 1.599 0.110 Stage3 1.006 2.735 0.368 1.330 5.625 2.735 0.006 ** Stage4 1.512 4.536 0.515 1.652 12.456 2.934 0.003 ** Purity -0.492 0.611 0.381 0.290 1.289 -1.292 0.196 Rsquare = 0.089 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.46e-03 Wald test p = 1.55e-03 Score (logrank) test p = 1.14e-03 ELOVL2 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 3.386 29.540 16959.832 0 Inf 0.000 1.000 Age -1.562 0.210 1840.384 0 Inf -0.001 0.999 RaceBlack 15.322 4508639.953 35593140.270 0 Inf 0.000 1.000 RaceWhite -23.870 0.000 39977514.585 0 Inf 0.000 1.000 Stage2 0.995 2.704 35232.628 0 Inf 0.000 1.000 Stage3 12.394 241303.371 363337.723 0 Inf 0.000 1.000 Purity -1.520 0.219 219217.964 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 1.29e-03 ELOVL2 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.060 1.061 0.372 0.512 2.200 0.160 0.873 Age 0.145 1.157 0.029 1.092 1.224 4.998 0.000 *** Gendermale -0.070 0.932 0.633 0.269 3.224 -0.111 0.912 RaceBlack 17.433 37256344.824 7932.246 0.000 Inf 0.002 0.998 RaceWhite 17.225 30261857.184 7932.246 0.000 Inf 0.002 0.998 Stage2 -0.143 0.866 1.160 0.089 8.414 -0.124 0.902 Stage3 0.261 1.298 0.871 0.236 7.152 0.300 0.764 Stage4 1.712 5.542 0.994 0.790 38.869 1.723 0.085 · Purity 2.187 8.907 1.095 1.041 76.238 1.996 0.046 * Rsquare = 0.149 (max possible = 3.47e-01 ) Likelihood ratio test p = 2.51e-10 Wald test p = 3.19e-04 Score (logrank) test p = 5.26e-11 ELOVL2 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -4.260 0.014 2.105 0.000 0.874 -2.024 0.043 * Age 0.089 1.093 0.039 1.012 1.181 2.253 0.024 * Gendermale 0.285 1.330 0.818 0.268 6.609 0.349 0.727 RaceBlack -18.722 0.000 11872.628 0.000 Inf -0.002 0.999 RaceWhite -1.222 0.295 1.230 0.026 3.284 -0.993 0.320 Purity 0.933 2.543 1.166 0.259 24.986 0.801 0.423 Rsquare = 0.124 (max possible = 4.51e-01 ) Likelihood ratio test p = 2.04e-02 Wald test p = 1.52e-01 Score (logrank) test p = 5.5e-02 ELOVL2 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 0.525 1.691 0.132 1.304 2.191 3.967 0.000 *** Age 0.044 1.044 0.016 1.012 1.078 2.674 0.007 ** RaceBlack -0.556 0.573 0.799 0.120 2.747 -0.696 0.487 RaceWhite -0.562 0.570 0.747 0.132 2.465 -0.753 0.452 Purity 0.281 1.324 0.658 0.365 4.806 0.427 0.670 Rsquare = 0.077 (max possible = 7.81e-01 ) Likelihood ratio test p = 4.05e-04 Wald test p = 3.71e-05 Score (logrank) test p = 3.92e-06 ELOVL2 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.237 0.789 0.201 0.532 1.171 -1.177 0.239 Age 0.051 1.052 0.026 1.001 1.107 1.981 0.048 * RaceBlack 17.905 59721502.580 6509.231 0.000 Inf 0.003 0.998 RaceWhite 18.033 67839037.020 6509.231 0.000 Inf 0.003 0.998 Purity -0.182 0.833 1.177 0.083 8.363 -0.155 0.877 Rsquare = 0.142 (max possible = 9.83e-01 ) Likelihood ratio test p = 1.59e-01 Wald test p = 2.7e-01 Score (logrank) test p = 1.89e-01 ELOVL2 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ELOVL2` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL2 -0.007 0.993 0.307 0.544 1.813 -0.022 0.982 Age 0.040 1.041 0.019 1.003 1.082 2.096 0.036 * Gendermale 0.273 1.314 0.484 0.508 3.394 0.563 0.573 Stage3 0.282 1.326 0.502 0.495 3.550 0.561 0.575 Stage4 3.758 42.854 1.218 3.934 466.818 3.084 0.002 ** Purity 1.950 7.025 1.259 0.595 82.910 1.548 0.122 Rsquare = 0.253 (max possible = 8.72e-01 ) Likelihood ratio test p = 1.01e-03 Wald test p = 3.51e-03 Score (logrank) test p = 2.53e-09 ELOVL3 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.324 1.383 0.121 1.092 1.752 2.685 0.007 ** Age 0.014 1.014 0.013 0.988 1.041 1.029 0.303 Gendermale 0.648 1.912 0.436 0.814 4.493 1.487 0.137 RaceBlack 0.262 1.300 13421.335 0.000 Inf 0.000 1.000 RaceWhite 17.921 60642222.135 11455.495 0.000 Inf 0.002 0.999 Purity 1.265 3.545 2.421 0.031 407.873 0.523 0.601 Rsquare = 0.161 (max possible = 9.38e-01 ) Likelihood ratio test p = 8.14e-02 Wald test p = 1.46e-01 Score (logrank) test p = 6.73e-02 ELOVL3 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.011 0.989 0.102 0.810 1.208 -0.105 0.916 Age 0.033 1.034 0.009 1.017 1.052 3.888 0.000 *** Gendermale -0.169 0.845 0.180 0.594 1.202 -0.937 0.349 RaceBlack 0.713 2.041 0.447 0.850 4.899 1.597 0.110 RaceWhite 0.120 1.128 0.356 0.561 2.268 0.338 0.736 Stage2 14.513 2009158.833 1862.561 0.000 Inf 0.008 0.994 Stage3 14.947 3101212.157 1862.561 0.000 Inf 0.008 0.994 Stage4 15.488 5324137.413 1862.561 0.000 Inf 0.008 0.993 Purity 0.136 1.145 0.343 0.584 2.245 0.395 0.693 Rsquare = 0.13 (max possible = 9.91e-01 ) Likelihood ratio test p = 2.01e-07 Wald test p = 1.23e-06 Score (logrank) test p = 3.37e-07 ELOVL3 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.144 1.155 0.118 0.917 1.454 1.222 0.222 Age 0.037 1.037 0.008 1.022 1.053 4.839 0.000 *** Gendermale 0.076 1.079 1.008 0.150 7.774 0.075 0.940 RaceBlack -0.022 0.978 0.619 0.290 3.293 -0.036 0.971 RaceWhite -0.233 0.792 0.596 0.246 2.546 -0.391 0.695 Stage2 0.407 1.502 0.304 0.828 2.725 1.338 0.181 Stage3 1.193 3.296 0.313 1.785 6.087 3.812 0.000 *** Stage4 2.539 12.671 0.389 5.909 27.174 6.524 0.000 *** Purity 0.485 1.625 0.420 0.713 3.701 1.156 0.248 Rsquare = 0.082 (max possible = 7.85e-01 ) Likelihood ratio test p = 1.31e-12 Wald test p = 2.59e-16 Score (logrank) test p = 3.24e-22 ELOVL3 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.698 4.970000e-01 0.321 0.265 0.933 -2.177 0.029 * Age 0.008 1.008000e+00 0.018 0.974 1.044 0.476 0.634 RaceBlack -0.988 3.720000e-01 1.109 0.042 3.275 -0.890 0.373 RaceWhite -1.093 3.350000e-01 1.100 0.039 2.897 -0.993 0.321 Stage2 18.532 1.117469e+08 6412.032 0.000 Inf 0.003 0.998 Stage3 20.056 5.133499e+08 6412.032 0.000 Inf 0.003 0.998 Stage4 21.591 2.380387e+09 6412.032 0.000 Inf 0.003 0.997 Purity 1.149 3.155000e+00 1.007 0.438 22.714 1.141 0.254 Rsquare = 0.19 (max possible = 7.18e-01 ) Likelihood ratio test p = 3.63e-05 Wald test p = 1.35e-03 Score (logrank) test p = 4.31e-07 ELOVL3 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.699 4.970000e-01 0.935 0.080 3.104 -0.748 0.454 Age 0.041 1.042000e+00 0.031 0.980 1.107 1.314 0.189 RaceBlack -3.454 3.200000e-02 1.872 0.001 1.241 -1.845 0.065 · RaceWhite -2.319 9.800000e-02 1.682 0.004 2.658 -1.379 0.168 Stage2 18.077 7.093792e+07 15465.863 0.000 Inf 0.001 0.999 Stage3 19.778 3.885370e+08 15465.863 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 2.510 1.230100e+01 2.271 0.143 1054.850 1.105 0.269 Rsquare = 0.377 (max possible = 6.68e-01 ) Likelihood ratio test p = 2.32e-04 Wald test p = 2.74e-01 Score (logrank) test p = 9.7e-15 ELOVL3 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.230 1.259 0.223 0.813 1.949 1.031 0.303 Age 0.049 1.050 0.012 1.026 1.075 4.153 0.000 *** Gendermale -15.353 0.000 3469.981 0.000 Inf -0.004 0.996 RaceBlack -0.471 0.624 1.175 0.062 6.244 -0.401 0.688 RaceWhite 0.208 1.231 1.032 0.163 9.313 0.202 0.840 Stage2 0.317 1.373 0.375 0.658 2.865 0.845 0.398 Stage3 0.882 2.416 0.394 1.115 5.234 2.236 0.025 * Stage4 2.187 8.905 0.593 2.787 28.457 3.689 0.000 *** Purity 0.318 1.375 0.610 0.416 4.542 0.522 0.601 Rsquare = 0.072 (max possible = 6.81e-01 ) Likelihood ratio test p = 7.01e-05 Wald test p = 1.33e-05 Score (logrank) test p = 2.43e-07 ELOVL3 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.524 1.688 0.196 1.151 2.477 2.679 0.007 ** Age 0.052 1.053 0.020 1.012 1.096 2.543 0.011 * Gendermale 1.228 3.413 1.109 0.388 30.005 1.107 0.268 RaceBlack 16.421 13536577.245 7045.953 0.000 Inf 0.002 0.998 RaceWhite 16.011 8987237.803 7045.953 0.000 Inf 0.002 0.998 Stage2 0.785 2.193 1.081 0.263 18.266 0.726 0.468 Stage3 1.723 5.599 1.071 0.686 45.725 1.608 0.108 Stage4 2.312 10.098 1.188 0.984 103.670 1.946 0.052 · Purity 0.706 2.025 1.269 0.168 24.342 0.556 0.578 Rsquare = 0.142 (max possible = 6.98e-01 ) Likelihood ratio test p = 4.26e-03 Wald test p = 5.66e-03 Score (logrank) test p = 8.37e-04 ELOVL3 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.130 1.139 0.103 0.930 1.395 1.259 0.208 Age 0.013 1.013 0.010 0.994 1.033 1.330 0.184 RaceBlack 1.105 3.018 1.069 0.371 24.538 1.033 0.302 RaceWhite 0.876 2.402 1.017 0.327 17.616 0.862 0.389 Purity 0.495 1.640 0.745 0.381 7.055 0.664 0.507 Rsquare = 0.02 (max possible = 8.91e-01 ) Likelihood ratio test p = 4.59e-01 Wald test p = 4.78e-01 Score (logrank) test p = 4.71e-01 ELOVL3 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 2.730 15.329 1.680 0.569 412.768 1.625 0.104 Age 0.015 1.015 0.021 0.974 1.057 0.705 0.481 Gendermale 0.091 1.095 0.586 0.347 3.454 0.155 0.877 RaceBlack 1.277 3.585 1.775 0.111 116.166 0.719 0.472 RaceWhite 0.046 1.047 1.145 0.111 9.881 0.040 0.968 Stage2 1.298 3.663 0.775 0.801 16.745 1.674 0.094 · Stage3 -16.076 0.000 7370.206 0.000 Inf -0.002 0.998 Stage4 1.229 3.417 0.720 0.833 14.019 1.706 0.088 · Purity 0.623 1.864 1.664 0.072 48.600 0.374 0.708 Rsquare = 0.267 (max possible = 9.46e-01 ) Likelihood ratio test p = 2.63e-01 Wald test p = 3.64e-01 Score (logrank) test p = 1.79e-01 ELOVL3 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.443 1.557 0.299 0.866 2.800 1.480 0.139 Age 0.023 1.024 0.012 1.001 1.047 2.013 0.044 * Gendermale 0.217 1.242 0.269 0.733 2.105 0.807 0.420 RaceBlack -0.449 0.638 0.825 0.127 3.218 -0.544 0.587 RaceWhite -0.519 0.595 0.776 0.130 2.724 -0.669 0.504 Stage2 0.347 1.415 0.575 0.459 4.363 0.604 0.546 Stage3 0.940 2.559 0.564 0.848 7.727 1.667 0.096 · Stage4 2.043 7.710 0.572 2.512 23.666 3.570 0.000 *** Purity -0.132 0.876 0.601 0.270 2.844 -0.220 0.826 Rsquare = 0.116 (max possible = 9.04e-01 ) Likelihood ratio test p = 2.16e-04 Wald test p = 8.29e-05 Score (logrank) test p = 1.16e-05 ELOVL3 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 4.315 74.800 2.000 1.484 3770.671 2.157 0.031 * Age 0.088 1.092 0.072 0.949 1.257 1.232 0.218 Gendermale 1.729 5.632 1.779 0.172 183.982 0.972 0.331 RaceBlack 2.859 17.452 2.857 0.065 4720.210 1.001 0.317 RaceWhite -7.086 0.001 5.039 0.000 16.280 -1.406 0.160 Purity -1.285 0.277 3.593 0.000 316.162 -0.358 0.721 Rsquare = 0.332 (max possible = 5.58e-01 ) Likelihood ratio test p = 1.1e-02 Wald test p = 4.21e-01 Score (logrank) test p = 1.82e-02 ELOVL3 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.265 0.767 0.218 0.500 1.177 -1.214 0.225 Age 0.009 1.009 0.014 0.982 1.037 0.637 0.524 Gendermale 0.420 1.522 0.540 0.528 4.390 0.778 0.437 RaceBlack 0.593 1.810 1.087 0.215 15.247 0.546 0.585 RaceWhite -0.039 0.962 0.449 0.399 2.321 -0.087 0.931 Stage2 0.745 2.106 0.655 0.584 7.599 1.138 0.255 Stage3 1.622 5.061 0.684 1.324 19.349 2.370 0.018 * Stage4 2.923 18.591 0.777 4.055 85.243 3.762 0.000 *** Purity 0.083 1.087 0.769 0.241 4.907 0.108 0.914 Rsquare = 0.151 (max possible = 9.32e-01 ) Likelihood ratio test p = 6.51e-03 Wald test p = 3.39e-03 Score (logrank) test p = 2.48e-04 ELOVL3 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 1.707 5.512 0.493 2.096 14.496 3.460 0.001 ** Age 0.031 1.032 0.008 1.016 1.049 3.836 0.000 *** Gendermale 0.109 1.115 0.226 0.716 1.736 0.482 0.630 RaceBlack 0.763 2.144 0.726 0.517 8.902 1.050 0.294 RaceWhite 0.011 1.011 0.615 0.303 3.375 0.018 0.985 Purity -0.645 0.525 0.559 0.175 1.568 -1.155 0.248 Rsquare = 0.192 (max possible = 9.98e-01 ) Likelihood ratio test p = 6.88e-05 Wald test p = 8.25e-05 Score (logrank) test p = 7.1e-05 ELOVL3 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.027 0.973 0.107 0.790 1.200 -0.252 0.801 Age 0.022 1.022 0.008 1.007 1.038 2.901 0.004 ** Gendermale -0.254 0.775 0.173 0.552 1.089 -1.470 0.142 RaceBlack 0.130 1.139 0.559 0.381 3.406 0.233 0.816 RaceWhite -0.250 0.779 0.511 0.286 2.120 -0.490 0.624 Stage2 0.609 1.839 0.544 0.633 5.345 1.119 0.263 Stage3 0.847 2.334 0.537 0.815 6.682 1.579 0.114 Stage4 1.253 3.502 0.510 1.289 9.514 2.458 0.014 * Purity -0.048 0.954 0.363 0.468 1.943 -0.131 0.896 Rsquare = 0.069 (max possible = 9.89e-01 ) Likelihood ratio test p = 5.14e-04 Wald test p = 1.38e-03 Score (logrank) test p = 1.01e-03 ELOVL3 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.217 1.242000e+00 0.247 0.766 2.014 0.880 0.379 Age 0.005 1.005000e+00 0.026 0.955 1.058 0.207 0.836 Gendermale -0.083 9.200000e-01 0.541 0.319 2.656 -0.154 0.878 RaceBlack 18.814 1.481495e+08 12127.228 0.000 Inf 0.002 0.999 RaceWhite 17.980 6.434068e+07 12127.228 0.000 Inf 0.001 0.999 Stage2 17.407 3.628042e+07 5375.777 0.000 Inf 0.003 0.997 Stage3 16.466 1.415898e+07 5375.777 0.000 Inf 0.003 0.998 Stage4 17.394 3.580922e+07 5375.777 0.000 Inf 0.003 0.997 Purity -1.665 1.890000e-01 1.081 0.023 1.573 -1.541 0.123 Rsquare = 0.097 (max possible = 9.17e-01 ) Likelihood ratio test p = 6.76e-01 Wald test p = 9.22e-01 Score (logrank) test p = 8.09e-01 ELOVL3 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.042 0.959 0.122 0.755 1.218 -0.341 0.733 Age 0.027 1.027 0.008 1.010 1.044 3.173 0.002 ** Gendermale -0.292 0.747 0.184 0.521 1.070 -1.589 0.112 RaceBlack -0.027 0.973 0.565 0.322 2.943 -0.048 0.962 RaceWhite -0.404 0.668 0.513 0.244 1.824 -0.788 0.431 Stage2 0.355 1.426 0.555 0.481 4.229 0.640 0.522 Stage3 0.721 2.056 0.541 0.712 5.938 1.332 0.183 Stage4 1.144 3.139 0.512 1.151 8.562 2.234 0.025 * Purity 0.194 1.214 0.402 0.553 2.669 0.484 0.629 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.25e-04 Wald test p = 9.27e-04 Score (logrank) test p = 7e-04 ELOVL3 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z ELOVL3 4.304 7.399800e+01 2.567 4.840000e-01 1.132462e+04 1.677 Age 0.079 1.082000e+00 0.030 1.021000e+00 1.147000e+00 2.652 Gendermale -1.003 3.670000e-01 0.753 8.400000e-02 1.604000e+00 -1.332 RaceBlack -18.608 0.000000e+00 11309.229 0.000000e+00 Inf -0.002 RaceWhite -2.293 1.010000e-01 1.210 9.000000e-03 1.082000e+00 -1.895 Stage2 17.548 4.179976e+07 0.858 7.773258e+06 2.247732e+08 20.446 Stage3 19.066 1.907457e+08 0.788 4.069716e+07 8.940162e+08 24.191 Stage4 20.664 9.425045e+08 0.960 1.434530e+08 6.192375e+09 21.514 Purity 2.766 1.589000e+01 4.259 4.000000e-03 6.702791e+04 0.649 p signif ELOVL3 0.094 · Age 0.008 ** Gendermale 0.183 RaceBlack 0.999 RaceWhite 0.058 · Stage2 0.000 *** Stage3 0.000 *** Stage4 0.000 *** Purity 0.516 Rsquare = 0.377 (max possible = 6.71e-01 ) Likelihood ratio test p = 4.77e-04 Wald test p = 1.7e-313 Score (logrank) test p = 1.19e-09 ELOVL3 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.741 2.098 0.283 1.206 3.652 2.621 0.009 ** Age 0.033 1.034 0.008 1.017 1.051 3.962 0.000 *** Gendermale -0.117 0.890 0.185 0.619 1.278 -0.632 0.527 RaceBlack 0.127 1.135 1.058 0.143 9.025 0.120 0.905 RaceWhite 0.231 1.260 1.015 0.172 9.204 0.227 0.820 Stage2 0.280 1.323 0.346 0.672 2.608 0.809 0.418 Stage3 0.800 2.226 0.230 1.418 3.495 3.478 0.001 ** Stage4 1.757 5.794 0.216 3.792 8.854 8.123 0.000 *** Purity 0.065 1.067 0.366 0.521 2.185 0.176 0.860 Rsquare = 0.184 (max possible = 9.65e-01 ) Likelihood ratio test p = 7.6e-16 Wald test p = 6.04e-16 Score (logrank) test p = 2.15e-19 ELOVL3 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.388 1.473 0.288 0.839 2.589 1.348 0.178 Age 0.009 1.009 0.016 0.979 1.041 0.594 0.552 Gendermale -0.531 0.588 0.388 0.275 1.258 -1.369 0.171 RaceBlack -2.020 0.133 1.197 0.013 1.384 -1.688 0.091 · RaceWhite -2.105 0.122 1.177 0.012 1.223 -1.789 0.074 · Stage2 -0.357 0.700 1.056 0.088 5.548 -0.338 0.736 Stage3 1.622 5.064 0.426 2.198 11.668 3.809 0.000 *** Stage4 2.753 15.696 0.509 5.784 42.595 5.406 0.000 *** Purity -0.210 0.810 0.762 0.182 3.606 -0.276 0.783 Rsquare = 0.168 (max possible = 7.58e-01 ) Likelihood ratio test p = 6.43e-06 Wald test p = 2.11e-06 Score (logrank) test p = 3.2e-10 ELOVL3 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.022 1.022 0.125 0.801 1.305 0.178 0.859 Age 0.038 1.039 0.008 1.022 1.055 4.686 0.000 *** Gendermale -0.134 0.874 0.212 0.577 1.324 -0.634 0.526 RaceBlack -0.334 0.716 1.108 0.082 6.286 -0.301 0.763 RaceWhite -0.699 0.497 1.019 0.067 3.661 -0.686 0.492 Rsquare = 0.156 (max possible = 9.96e-01 ) Likelihood ratio test p = 1.25e-04 Wald test p = 3.86e-04 Score (logrank) test p = 2.8e-04 ELOVL3 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.774 2.168 0.552 0.735 6.394 1.403 0.161 Age 0.061 1.063 0.008 1.047 1.079 7.979 0.000 *** Gendermale 0.104 1.110 0.195 0.757 1.627 0.532 0.595 RaceBlack 15.370 4733883.826 2022.301 0.000 Inf 0.008 0.994 RaceWhite 15.359 4680600.418 2022.301 0.000 Inf 0.008 0.994 Purity -0.742 0.476 0.436 0.203 1.118 -1.704 0.088 · Rsquare = 0.14 (max possible = 9.07e-01 ) Likelihood ratio test p = 4.81e-13 Wald test p = 4.03e-13 Score (logrank) test p = 3.83e-14 ELOVL3 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.407 1.502 0.147 1.125 2.005 2.760 0.006 ** Age 0.012 1.012 0.008 0.996 1.028 1.423 0.155 Gendermale -0.062 0.940 0.228 0.602 1.469 -0.271 0.786 RaceBlack 0.901 2.463 0.489 0.945 6.419 1.844 0.065 · RaceWhite -0.027 0.973 0.238 0.611 1.550 -0.114 0.909 Stage2 0.131 1.140 0.276 0.664 1.957 0.475 0.635 Stage3 0.893 2.444 0.236 1.539 3.879 3.789 0.000 *** Stage4 1.569 4.803 0.620 1.426 16.177 2.533 0.011 * Purity 0.401 1.493 0.453 0.615 3.628 0.885 0.376 Rsquare = 0.103 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.03e-04 Wald test p = 2.57e-05 Score (logrank) test p = 5.23e-06 ELOVL3 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.136 1.145 0.084 0.972 1.349 1.624 0.104 Age 0.008 1.008 0.009 0.990 1.026 0.902 0.367 Gendermale 0.038 1.039 0.169 0.746 1.446 0.224 0.822 RaceBlack 16.234 11233181.160 1844.028 0.000 Inf 0.009 0.993 RaceWhite 16.374 12917470.893 1844.028 0.000 Inf 0.009 0.993 Stage2 0.864 2.373 0.201 1.600 3.520 4.296 0.000 *** Stage3 1.000 2.718 0.218 1.773 4.167 4.587 0.000 *** Stage4 1.002 2.725 0.333 1.418 5.235 3.009 0.003 ** Purity 0.620 1.859 0.343 0.949 3.643 1.807 0.071 · Rsquare = 0.102 (max possible = 9.74e-01 ) Likelihood ratio test p = 8.67e-07 Wald test p = 1.06e-05 Score (logrank) test p = 1.32e-06 ELOVL3 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.127 0.881 0.097 0.729 1.065 -1.309 0.190 Age 0.017 1.017 0.009 0.998 1.036 1.780 0.075 · Gendermale 0.447 1.564 0.193 1.071 2.284 2.314 0.021 * RaceBlack 0.005 1.005 0.603 0.308 3.276 0.008 0.993 RaceWhite -0.512 0.599 0.560 0.200 1.797 -0.914 0.361 Stage2 0.242 1.274 0.188 0.881 1.842 1.286 0.199 Stage3 0.652 1.919 0.217 1.255 2.934 3.008 0.003 ** Stage4 0.809 2.245 0.791 0.476 10.586 1.022 0.307 Purity -0.350 0.705 0.366 0.344 1.444 -0.956 0.339 Rsquare = 0.055 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.29e-02 Wald test p = 1.02e-02 Score (logrank) test p = 8.64e-03 ELOVL3 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.138 0.871 0.175 0.619 1.227 -0.789 0.430 Age 0.021 1.021 0.016 0.990 1.054 1.338 0.181 Gendermale -0.141 0.869 0.332 0.453 1.664 -0.425 0.671 RaceBlack 0.164 1.178 1.532 0.058 23.738 0.107 0.915 RaceWhite -0.486 0.615 1.046 0.079 4.777 -0.465 0.642 Stage2 -0.240 0.786 0.469 0.313 1.972 -0.512 0.608 Stage3 -0.128 0.880 0.422 0.385 2.011 -0.303 0.762 Stage4 -0.201 0.818 0.482 0.318 2.103 -0.418 0.676 Purity -0.754 0.471 0.554 0.159 1.394 -1.360 0.174 Rsquare = 0.067 (max possible = 9.98e-01 ) Likelihood ratio test p = 7.47e-01 Wald test p = 7.3e-01 Score (logrank) test p = 7.2e-01 ELOVL3 in OV (n=303): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.016 1.016 0.070 0.886 1.166 0.228 0.819 Age 0.036 1.037 0.008 1.020 1.054 4.441 0.000 *** RaceBlack -0.066 0.936 0.579 0.301 2.914 -0.114 0.909 RaceWhite -0.167 0.846 0.517 0.307 2.332 -0.322 0.747 Purity -0.550 0.577 0.668 0.156 2.138 -0.823 0.411 Rsquare = 0.081 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.13e-03 Wald test p = 9.89e-04 Score (logrank) test p = 8.25e-04 ELOVL3 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.167 1.181 0.396 0.544 2.566 0.421 0.674 Age 0.022 1.022 0.011 1.000 1.044 2.000 0.045 * Gendermale -0.200 0.818 0.220 0.532 1.259 -0.913 0.361 RaceBlack -0.030 0.971 0.737 0.229 4.120 -0.040 0.968 RaceWhite 0.364 1.440 0.474 0.569 3.643 0.769 0.442 Stage2 0.625 1.869 0.437 0.794 4.398 1.433 0.152 Stage3 -0.234 0.791 1.091 0.093 6.715 -0.215 0.830 Stage4 0.239 1.269 0.824 0.253 6.381 0.290 0.772 Purity -0.652 0.521 0.411 0.233 1.166 -1.586 0.113 Rsquare = 0.089 (max possible = 9.91e-01 ) Likelihood ratio test p = 7.91e-02 Wald test p = 1.14e-01 Score (logrank) test p = 1.09e-01 ELOVL3 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.825 4.38000e-01 2.429 0.004 51.198 -0.340 0.734 Age 0.036 1.03700e+00 0.028 0.981 1.096 1.289 0.197 Gendermale 1.373 3.94700e+00 0.894 0.684 22.773 1.536 0.125 RaceBlack -0.317 7.28000e-01 19770.958 0.000 Inf 0.000 1.000 RaceWhite 17.238 3.06438e+07 15802.059 0.000 Inf 0.001 0.999 Purity 5.634 2.79879e+02 3.491 0.299 262207.794 1.614 0.107 Rsquare = 0.055 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.54e-01 Wald test p = 4.27e-01 Score (logrank) test p = 3.12e-01 ELOVL3 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ELOVL3 4.911 1.357620e+02 2.546 9.250000e-01 1.993554e+04 1.929 0.054 Age 0.024 1.024000e+00 0.061 9.090000e-01 1.153000e+00 0.393 0.694 RaceBlack 19.702 3.600347e+08 1.108 4.100890e+07 3.160899e+09 17.775 0.000 RaceWhite 20.640 9.205251e+08 1.108 1.048503e+08 8.081683e+09 18.622 0.000 Purity 0.323 1.381000e+00 1.431 8.400000e-02 2.283900e+01 0.226 0.822 signif ELOVL3 · Age RaceBlack *** RaceWhite *** Purity Rsquare = 0.04 (max possible = 1.83e-01 ) Likelihood ratio test p = 5.23e-03 Wald test p = 7.95e-142 Score (logrank) test p = 8.24e-12 ELOVL3 in READ (n=166): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.241 1.273 1.694 0.046 35.242 0.142 0.887 Age 0.110 1.116 0.044 1.024 1.217 2.504 0.012 * Gendermale -0.335 0.715 0.701 0.181 2.825 -0.478 0.632 RaceBlack 13.437 684543.051 10133.308 0.000 Inf 0.001 0.999 RaceWhite 12.380 237968.093 10133.308 0.000 Inf 0.001 0.999 Stage2 -1.895 0.150 1.300 0.012 1.923 -1.457 0.145 Stage3 -0.503 0.605 0.920 0.100 3.670 -0.547 0.585 Stage4 -0.160 0.852 0.957 0.131 5.565 -0.167 0.868 Purity 0.184 1.202 1.387 0.079 18.229 0.133 0.894 Rsquare = 0.209 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.68e-02 Wald test p = 2.34e-01 Score (logrank) test p = 4.84e-02 ELOVL3 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.068 0.934 0.122 0.736 1.186 -0.560 0.576 Age 0.023 1.023 0.008 1.007 1.040 2.743 0.006 ** Gendermale -0.001 0.999 0.223 0.645 1.545 -0.006 0.995 RaceBlack -0.159 0.853 1.088 0.101 7.196 -0.146 0.884 RaceWhite -0.495 0.610 1.024 0.082 4.533 -0.483 0.629 Purity 0.879 2.408 0.584 0.766 7.563 1.504 0.132 Rsquare = 0.044 (max possible = 9.75e-01 ) Likelihood ratio test p = 1.07e-01 Wald test p = 1.43e-01 Score (logrank) test p = 1.42e-01 ELOVL3 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.001 0.999 0.100 0.822 1.215 -0.007 0.995 Age 0.018 1.019 0.005 1.008 1.029 3.541 0.000 *** Gendermale -0.050 0.951 0.158 0.698 1.295 -0.319 0.750 RaceWhite -1.286 0.276 0.402 0.126 0.607 -3.202 0.001 ** Stage2 0.275 1.317 0.219 0.858 2.021 1.259 0.208 Stage3 0.611 1.842 0.204 1.235 2.748 2.994 0.003 ** Stage4 1.350 3.858 0.352 1.936 7.689 3.838 0.000 *** Purity 1.019 2.770 0.343 1.413 5.430 2.968 0.003 ** Rsquare = 0.123 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.23e-08 Wald test p = 1.19e-08 Score (logrank) test p = 1.43e-09 ELOVL3 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.217 8.050000e-01 0.326 0.425 1.525 -0.665 0.506 Age 0.011 1.011000e+00 0.016 0.980 1.043 0.707 0.479 Gendermale 0.146 1.157000e+00 0.446 0.482 2.773 0.326 0.744 RaceWhite -1.251 2.860000e-01 0.618 0.085 0.961 -2.024 0.043 * Stage2 17.641 4.584754e+07 6181.319 0.000 Inf 0.003 0.998 Stage3 18.108 7.313695e+07 6181.319 0.000 Inf 0.003 0.998 Stage4 20.174 5.774259e+08 6181.319 0.000 Inf 0.003 0.997 Purity 0.083 1.087000e+00 0.976 0.160 7.364 0.085 0.932 Rsquare = 0.151 (max possible = 8.69e-01 ) Likelihood ratio test p = 5.19e-02 Wald test p = 5.28e-02 Score (logrank) test p = 4.17e-03 ELOVL3 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.018 0.983 0.112 0.789 1.223 -0.157 0.876 Age 0.021 1.021 0.006 1.010 1.032 3.660 0.000 *** Gendermale -0.060 0.942 0.172 0.672 1.321 -0.346 0.730 RaceWhite -1.053 0.349 0.600 0.108 1.131 -1.754 0.079 · Stage2 0.153 1.166 0.230 0.742 1.831 0.665 0.506 Stage3 0.563 1.756 0.209 1.166 2.644 2.694 0.007 ** Stage4 1.132 3.103 0.400 1.418 6.792 2.833 0.005 ** Purity 1.137 3.118 0.372 1.503 6.468 3.054 0.002 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.09e-06 Wald test p = 1.69e-06 Score (logrank) test p = 6.53e-07 ELOVL3 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.010 0.990 0.156 0.730 1.343 -0.066 0.947 Age 0.026 1.027 0.010 1.006 1.047 2.586 0.010 * Gendermale 0.120 1.127 0.210 0.747 1.701 0.571 0.568 RaceBlack 0.268 1.308 0.447 0.544 3.143 0.599 0.549 RaceWhite 0.094 1.099 0.244 0.681 1.773 0.387 0.699 Stage2 0.487 1.628 0.390 0.758 3.494 1.250 0.211 Stage3 0.919 2.508 0.364 1.230 5.114 2.529 0.011 * Stage4 1.321 3.747 0.504 1.395 10.061 2.621 0.009 ** Purity -0.554 0.574 0.382 0.272 1.214 -1.452 0.146 Rsquare = 0.069 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.37e-02 Wald test p = 1.87e-02 Score (logrank) test p = 1.53e-02 ELOVL3 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.959 0.383 11381.053 0 Inf 0.000 1.000 Age -1.680 0.186 1845.611 0 Inf -0.001 0.999 RaceBlack 9.271 10625.557 19509809.697 0 Inf 0.000 1.000 RaceWhite -33.284 0.000 19893790.405 0 Inf 0.000 1.000 Stage2 -3.035 0.048 43284.376 0 Inf 0.000 1.000 Stage3 12.414 246321.235 105968.741 0 Inf 0.000 1.000 Purity 14.630 2258258.144 213558.325 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 2.25e-03 ELOVL3 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 4.253 70.331 1.606 3.023 1636.428 2.649 0.008 ** Age 0.146 1.157 0.028 1.094 1.223 5.150 0.000 *** Gendermale 0.289 1.335 0.618 0.397 4.483 0.467 0.640 RaceBlack 17.116 27120335.337 7586.864 0.000 Inf 0.002 0.998 RaceWhite 17.067 25835745.692 7586.864 0.000 Inf 0.002 0.998 Stage2 -0.029 0.971 1.079 0.117 8.043 -0.027 0.978 Stage3 -0.140 0.869 0.855 0.163 4.645 -0.164 0.870 Stage4 1.718 5.573 0.963 0.844 36.805 1.784 0.074 · Purity 1.897 6.669 1.094 0.781 56.935 1.734 0.083 · Rsquare = 0.161 (max possible = 3.47e-01 ) Likelihood ratio test p = 1.88e-11 Wald test p = 6.73e-05 Score (logrank) test p = 1.23e-12 ELOVL3 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 1.048 2.852 2.316 0.030 267.172 0.452 0.651 Age 0.045 1.046 0.032 0.983 1.114 1.415 0.157 Gendermale -0.235 0.791 0.746 0.183 3.412 -0.315 0.753 RaceBlack -16.138 0.000 10138.445 0.000 Inf -0.002 0.999 RaceWhite 0.880 2.411 1.429 0.147 39.674 0.616 0.538 Purity 0.414 1.513 1.097 0.176 13.002 0.378 0.706 Rsquare = 0.046 (max possible = 4.51e-01 ) Likelihood ratio test p = 5.08e-01 Wald test p = 6.55e-01 Score (logrank) test p = 5.67e-01 ELOVL3 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 0.173 1.189 0.141 0.902 1.568 1.228 0.220 Age 0.047 1.048 0.016 1.015 1.082 2.878 0.004 ** RaceBlack -0.536 0.585 0.803 0.121 2.821 -0.668 0.504 RaceWhite -0.614 0.541 0.751 0.124 2.359 -0.817 0.414 Purity 0.391 1.479 0.653 0.411 5.322 0.599 0.549 Rsquare = 0.043 (max possible = 7.81e-01 ) Likelihood ratio test p = 2.9e-02 Wald test p = 3.44e-02 Score (logrank) test p = 2.94e-02 ELOVL3 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -0.021 0.979 0.200 0.661 1.450 -0.105 0.917 Age 0.044 1.045 0.024 0.997 1.095 1.817 0.069 · RaceBlack 17.605 44230509.303 6473.210 0.000 Inf 0.003 0.998 RaceWhite 17.854 56741366.993 6473.210 0.000 Inf 0.003 0.998 Purity -0.829 0.436 1.127 0.048 3.974 -0.736 0.462 Rsquare = 0.119 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.53e-01 Wald test p = 3.58e-01 Score (logrank) test p = 2.64e-01 ELOVL3 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ELOVL3` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL3 -1.945 0.143 1.956 0.003 6.608 -0.994 0.320 Age 0.043 1.044 0.020 1.005 1.086 2.202 0.028 * Gendermale 0.282 1.326 0.488 0.509 3.452 0.577 0.564 Stage3 0.297 1.345 0.499 0.506 3.577 0.594 0.552 Stage4 3.696 40.271 1.219 3.696 438.762 3.033 0.002 ** Purity 1.703 5.490 1.245 0.478 63.047 1.367 0.172 Rsquare = 0.266 (max possible = 8.72e-01 ) Likelihood ratio test p = 5.73e-04 Wald test p = 2.18e-03 Score (logrank) test p = 1.71e-09 ELOVL4 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.196 1.216 0.160 0.889 1.664 1.224 0.221 Age 0.005 1.005 0.014 0.979 1.033 0.385 0.700 Gendermale 0.374 1.453 0.417 0.642 3.290 0.897 0.370 RaceBlack 0.285 1.330 12187.467 0.000 Inf 0.000 1.000 RaceWhite 16.959 23179573.996 10386.873 0.000 Inf 0.002 0.999 Purity 2.540 12.680 2.349 0.127 1267.631 1.081 0.280 Rsquare = 0.088 (max possible = 9.38e-01 ) Likelihood ratio test p = 4.37e-01 Wald test p = 7.17e-01 Score (logrank) test p = 5.48e-01 ELOVL4 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.162 1.176 0.074 1.018 1.358 2.203 0.028 * Age 0.034 1.034 0.009 1.017 1.052 3.911 0.000 *** Gendermale -0.204 0.815 0.179 0.574 1.158 -1.141 0.254 RaceBlack 0.554 1.740 0.453 0.716 4.229 1.223 0.221 RaceWhite 0.027 1.028 0.358 0.510 2.071 0.076 0.939 Stage2 14.370 1741380.484 1885.652 0.000 Inf 0.008 0.994 Stage3 14.819 2728654.839 1885.652 0.000 Inf 0.008 0.994 Stage4 15.343 4607230.085 1885.652 0.000 Inf 0.008 0.994 Purity 0.156 1.169 0.342 0.599 2.284 0.457 0.647 Rsquare = 0.142 (max possible = 9.91e-01 ) Likelihood ratio test p = 2.77e-08 Wald test p = 1.75e-07 Score (logrank) test p = 4.35e-08 ELOVL4 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.119 1.126 0.106 0.914 1.388 1.118 0.264 Age 0.037 1.037 0.008 1.022 1.053 4.829 0.000 *** Gendermale 0.090 1.094 1.008 0.152 7.894 0.089 0.929 RaceBlack -0.038 0.963 0.620 0.285 3.248 -0.061 0.951 RaceWhite -0.249 0.779 0.596 0.242 2.508 -0.418 0.676 Stage2 0.392 1.480 0.304 0.816 2.687 1.290 0.197 Stage3 1.166 3.210 0.313 1.736 5.933 3.720 0.000 *** Stage4 2.547 12.775 0.389 5.956 27.399 6.543 0.000 *** Purity 0.488 1.629 0.419 0.716 3.703 1.164 0.245 Rsquare = 0.082 (max possible = 7.85e-01 ) Likelihood ratio test p = 1.45e-12 Wald test p = 4.37e-16 Score (logrank) test p = 4.9e-22 ELOVL4 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.274 7.600000e-01 0.186 0.528 1.095 -1.472 0.141 Age 0.008 1.008000e+00 0.017 0.975 1.043 0.465 0.642 RaceBlack -1.029 3.570000e-01 1.132 0.039 3.287 -0.909 0.363 RaceWhite -1.385 2.500000e-01 1.145 0.027 2.362 -1.210 0.226 Stage2 18.674 1.288098e+08 6473.290 0.000 Inf 0.003 0.998 Stage3 20.128 5.512988e+08 6473.290 0.000 Inf 0.003 0.998 Stage4 21.807 2.956304e+09 6473.290 0.000 Inf 0.003 0.997 Purity 1.146 3.144000e+00 0.995 0.447 22.095 1.152 0.249 Rsquare = 0.169 (max possible = 7.18e-01 ) Likelihood ratio test p = 2.03e-04 Wald test p = 2.78e-03 Score (logrank) test p = 1.07e-06 ELOVL4 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.423 6.550000e-01 0.769 0.145 2.956 -0.551 0.582 Age 0.029 1.030000e+00 0.028 0.975 1.088 1.057 0.291 RaceBlack -2.847 5.800000e-02 1.817 0.002 2.044 -1.567 0.117 RaceWhite -1.498 2.240000e-01 1.479 0.012 4.058 -1.013 0.311 Stage2 18.108 7.311665e+07 15700.383 0.000 Inf 0.001 0.999 Stage3 20.007 4.885034e+08 15700.383 0.000 Inf 0.001 0.999 Stage4 52.330 5.328077e+22 1895768.933 0.000 Inf 0.000 1.000 Purity 3.157 2.350000e+01 2.380 0.221 2496.550 1.326 0.185 Rsquare = 0.374 (max possible = 6.68e-01 ) Likelihood ratio test p = 5.56e-04 Wald test p = 1e+00 Score (logrank) test p = 3.34e-14 ELOVL4 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.387 1.473 0.241 0.918 2.362 1.606 0.108 Age 0.048 1.049 0.012 1.025 1.074 4.063 0.000 *** Gendermale -15.287 0.000 3452.379 0.000 Inf -0.004 0.996 RaceBlack -0.489 0.614 1.178 0.061 6.170 -0.415 0.678 RaceWhite 0.148 1.160 1.035 0.152 8.824 0.143 0.886 Stage2 0.247 1.281 0.378 0.610 2.689 0.654 0.513 Stage3 0.770 2.160 0.398 0.990 4.710 1.935 0.053 · Stage4 2.121 8.338 0.591 2.617 26.565 3.587 0.000 *** Purity 0.383 1.467 0.611 0.443 4.861 0.627 0.530 Rsquare = 0.075 (max possible = 6.81e-01 ) Likelihood ratio test p = 3.96e-05 Wald test p = 7.3e-06 Score (logrank) test p = 1.34e-07 ELOVL4 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.443 1.557 0.251 0.953 2.546 1.766 0.077 · Age 0.061 1.062 0.022 1.017 1.110 2.718 0.007 ** Gendermale 1.078 2.939 1.110 0.334 25.883 0.971 0.331 RaceBlack 16.763 19050688.551 6608.827 0.000 Inf 0.003 0.998 RaceWhite 15.804 7303899.991 6608.827 0.000 Inf 0.002 0.998 Stage2 0.731 2.077 1.073 0.254 16.996 0.681 0.496 Stage3 1.666 5.290 1.068 0.652 42.923 1.560 0.119 Stage4 2.423 11.280 1.208 1.056 120.459 2.005 0.045 * Purity 0.776 2.173 1.325 0.162 29.163 0.586 0.558 Rsquare = 0.121 (max possible = 6.98e-01 ) Likelihood ratio test p = 1.68e-02 Wald test p = 4.05e-02 Score (logrank) test p = 1.09e-02 ELOVL4 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.138 1.148 0.111 0.923 1.427 1.238 0.216 Age 0.009 1.009 0.010 0.989 1.029 0.889 0.374 RaceBlack 1.068 2.908 1.068 0.359 23.570 1.000 0.317 RaceWhite 0.821 2.272 1.015 0.311 16.603 0.809 0.419 Purity 0.532 1.703 0.727 0.409 7.085 0.732 0.464 Rsquare = 0.02 (max possible = 8.91e-01 ) Likelihood ratio test p = 4.65e-01 Wald test p = 4.89e-01 Score (logrank) test p = 4.8e-01 ELOVL4 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -2.051 0.129 1.584 0.006 2.869 -1.295 0.195 Age 0.020 1.020 0.024 0.972 1.070 0.815 0.415 Gendermale 0.237 1.267 0.548 0.433 3.707 0.433 0.665 RaceBlack -0.990 0.371 1.674 0.014 9.887 -0.591 0.554 RaceWhite -1.670 0.188 1.103 0.022 1.634 -1.515 0.130 Stage2 0.523 1.687 0.702 0.426 6.685 0.745 0.457 Stage3 -15.228 0.000 7132.837 0.000 Inf -0.002 0.998 Stage4 1.078 2.939 0.710 0.730 11.829 1.518 0.129 Purity 2.044 7.724 1.810 0.222 268.178 1.130 0.259 Rsquare = 0.253 (max possible = 9.46e-01 ) Likelihood ratio test p = 3.13e-01 Wald test p = 5.89e-01 Score (logrank) test p = 3.56e-01 ELOVL4 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.235 1.265 0.445 0.529 3.029 0.528 0.597 Age 0.025 1.025 0.012 1.002 1.048 2.124 0.034 * Gendermale 0.226 1.254 0.269 0.739 2.127 0.840 0.401 RaceBlack -0.482 0.618 0.833 0.121 3.159 -0.579 0.563 RaceWhite -0.503 0.605 0.780 0.131 2.791 -0.644 0.519 Stage2 0.200 1.221 0.562 0.406 3.677 0.355 0.722 Stage3 0.792 2.209 0.550 0.751 6.495 1.440 0.150 Stage4 1.875 6.521 0.553 2.205 19.283 3.390 0.001 ** Purity -0.070 0.932 0.667 0.252 3.442 -0.105 0.916 Rsquare = 0.11 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.18e-04 Wald test p = 1.47e-04 Score (logrank) test p = 2.17e-05 ELOVL4 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.976 2.654 0.944 0.418 16.872 1.034 0.301 Age -0.006 0.994 0.044 0.911 1.084 -0.134 0.894 Gendermale 0.446 1.562 1.117 0.175 13.954 0.399 0.690 RaceBlack 0.619 1.857 1.704 0.066 52.350 0.363 0.716 RaceWhite -2.456 0.086 1.416 0.005 1.376 -1.735 0.083 · Purity -2.065 0.127 2.231 0.002 10.052 -0.926 0.355 Rsquare = 0.151 (max possible = 5.58e-01 ) Likelihood ratio test p = 3.47e-01 Wald test p = 5.04e-01 Score (logrank) test p = 2.6e-01 ELOVL4 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.267 1.306 0.147 0.980 1.740 1.820 0.069 · Age 0.016 1.016 0.014 0.988 1.045 1.117 0.264 Gendermale 0.648 1.912 0.547 0.654 5.585 1.184 0.236 RaceBlack 0.597 1.818 1.079 0.219 15.078 0.553 0.580 RaceWhite 0.123 1.131 0.458 0.461 2.778 0.269 0.788 Stage2 0.525 1.690 0.661 0.463 6.174 0.794 0.427 Stage3 1.254 3.506 0.680 0.925 13.281 1.846 0.065 · Stage4 2.720 15.183 0.769 3.362 68.577 3.536 0.000 *** Purity 0.236 1.267 0.781 0.274 5.855 0.303 0.762 Rsquare = 0.161 (max possible = 9.32e-01 ) Likelihood ratio test p = 3.47e-03 Wald test p = 1.7e-03 Score (logrank) test p = 1.27e-04 ELOVL4 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.212 1.236 0.144 0.933 1.638 1.474 0.140 Age 0.031 1.031 0.008 1.015 1.048 3.800 0.000 *** Gendermale -0.104 0.902 0.213 0.593 1.370 -0.485 0.628 RaceBlack 0.449 1.567 0.728 0.376 6.531 0.617 0.537 RaceWhite -0.267 0.766 0.615 0.229 2.556 -0.434 0.664 Purity -1.111 0.329 0.532 0.116 0.933 -2.090 0.037 * Rsquare = 0.143 (max possible = 9.98e-01 ) Likelihood ratio test p = 1.92e-03 Wald test p = 2.41e-03 Score (logrank) test p = 2.01e-03 ELOVL4 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.015 1.015 0.061 0.901 1.143 0.241 0.810 Age 0.022 1.022 0.008 1.007 1.038 2.901 0.004 ** Gendermale -0.249 0.779 0.172 0.557 1.091 -1.451 0.147 RaceBlack 0.120 1.127 0.562 0.375 3.390 0.213 0.831 RaceWhite -0.259 0.772 0.513 0.282 2.110 -0.505 0.614 Stage2 0.614 1.847 0.544 0.636 5.362 1.129 0.259 Stage3 0.844 2.326 0.537 0.812 6.666 1.571 0.116 Stage4 1.250 3.490 0.510 1.284 9.487 2.450 0.014 * Purity -0.033 0.968 0.368 0.471 1.991 -0.089 0.929 Rsquare = 0.069 (max possible = 9.89e-01 ) Likelihood ratio test p = 5.15e-04 Wald test p = 1.33e-03 Score (logrank) test p = 9.55e-04 ELOVL4 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.105 1.111000e+00 0.266 0.660 1.870 0.397 0.692 Age 0.011 1.011000e+00 0.025 0.962 1.062 0.417 0.677 Gendermale -0.173 8.420000e-01 0.536 0.294 2.405 -0.322 0.747 RaceBlack 18.875 1.575154e+08 12059.421 0.000 Inf 0.002 0.999 RaceWhite 18.002 6.580357e+07 12059.421 0.000 Inf 0.001 0.999 Stage2 17.471 3.869953e+07 5324.498 0.000 Inf 0.003 0.997 Stage3 16.682 1.757102e+07 5324.498 0.000 Inf 0.003 0.998 Stage4 17.570 4.271898e+07 5324.498 0.000 Inf 0.003 0.997 Purity -1.603 2.010000e-01 1.075 0.024 1.654 -1.492 0.136 Rsquare = 0.089 (max possible = 9.17e-01 ) Likelihood ratio test p = 7.32e-01 Wald test p = 9.44e-01 Score (logrank) test p = 8.5e-01 ELOVL4 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.006 1.006 0.063 0.889 1.139 0.096 0.923 Age 0.027 1.027 0.008 1.010 1.044 3.189 0.001 ** Gendermale -0.285 0.752 0.183 0.526 1.076 -1.559 0.119 RaceBlack -0.024 0.977 0.568 0.321 2.972 -0.042 0.967 RaceWhite -0.401 0.670 0.515 0.244 1.837 -0.779 0.436 Stage2 0.365 1.440 0.554 0.486 4.265 0.659 0.510 Stage3 0.723 2.060 0.542 0.712 5.965 1.333 0.183 Stage4 1.144 3.140 0.513 1.149 8.580 2.231 0.026 * Purity 0.215 1.240 0.404 0.562 2.738 0.533 0.594 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.39e-04 Wald test p = 9.37e-04 Score (logrank) test p = 6.99e-04 ELOVL4 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ELOVL4 0.401 1.494000e+00 0.348 0.755 2.956000e+00 1.152 0.249 Age 0.080 1.084000e+00 0.030 1.022 1.149000e+00 2.686 0.007 Gendermale -0.865 4.210000e-01 0.727 0.101 1.749000e+00 -1.190 0.234 RaceBlack -17.776 0.000000e+00 6069.168 0.000 Inf -0.003 0.998 RaceWhite -2.221 1.080000e-01 1.156 0.011 1.045000e+00 -1.922 0.055 Stage2 16.214 1.101134e+07 0.844 2107752.268 5.752551e+07 19.222 0.000 Stage3 16.809 1.996183e+07 0.781 4316879.107 9.230622e+07 21.515 0.000 Stage4 19.052 1.880381e+08 0.893 32697109.541 1.081390e+09 21.346 0.000 Purity 0.286 1.331000e+00 3.674 0.001 1.784749e+03 0.078 0.938 signif ELOVL4 Age ** Gendermale RaceBlack RaceWhite · Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.356 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.06e-03 Wald test p = 1.34e-274 Score (logrank) test p = 7.75e-09 ELOVL4 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.151 1.163 0.172 0.830 1.630 0.875 0.382 Age 0.035 1.036 0.008 1.019 1.053 4.204 0.000 *** Gendermale -0.079 0.924 0.183 0.645 1.324 -0.431 0.666 RaceBlack 0.208 1.231 1.056 0.156 9.749 0.197 0.844 RaceWhite 0.169 1.184 1.014 0.162 8.636 0.166 0.868 Stage2 0.186 1.205 0.347 0.610 2.378 0.537 0.591 Stage3 0.823 2.278 0.230 1.451 3.577 3.578 0.000 *** Stage4 1.769 5.867 0.216 3.841 8.962 8.187 0.000 *** Purity 0.028 1.029 0.368 0.500 2.115 0.077 0.939 Rsquare = 0.175 (max possible = 9.65e-01 ) Likelihood ratio test p = 7.47e-15 Wald test p = 8.46e-15 Score (logrank) test p = 4.47e-18 ELOVL4 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.295 1.344 0.218 0.877 2.059 1.356 0.175 Age 0.012 1.012 0.016 0.980 1.044 0.729 0.466 Gendermale -0.457 0.633 0.386 0.297 1.350 -1.183 0.237 RaceBlack -1.893 0.151 1.202 0.014 1.589 -1.575 0.115 RaceWhite -1.821 0.162 1.197 0.015 1.692 -1.521 0.128 Stage2 -0.369 0.691 1.056 0.087 5.480 -0.350 0.727 Stage3 1.440 4.221 0.452 1.739 10.247 3.183 0.001 ** Stage4 2.720 15.183 0.503 5.661 40.716 5.405 0.000 *** Purity -0.327 0.721 0.744 0.168 3.102 -0.439 0.661 Rsquare = 0.17 (max possible = 7.58e-01 ) Likelihood ratio test p = 5.58e-06 Wald test p = 1.68e-06 Score (logrank) test p = 2.59e-10 ELOVL4 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.018 1.018 0.570 0.333 3.112 0.031 0.975 Age 0.038 1.039 0.008 1.022 1.055 4.677 0.000 *** Gendermale -0.134 0.875 0.213 0.577 1.327 -0.629 0.529 RaceBlack -0.343 0.709 1.114 0.080 6.295 -0.308 0.758 RaceWhite -0.704 0.494 1.026 0.066 3.694 -0.686 0.492 Rsquare = 0.156 (max possible = 9.96e-01 ) Likelihood ratio test p = 1.27e-04 Wald test p = 4.02e-04 Score (logrank) test p = 2.88e-04 ELOVL4 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.181 0.834 0.125 0.653 1.066 -1.450 0.147 Age 0.062 1.064 0.008 1.048 1.081 8.079 0.000 *** Gendermale 0.040 1.041 0.197 0.707 1.533 0.205 0.837 RaceBlack 15.252 4204515.189 1992.732 0.000 Inf 0.008 0.994 RaceWhite 15.358 4676055.088 1992.732 0.000 Inf 0.008 0.994 Purity -0.936 0.392 0.407 0.177 0.871 -2.300 0.021 * Rsquare = 0.14 (max possible = 9.07e-01 ) Likelihood ratio test p = 4.2e-13 Wald test p = 4.96e-13 Score (logrank) test p = 3.54e-14 ELOVL4 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.484 1.623 0.175 1.152 2.286 2.770 0.006 ** Age 0.012 1.012 0.008 0.996 1.028 1.421 0.155 Gendermale -0.091 0.913 0.227 0.585 1.425 -0.401 0.688 RaceBlack 0.985 2.677 0.491 1.023 7.009 2.006 0.045 * RaceWhite 0.040 1.041 0.240 0.651 1.666 0.168 0.866 Stage2 0.294 1.342 0.262 0.803 2.242 1.123 0.262 Stage3 0.926 2.525 0.235 1.593 4.005 3.938 0.000 *** Stage4 1.608 4.994 0.619 1.484 16.798 2.598 0.009 ** Purity 0.727 2.068 0.461 0.838 5.105 1.576 0.115 Rsquare = 0.102 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.23e-04 Wald test p = 4.06e-05 Score (logrank) test p = 1.17e-05 ELOVL4 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.060 1.062 0.089 0.892 1.264 0.679 0.497 Age 0.007 1.007 0.009 0.990 1.025 0.820 0.412 Gendermale 0.018 1.018 0.169 0.731 1.418 0.107 0.915 RaceBlack 16.049 9335136.521 1889.786 0.000 Inf 0.008 0.993 RaceWhite 16.242 11323438.748 1889.786 0.000 Inf 0.009 0.993 Stage2 0.870 2.388 0.201 1.610 3.542 4.327 0.000 *** Stage3 1.012 2.752 0.218 1.796 4.218 4.647 0.000 *** Stage4 1.007 2.736 0.334 1.422 5.265 3.014 0.003 ** Purity 0.597 1.817 0.343 0.927 3.560 1.739 0.082 · Rsquare = 0.098 (max possible = 9.74e-01 ) Likelihood ratio test p = 1.99e-06 Wald test p = 2.65e-05 Score (logrank) test p = 2.99e-06 ELOVL4 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.055 0.947 0.076 0.816 1.099 -0.718 0.473 Age 0.017 1.017 0.009 0.999 1.036 1.804 0.071 · Gendermale 0.443 1.558 0.193 1.066 2.275 2.292 0.022 * RaceBlack 0.050 1.051 0.605 0.321 3.444 0.083 0.934 RaceWhite -0.497 0.608 0.560 0.203 1.825 -0.887 0.375 Stage2 0.234 1.264 0.189 0.872 1.832 1.236 0.216 Stage3 0.604 1.829 0.214 1.202 2.783 2.818 0.005 ** Stage4 0.774 2.169 0.789 0.462 10.184 0.981 0.327 Purity -0.337 0.714 0.365 0.349 1.460 -0.923 0.356 Rsquare = 0.052 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.03e-02 Wald test p = 1.58e-02 Score (logrank) test p = 1.37e-02 ELOVL4 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.506 1.659 0.225 1.067 2.579 2.247 0.025 * Age 0.029 1.030 0.016 0.997 1.063 1.789 0.074 · Gendermale -0.122 0.885 0.326 0.467 1.676 -0.375 0.708 RaceBlack 1.245 3.471 1.609 0.148 81.227 0.774 0.439 RaceWhite 0.159 1.172 1.083 0.140 9.781 0.147 0.883 Stage2 -0.128 0.880 0.470 0.350 2.212 -0.272 0.785 Stage3 -0.181 0.834 0.422 0.365 1.907 -0.430 0.667 Stage4 -0.173 0.842 0.479 0.329 2.151 -0.360 0.719 Purity -0.800 0.449 0.550 0.153 1.321 -1.454 0.146 Rsquare = 0.112 (max possible = 9.98e-01 ) Likelihood ratio test p = 3.44e-01 Wald test p = 3.48e-01 Score (logrank) test p = 3.31e-01 ELOVL4 in OV (n=303): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.010 0.990 0.109 0.799 1.226 -0.094 0.925 Age 0.036 1.037 0.008 1.020 1.053 4.440 0.000 *** RaceBlack -0.054 0.948 0.577 0.306 2.934 -0.093 0.926 RaceWhite -0.156 0.855 0.515 0.312 2.348 -0.303 0.762 Purity -0.532 0.588 0.689 0.152 2.266 -0.772 0.440 Rsquare = 0.081 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.15e-03 Wald test p = 9.97e-04 Score (logrank) test p = 8.28e-04 ELOVL4 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.368 0.692 0.211 0.458 1.047 -1.743 0.081 · Age 0.017 1.017 0.011 0.995 1.040 1.499 0.134 Gendermale -0.254 0.776 0.218 0.506 1.188 -1.168 0.243 RaceBlack 0.084 1.087 0.740 0.255 4.642 0.113 0.910 RaceWhite 0.399 1.491 0.473 0.590 3.765 0.845 0.398 Stage2 0.382 1.466 0.447 0.610 3.522 0.855 0.393 Stage3 -0.400 0.670 1.089 0.079 5.667 -0.367 0.713 Stage4 0.022 1.022 0.829 0.201 5.191 0.027 0.979 Purity -0.782 0.457 0.419 0.201 1.039 -1.868 0.062 · Rsquare = 0.106 (max possible = 9.91e-01 ) Likelihood ratio test p = 2.93e-02 Wald test p = 7e-02 Score (logrank) test p = 5.95e-02 ELOVL4 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 1.542 4.676 0.849 0.885 24.707 1.816 0.069 · Age 0.044 1.044 0.028 0.988 1.104 1.535 0.125 Gendermale 1.269 3.557 0.879 0.636 19.909 1.444 0.149 RaceBlack -0.791 0.454 19198.468 0.000 Inf 0.000 1.000 RaceWhite 17.056 25534087.969 15025.635 0.000 Inf 0.001 0.999 Purity 3.069 21.512 4.005 0.008 55203.329 0.766 0.444 Rsquare = 0.076 (max possible = 3.07e-01 ) Likelihood ratio test p = 4.23e-02 Wald test p = 1.81e-01 Score (logrank) test p = 1.34e-01 ELOVL4 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.034 1.035 0.360 0.511 2.096 0.095 0.925 Age 0.009 1.009 0.057 0.903 1.128 0.161 0.872 RaceBlack 14.987 3226418.774 6739.861 0.000 Inf 0.002 0.998 RaceWhite 16.274 11682621.375 6739.860 0.000 Inf 0.002 0.998 Purity 1.096 2.991 1.395 0.194 46.013 0.786 0.432 Rsquare = 0.007 (max possible = 1.83e-01 ) Likelihood ratio test p = 7.43e-01 Wald test p = 8.66e-01 Score (logrank) test p = 8.14e-01 ELOVL4 in READ (n=166): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.724 2.062 0.654 0.572 7.435 1.106 0.269 Age 0.118 1.125 0.048 1.024 1.235 2.460 0.014 * Gendermale -0.286 0.751 0.742 0.176 3.214 -0.385 0.700 RaceBlack 13.507 734745.186 10239.292 0.000 Inf 0.001 0.999 RaceWhite 12.334 227385.235 10239.292 0.000 Inf 0.001 0.999 Stage2 -1.975 0.139 1.270 0.012 1.671 -1.555 0.120 Stage3 -0.584 0.557 0.938 0.089 3.504 -0.623 0.533 Stage4 -0.363 0.696 0.988 0.100 4.825 -0.367 0.714 Purity 0.519 1.680 1.492 0.090 31.270 0.348 0.728 Rsquare = 0.22 (max possible = 7.22e-01 ) Likelihood ratio test p = 2.6e-02 Wald test p = 2.37e-01 Score (logrank) test p = 4.17e-02 ELOVL4 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.233 1.263 0.106 1.026 1.554 2.200 0.028 * Age 0.022 1.023 0.008 1.006 1.039 2.699 0.007 ** Gendermale 0.077 1.080 0.227 0.693 1.685 0.341 0.733 RaceBlack -0.053 0.948 1.086 0.113 7.966 -0.049 0.961 RaceWhite -0.359 0.698 1.023 0.094 5.183 -0.351 0.725 Purity 0.931 2.536 0.565 0.838 7.676 1.647 0.099 · Rsquare = 0.062 (max possible = 9.75e-01 ) Likelihood ratio test p = 2.01e-02 Wald test p = 2.52e-02 Score (logrank) test p = 2.38e-02 ELOVL4 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.005 0.995 0.074 0.861 1.152 -0.061 0.951 Age 0.018 1.019 0.005 1.008 1.029 3.531 0.000 *** Gendermale -0.050 0.952 0.158 0.699 1.296 -0.314 0.753 RaceWhite -1.285 0.277 0.401 0.126 0.608 -3.201 0.001 ** Stage2 0.277 1.319 0.220 0.857 2.029 1.258 0.208 Stage3 0.612 1.844 0.205 1.234 2.756 2.986 0.003 ** Stage4 1.352 3.864 0.352 1.937 7.710 3.835 0.000 *** Purity 1.017 2.765 0.342 1.416 5.402 2.978 0.003 ** Rsquare = 0.123 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.23e-08 Wald test p = 1.18e-08 Score (logrank) test p = 1.4e-09 ELOVL4 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.391 1.479000e+00 0.179 1.042 2.099 2.193 0.028 * Age 0.016 1.016000e+00 0.016 0.984 1.049 0.956 0.339 Gendermale 0.425 1.529000e+00 0.449 0.635 3.684 0.947 0.344 RaceWhite -1.161 3.130000e-01 0.639 0.090 1.094 -1.819 0.069 · Stage2 17.773 5.232808e+07 6302.598 0.000 Inf 0.003 0.998 Stage3 18.438 1.017431e+08 6302.598 0.000 Inf 0.003 0.998 Stage4 20.623 9.050274e+08 6302.598 0.000 Inf 0.003 0.997 Purity 1.082 2.950000e+00 1.020 0.399 21.786 1.060 0.289 Rsquare = 0.186 (max possible = 8.69e-01 ) Likelihood ratio test p = 1.3e-02 Wald test p = 1.17e-02 Score (logrank) test p = 6.4e-04 ELOVL4 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.089 0.915 0.086 0.773 1.081 -1.044 0.296 Age 0.020 1.020 0.006 1.009 1.032 3.561 0.000 *** Gendermale -0.042 0.959 0.173 0.683 1.346 -0.243 0.808 RaceWhite -1.026 0.358 0.601 0.110 1.163 -1.708 0.088 · Stage2 0.182 1.200 0.232 0.762 1.891 0.786 0.432 Stage3 0.590 1.804 0.211 1.194 2.725 2.800 0.005 ** Stage4 1.165 3.206 0.400 1.463 7.023 2.912 0.004 ** Purity 1.121 3.067 0.369 1.488 6.322 3.037 0.002 ** Rsquare = 0.137 (max possible = 9.95e-01 ) Likelihood ratio test p = 6.77e-07 Wald test p = 9.08e-07 Score (logrank) test p = 3.49e-07 ELOVL4 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.453 1.573 0.148 1.178 2.102 3.068 0.002 ** Age 0.032 1.033 0.011 1.012 1.054 3.054 0.002 ** Gendermale 0.171 1.187 0.209 0.789 1.787 0.822 0.411 RaceBlack 0.432 1.541 0.453 0.634 3.742 0.954 0.340 RaceWhite 0.149 1.160 0.245 0.718 1.876 0.607 0.544 Stage2 0.619 1.858 0.393 0.859 4.016 1.574 0.115 Stage3 1.031 2.804 0.365 1.372 5.730 2.828 0.005 ** Stage4 1.492 4.445 0.504 1.654 11.948 2.957 0.003 ** Purity -0.424 0.654 0.379 0.311 1.376 -1.119 0.263 Rsquare = 0.095 (max possible = 9.79e-01 ) Likelihood ratio test p = 6.49e-04 Wald test p = 9.61e-04 Score (logrank) test p = 7.1e-04 ELOVL4 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -4.437 1.200000e-02 32476.401 0 Inf 0.000 1.000 Age -1.553 2.120000e-01 1825.043 0 Inf -0.001 0.999 RaceBlack -7.242 1.000000e-03 15599278.110 0 Inf 0.000 1.000 RaceWhite -49.135 0.000000e+00 18135753.192 0 Inf 0.000 1.000 Stage2 2.112 8.264000e+00 37208.376 0 Inf 0.000 1.000 Stage3 19.442 2.778076e+08 143781.221 0 Inf 0.000 1.000 Purity 23.437 1.508788e+10 202874.089 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 2.9e-03 ELOVL4 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.527 1.694 0.605 0.518 5.543 0.872 0.383 Age 0.154 1.167 0.030 1.099 1.239 5.056 0.000 *** Gendermale 0.025 1.025 0.634 0.296 3.554 0.039 0.969 RaceBlack 17.497 39699956.038 9453.269 0.000 Inf 0.002 0.999 RaceWhite 17.433 37230989.188 9453.269 0.000 Inf 0.002 0.999 Stage2 -0.272 0.762 1.076 0.093 6.271 -0.253 0.800 Stage3 0.136 1.145 0.853 0.215 6.100 0.159 0.874 Stage4 1.468 4.339 1.004 0.606 31.045 1.462 0.144 Purity 2.226 9.261 1.110 1.051 81.564 2.005 0.045 * Rsquare = 0.151 (max possible = 3.47e-01 ) Likelihood ratio test p = 1.82e-10 Wald test p = 5.75e-04 Score (logrank) test p = 1.18e-10 ELOVL4 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.552 0.576 0.209 0.382 0.867 -2.640 0.008 ** Age 0.013 1.013 0.035 0.946 1.086 0.378 0.706 Gendermale 0.098 1.103 0.794 0.233 5.235 0.124 0.901 RaceBlack -13.581 0.000 8564.477 0.000 Inf -0.002 0.999 RaceWhite 1.672 5.323 1.331 0.392 72.263 1.256 0.209 Purity -0.015 0.985 1.248 0.085 11.368 -0.012 0.990 Rsquare = 0.114 (max possible = 4.51e-01 ) Likelihood ratio test p = 3.39e-02 Wald test p = 1.41e-01 Score (logrank) test p = 2.45e-02 ELOVL4 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 0.539 1.715 0.162 1.248 2.357 3.322 0.001 ** Age 0.046 1.047 0.016 1.015 1.080 2.910 0.004 ** RaceBlack -0.861 0.423 0.820 0.085 2.107 -1.051 0.293 RaceWhite -0.681 0.506 0.753 0.116 2.214 -0.905 0.366 Purity 0.462 1.587 0.664 0.432 5.837 0.695 0.487 Rsquare = 0.069 (max possible = 7.81e-01 ) Likelihood ratio test p = 1.18e-03 Wald test p = 4.58e-04 Score (logrank) test p = 2.14e-04 ELOVL4 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.032 0.968 0.184 0.675 1.389 -0.175 0.861 Age 0.044 1.045 0.024 0.996 1.095 1.811 0.070 · RaceBlack 17.594 43732273.909 6475.206 0.000 Inf 0.003 0.998 RaceWhite 17.839 55897466.260 6475.206 0.000 Inf 0.003 0.998 Purity -0.814 0.443 1.104 0.051 3.860 -0.737 0.461 Rsquare = 0.119 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.51e-01 Wald test p = 3.58e-01 Score (logrank) test p = 2.65e-01 ELOVL4 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ELOVL4` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL4 -0.263 0.769 0.328 0.404 1.463 -0.800 0.423 Age 0.043 1.044 0.020 1.005 1.086 2.198 0.028 * Gendermale 0.324 1.382 0.486 0.534 3.579 0.666 0.505 Stage3 0.321 1.378 0.497 0.520 3.654 0.645 0.519 Stage4 3.779 43.785 1.220 4.009 478.186 3.098 0.002 ** Purity 1.597 4.937 1.242 0.433 56.282 1.286 0.198 Rsquare = 0.262 (max possible = 8.72e-01 ) Likelihood ratio test p = 6.81e-04 Wald test p = 2.33e-03 Score (logrank) test p = 1.38e-09 ELOVL5 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.070 1.072 0.202 0.721 1.593 0.344 0.731 Age 0.005 1.005 0.014 0.978 1.033 0.346 0.729 Gendermale 0.390 1.476 0.422 0.646 3.375 0.924 0.356 RaceBlack 0.047 1.048 11975.018 0.000 Inf 0.000 1.000 RaceWhite 16.910 22065118.976 10197.173 0.000 Inf 0.002 0.999 Purity 2.870 17.645 2.376 0.168 1858.719 1.208 0.227 Rsquare = 0.068 (max possible = 9.38e-01 ) Likelihood ratio test p = 6.08e-01 Wald test p = 8.96e-01 Score (logrank) test p = 7.52e-01 ELOVL5 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.083 1.087 0.086 0.919 1.286 0.970 0.332 Age 0.034 1.034 0.009 1.017 1.052 3.921 0.000 *** Gendermale -0.149 0.861 0.180 0.606 1.225 -0.831 0.406 RaceBlack 0.697 2.007 0.447 0.836 4.820 1.559 0.119 RaceWhite 0.077 1.080 0.357 0.537 2.174 0.217 0.829 Stage2 14.589 2168342.716 1856.209 0.000 Inf 0.008 0.994 Stage3 15.030 3367911.004 1856.209 0.000 Inf 0.008 0.994 Stage4 15.540 5612382.337 1856.209 0.000 Inf 0.008 0.993 Purity 0.158 1.171 0.340 0.602 2.279 0.465 0.642 Rsquare = 0.133 (max possible = 9.91e-01 ) Likelihood ratio test p = 1.35e-07 Wald test p = 8.36e-07 Score (logrank) test p = 2.53e-07 ELOVL5 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.031 0.970 0.074 0.839 1.121 -0.416 0.677 Age 0.036 1.037 0.008 1.021 1.052 4.759 0.000 *** Gendermale 0.075 1.078 1.010 0.149 7.807 0.074 0.941 RaceBlack -0.008 0.992 0.619 0.295 3.339 -0.013 0.990 RaceWhite -0.214 0.807 0.596 0.251 2.596 -0.359 0.719 Stage2 0.400 1.492 0.304 0.822 2.708 1.314 0.189 Stage3 1.176 3.241 0.314 1.751 5.998 3.744 0.000 *** Stage4 2.498 12.154 0.391 5.651 26.140 6.392 0.000 *** Purity 0.521 1.683 0.421 0.738 3.841 1.237 0.216 Rsquare = 0.081 (max possible = 7.85e-01 ) Likelihood ratio test p = 2.29e-12 Wald test p = 6.52e-16 Score (logrank) test p = 7.57e-22 ELOVL5 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.258 7.730000e-01 0.234 0.489 1.222 -1.103 0.270 Age 0.017 1.017000e+00 0.018 0.981 1.053 0.915 0.360 RaceBlack -0.981 3.750000e-01 1.116 0.042 3.338 -0.880 0.379 RaceWhite -1.220 2.950000e-01 1.124 0.033 2.672 -1.085 0.278 Stage2 18.684 1.300781e+08 6508.586 0.000 Inf 0.003 0.998 Stage3 20.078 5.245342e+08 6508.586 0.000 Inf 0.003 0.998 Stage4 21.423 2.013234e+09 6508.586 0.000 Inf 0.003 0.997 Purity 0.668 1.951000e+00 0.972 0.290 13.115 0.688 0.492 Rsquare = 0.163 (max possible = 7.18e-01 ) Likelihood ratio test p = 3.23e-04 Wald test p = 5.82e-03 Score (logrank) test p = 3.09e-06 ELOVL5 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.073 1.076000e+00 0.483 0.417 2.773 0.151 0.880 Age 0.034 1.034000e+00 0.030 0.975 1.097 1.119 0.263 RaceBlack -3.087 4.600000e-02 1.800 0.001 1.553 -1.715 0.086 · RaceWhite -1.715 1.800000e-01 1.447 0.011 3.068 -1.185 0.236 Stage2 18.088 7.166828e+07 14948.925 0.000 Inf 0.001 0.999 Stage3 19.687 3.546760e+08 14948.925 0.000 Inf 0.001 0.999 Stage4 52.459 6.060235e+22 1926647.761 0.000 Inf 0.000 1.000 Purity 3.089 2.194900e+01 2.279 0.252 1909.588 1.356 0.175 Rsquare = 0.37 (max possible = 6.68e-01 ) Likelihood ratio test p = 6.32e-04 Wald test p = 1e+00 Score (logrank) test p = 4.23e-14 ELOVL5 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.004 0.996 0.129 0.773 1.283 -0.031 0.975 Age 0.049 1.050 0.012 1.026 1.074 4.086 0.000 *** Gendermale -15.353 0.000 3451.770 0.000 Inf -0.004 0.996 RaceBlack -0.431 0.650 1.180 0.064 6.564 -0.365 0.715 RaceWhite 0.250 1.284 1.040 0.167 9.853 0.241 0.810 Stage2 0.326 1.385 0.375 0.665 2.887 0.870 0.384 Stage3 0.860 2.363 0.402 1.074 5.200 2.136 0.033 * Stage4 2.153 8.614 0.595 2.682 27.665 3.617 0.000 *** Purity 0.311 1.364 0.625 0.401 4.640 0.497 0.619 Rsquare = 0.07 (max possible = 6.81e-01 ) Likelihood ratio test p = 1.04e-04 Wald test p = 2.02e-05 Score (logrank) test p = 4.07e-07 ELOVL5 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.460 1.584 0.257 0.958 2.621 1.792 0.073 · Age 0.054 1.055 0.022 1.011 1.101 2.438 0.015 * Gendermale 0.545 1.725 1.184 0.169 17.565 0.460 0.645 RaceBlack 16.625 16600221.562 6250.270 0.000 Inf 0.003 0.998 RaceWhite 15.968 8603770.114 6250.270 0.000 Inf 0.003 0.998 Stage2 0.918 2.505 1.080 0.302 20.799 0.850 0.395 Stage3 1.996 7.360 1.083 0.881 61.491 1.843 0.065 · Stage4 2.784 16.177 1.238 1.430 183.029 2.249 0.025 * Purity 0.634 1.885 1.349 0.134 26.528 0.470 0.638 Rsquare = 0.124 (max possible = 6.98e-01 ) Likelihood ratio test p = 1.34e-02 Wald test p = 3.58e-02 Score (logrank) test p = 9.46e-03 ELOVL5 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.071 1.073 0.157 0.789 1.460 0.449 0.654 Age 0.011 1.011 0.010 0.992 1.031 1.108 0.268 RaceBlack 1.074 2.926 1.070 0.359 23.824 1.004 0.316 RaceWhite 0.821 2.274 1.015 0.311 16.619 0.809 0.418 Purity 0.604 1.830 0.738 0.431 7.767 0.819 0.413 Rsquare = 0.015 (max possible = 8.91e-01 ) Likelihood ratio test p = 6.49e-01 Wald test p = 6.83e-01 Score (logrank) test p = 6.75e-01 ELOVL5 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.467 1.596 0.407 0.719 3.544 1.148 0.251 Age 0.018 1.018 0.021 0.978 1.060 0.863 0.388 Gendermale 0.307 1.359 0.564 0.450 4.110 0.544 0.586 RaceBlack -0.597 0.550 1.478 0.030 9.975 -0.404 0.686 RaceWhite -0.855 0.425 0.893 0.074 2.449 -0.958 0.338 Stage2 0.592 1.808 0.657 0.499 6.548 0.901 0.367 Stage3 -15.135 0.000 7146.509 0.000 Inf -0.002 0.998 Stage4 0.917 2.502 0.689 0.648 9.663 1.330 0.183 Purity 2.837 17.060 1.695 0.616 472.506 1.674 0.094 · Rsquare = 0.241 (max possible = 9.46e-01 ) Likelihood ratio test p = 3.57e-01 Wald test p = 5.38e-01 Score (logrank) test p = 3.47e-01 ELOVL5 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.158 1.171 0.121 0.924 1.484 1.309 0.191 Age 0.027 1.027 0.012 1.004 1.052 2.280 0.023 * Gendermale 0.236 1.266 0.269 0.748 2.143 0.877 0.380 RaceBlack -0.479 0.619 0.818 0.125 3.078 -0.586 0.558 RaceWhite -0.515 0.598 0.769 0.132 2.698 -0.669 0.503 Stage2 0.155 1.167 0.563 0.387 3.522 0.274 0.784 Stage3 0.796 2.218 0.550 0.754 6.522 1.447 0.148 Stage4 1.765 5.841 0.560 1.948 17.512 3.150 0.002 ** Purity -0.136 0.873 0.610 0.264 2.886 -0.223 0.824 Rsquare = 0.115 (max possible = 9.04e-01 ) Likelihood ratio test p = 2.28e-04 Wald test p = 8e-05 Score (logrank) test p = 1.1e-05 ELOVL5 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 2.997 20.017 1.514 1.031 388.818 1.980 0.048 * Age -0.031 0.970 0.064 0.856 1.098 -0.487 0.626 Gendermale 1.834 6.258 1.140 0.670 58.484 1.608 0.108 RaceBlack 4.482 88.431 2.613 0.528 14807.154 1.716 0.086 · RaceWhite -3.129 0.044 1.586 0.002 0.980 -1.973 0.049 * Purity -2.931 0.053 2.453 0.000 6.526 -1.195 0.232 Rsquare = 0.241 (max possible = 5.58e-01 ) Likelihood ratio test p = 7.9e-02 Wald test p = 2.6e-01 Score (logrank) test p = 1.46e-01 ELOVL5 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.049 1.050 0.132 0.811 1.360 0.370 0.711 Age 0.012 1.012 0.015 0.982 1.042 0.770 0.442 Gendermale 0.527 1.694 0.552 0.574 4.999 0.955 0.339 RaceBlack 0.322 1.380 1.068 0.170 11.193 0.301 0.763 RaceWhite -0.043 0.958 0.456 0.392 2.340 -0.095 0.924 Stage2 0.641 1.899 0.670 0.511 7.059 0.957 0.338 Stage3 1.402 4.064 0.684 1.063 15.546 2.049 0.040 * Stage4 2.814 16.681 0.783 3.592 77.457 3.592 0.000 *** Purity 0.326 1.386 0.827 0.274 7.009 0.395 0.693 Rsquare = 0.142 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.1e-02 Wald test p = 5e-03 Score (logrank) test p = 4.21e-04 ELOVL5 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.107 1.113 0.205 0.745 1.663 0.525 0.600 Age 0.029 1.030 0.008 1.013 1.047 3.579 0.000 *** Gendermale -0.093 0.911 0.213 0.600 1.383 -0.438 0.661 RaceBlack 0.449 1.566 0.743 0.365 6.716 0.604 0.546 RaceWhite -0.281 0.755 0.619 0.224 2.542 -0.454 0.650 Purity -1.104 0.332 0.534 0.116 0.945 -2.067 0.039 * Rsquare = 0.131 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.3e-03 Wald test p = 5.79e-03 Score (logrank) test p = 5.11e-03 ELOVL5 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.069 1.072 0.091 0.896 1.282 0.759 0.448 Age 0.022 1.022 0.008 1.007 1.038 2.878 0.004 ** Gendermale -0.257 0.773 0.172 0.552 1.084 -1.493 0.135 RaceBlack 0.084 1.088 0.563 0.361 3.275 0.149 0.881 RaceWhite -0.268 0.765 0.512 0.281 2.085 -0.524 0.600 Stage2 0.613 1.846 0.544 0.636 5.358 1.128 0.259 Stage3 0.853 2.346 0.537 0.820 6.715 1.589 0.112 Stage4 1.239 3.452 0.510 1.270 9.383 2.428 0.015 * Purity -0.035 0.966 0.363 0.474 1.968 -0.096 0.923 Rsquare = 0.071 (max possible = 9.89e-01 ) Likelihood ratio test p = 4.2e-04 Wald test p = 1.07e-03 Score (logrank) test p = 7.67e-04 ELOVL5 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.303 1.353000e+00 0.405 0.611 2.996 0.746 0.455 Age 0.012 1.012000e+00 0.025 0.965 1.062 0.486 0.627 Gendermale -0.152 8.590000e-01 0.538 0.299 2.467 -0.282 0.778 RaceBlack 18.782 1.435667e+08 12127.968 0.000 Inf 0.002 0.999 RaceWhite 17.927 6.103679e+07 12127.968 0.000 Inf 0.001 0.999 Stage2 17.351 3.430387e+07 5344.842 0.000 Inf 0.003 0.997 Stage3 16.446 1.387448e+07 5344.842 0.000 Inf 0.003 0.998 Stage4 17.475 3.885431e+07 5344.842 0.000 Inf 0.003 0.997 Purity -1.372 2.540000e-01 1.098 0.029 2.182 -1.249 0.211 Rsquare = 0.095 (max possible = 9.17e-01 ) Likelihood ratio test p = 6.9e-01 Wald test p = 9.33e-01 Score (logrank) test p = 8.3e-01 ELOVL5 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.040 1.041 0.095 0.865 1.253 0.427 0.670 Age 0.027 1.027 0.008 1.010 1.044 3.154 0.002 ** Gendermale -0.290 0.748 0.183 0.523 1.071 -1.585 0.113 RaceBlack -0.047 0.954 0.568 0.313 2.906 -0.083 0.934 RaceWhite -0.407 0.665 0.513 0.243 1.819 -0.794 0.427 Stage2 0.368 1.445 0.554 0.488 4.276 0.664 0.507 Stage3 0.731 2.076 0.541 0.719 5.994 1.351 0.177 Stage4 1.138 3.120 0.512 1.143 8.516 2.221 0.026 * Purity 0.211 1.235 0.400 0.564 2.702 0.528 0.598 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.17e-04 Wald test p = 8.68e-04 Score (logrank) test p = 6.48e-04 ELOVL5 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ELOVL5 1.285 3.614 0.412 1.612 8.101000e+00 3.120 0.002 Age 0.079 1.082 0.030 1.019 1.148000e+00 2.592 0.010 Gendermale -0.615 0.540 0.731 0.129 2.264000e+00 -0.842 0.400 RaceBlack -11.180 0.000 2861.102 0.000 Inf -0.004 0.997 RaceWhite 1.415 4.117 1.157 0.426 3.978400e+01 1.223 0.221 Stage2 13.094 485816.959 0.850 91792.219 2.571221e+06 15.401 0.000 Stage3 14.750 2545479.140 0.779 552681.039 1.172370e+07 18.928 0.000 Stage4 16.997 24089800.720 0.893 4183254.703 1.387242e+08 19.029 0.000 Purity 5.444 231.408 4.126 0.071 7.528094e+05 1.319 0.187 signif ELOVL5 ** Age * Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.381 (max possible = 6.71e-01 ) Likelihood ratio test p = 4.09e-04 Wald test p = 9.65e-205 Score (logrank) test p = 5.8e-09 ELOVL5 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.000 1.000 0.156 0.737 1.357 0.000 1.000 Age 0.035 1.036 0.008 1.019 1.053 4.128 0.000 *** Gendermale -0.082 0.921 0.187 0.639 1.330 -0.437 0.662 RaceBlack 0.203 1.225 1.056 0.154 9.716 0.192 0.848 RaceWhite 0.153 1.165 1.017 0.159 8.557 0.150 0.881 Stage2 0.215 1.239 0.344 0.631 2.434 0.623 0.533 Stage3 0.811 2.250 0.231 1.432 3.538 3.515 0.000 *** Stage4 1.759 5.808 0.216 3.805 8.864 8.156 0.000 *** Purity -0.004 0.996 0.387 0.467 2.126 -0.009 0.992 Rsquare = 0.174 (max possible = 9.65e-01 ) Likelihood ratio test p = 1.04e-14 Wald test p = 1.07e-14 Score (logrank) test p = 5.57e-18 ELOVL5 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.523 1.688 0.203 1.134 2.511 2.580 0.010 * Age 0.015 1.015 0.016 0.984 1.048 0.965 0.335 Gendermale -0.580 0.560 0.387 0.262 1.196 -1.499 0.134 RaceBlack -1.622 0.198 1.220 0.018 2.158 -1.329 0.184 RaceWhite -1.345 0.261 1.230 0.023 2.903 -1.093 0.274 Stage2 -0.374 0.688 1.057 0.087 5.468 -0.353 0.724 Stage3 1.433 4.193 0.438 1.779 9.886 3.276 0.001 ** Stage4 2.557 12.892 0.510 4.745 35.028 5.013 0.000 *** Purity -0.332 0.717 0.746 0.166 3.096 -0.445 0.656 Rsquare = 0.187 (max possible = 7.58e-01 ) Likelihood ratio test p = 7.89e-07 Wald test p = 5.51e-07 Score (logrank) test p = 4.37e-11 ELOVL5 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.122 1.129 0.136 0.865 1.473 0.895 0.371 Age 0.039 1.040 0.008 1.023 1.057 4.751 0.000 *** Gendermale -0.115 0.891 0.212 0.588 1.352 -0.542 0.588 RaceBlack -0.233 0.792 1.111 0.090 6.988 -0.210 0.834 RaceWhite -0.727 0.484 1.018 0.066 3.555 -0.714 0.475 Rsquare = 0.16 (max possible = 9.96e-01 ) Likelihood ratio test p = 8.8e-05 Wald test p = 2.87e-04 Score (logrank) test p = 1.96e-04 ELOVL5 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.436 1.547 0.201 1.044 2.294 2.173 0.030 * Age 0.061 1.063 0.008 1.047 1.080 7.943 0.000 *** Gendermale 0.096 1.101 0.195 0.752 1.613 0.495 0.620 RaceBlack 15.004 3282826.492 2100.784 0.000 Inf 0.007 0.994 RaceWhite 15.218 4063339.746 2100.783 0.000 Inf 0.007 0.994 Purity -1.138 0.320 0.415 0.142 0.723 -2.743 0.006 ** Rsquare = 0.145 (max possible = 9.07e-01 ) Likelihood ratio test p = 1.2e-13 Wald test p = 2.28e-13 Score (logrank) test p = 1.09e-14 ELOVL5 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.020 1.020 0.101 0.836 1.244 0.195 0.845 Age 0.011 1.011 0.008 0.995 1.027 1.342 0.180 Gendermale -0.142 0.868 0.226 0.558 1.351 -0.628 0.530 RaceBlack 0.885 2.422 0.491 0.926 6.337 1.803 0.071 · RaceWhite 0.002 1.002 0.237 0.630 1.594 0.008 0.993 Stage2 0.312 1.366 0.261 0.819 2.278 1.194 0.232 Stage3 0.942 2.564 0.238 1.609 4.088 3.959 0.000 *** Stage4 1.594 4.923 0.619 1.465 16.545 2.577 0.010 * Purity 0.576 1.778 0.458 0.725 4.363 1.257 0.209 Rsquare = 0.085 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.19e-03 Wald test p = 7.15e-04 Score (logrank) test p = 2.7e-04 ELOVL5 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.036 1.036 0.117 0.824 1.304 0.306 0.760 Age 0.007 1.007 0.009 0.989 1.025 0.784 0.433 Gendermale 0.025 1.025 0.171 0.734 1.433 0.147 0.883 RaceBlack 16.111 9927335.808 1885.624 0.000 Inf 0.009 0.993 RaceWhite 16.284 11799391.673 1885.624 0.000 Inf 0.009 0.993 Stage2 0.864 2.372 0.201 1.600 3.516 4.298 0.000 *** Stage3 1.006 2.735 0.219 1.779 4.203 4.587 0.000 *** Stage4 0.992 2.697 0.337 1.394 5.218 2.945 0.003 ** Purity 0.594 1.812 0.343 0.925 3.549 1.734 0.083 · Rsquare = 0.097 (max possible = 9.74e-01 ) Likelihood ratio test p = 2.31e-06 Wald test p = 3.01e-05 Score (logrank) test p = 3.48e-06 ELOVL5 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.012 1.013 0.132 0.781 1.312 0.094 0.925 Age 0.016 1.016 0.009 0.998 1.035 1.752 0.080 · Gendermale 0.436 1.546 0.194 1.058 2.259 2.252 0.024 * RaceBlack 0.012 1.012 0.608 0.307 3.329 0.019 0.985 RaceWhite -0.516 0.597 0.564 0.198 1.801 -0.916 0.360 Stage2 0.210 1.233 0.188 0.853 1.782 1.116 0.264 Stage3 0.601 1.824 0.216 1.195 2.785 2.786 0.005 ** Stage4 0.760 2.138 0.794 0.451 10.140 0.957 0.339 Purity -0.347 0.707 0.365 0.345 1.447 -0.949 0.343 Rsquare = 0.05 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.42e-02 Wald test p = 1.87e-02 Score (logrank) test p = 1.61e-02 ELOVL5 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.354 1.424 0.176 1.009 2.009 2.013 0.044 * Age 0.020 1.020 0.016 0.990 1.052 1.293 0.196 Gendermale -0.235 0.791 0.329 0.415 1.506 -0.714 0.475 RaceBlack -0.185 0.831 1.531 0.041 16.702 -0.121 0.904 RaceWhite -0.774 0.461 1.057 0.058 3.659 -0.732 0.464 Stage2 -0.076 0.927 0.475 0.365 2.352 -0.160 0.873 Stage3 0.021 1.021 0.423 0.446 2.338 0.049 0.961 Stage4 -0.093 0.911 0.478 0.357 2.323 -0.196 0.845 Purity -0.460 0.631 0.563 0.210 1.902 -0.817 0.414 Rsquare = 0.106 (max possible = 9.98e-01 ) Likelihood ratio test p = 3.93e-01 Wald test p = 3.99e-01 Score (logrank) test p = 3.8e-01 ELOVL5 in OV (n=303): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.022 1.023 0.098 0.844 1.239 0.227 0.820 Age 0.036 1.037 0.008 1.020 1.054 4.445 0.000 *** RaceBlack -0.059 0.943 0.577 0.304 2.922 -0.102 0.919 RaceWhite -0.160 0.853 0.515 0.311 2.341 -0.310 0.757 Purity -0.524 0.592 0.677 0.157 2.232 -0.774 0.439 Rsquare = 0.081 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.13e-03 Wald test p = 9.73e-04 Score (logrank) test p = 8.01e-04 ELOVL5 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.001 0.999 0.151 0.743 1.343 -0.008 0.993 Age 0.022 1.022 0.011 1.000 1.044 1.996 0.046 * Gendermale -0.215 0.806 0.219 0.525 1.239 -0.983 0.326 RaceBlack -0.022 0.978 0.741 0.229 4.179 -0.030 0.976 RaceWhite 0.359 1.431 0.476 0.564 3.636 0.754 0.451 Stage2 0.623 1.865 0.443 0.783 4.441 1.408 0.159 Stage3 -0.238 0.788 1.096 0.092 6.750 -0.218 0.828 Stage4 0.237 1.268 0.824 0.252 6.376 0.288 0.774 Purity -0.672 0.511 0.424 0.223 1.172 -1.586 0.113 Rsquare = 0.088 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.34e-02 Wald test p = 1.2e-01 Score (logrank) test p = 1.15e-01 ELOVL5 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.478 0.620 0.580 0.199 1.933 -0.824 0.410 Age 0.040 1.041 0.030 0.982 1.104 1.342 0.179 Gendermale 1.592 4.912 0.954 0.758 31.840 1.669 0.095 · RaceBlack 0.211 1.235 19458.053 0.000 Inf 0.000 1.000 RaceWhite 17.320 33278437.011 14893.513 0.000 Inf 0.001 0.999 Purity 5.778 323.016 3.143 0.682 152914.470 1.838 0.066 · Rsquare = 0.058 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.32e-01 Wald test p = 3.78e-01 Score (logrank) test p = 2.76e-01 ELOVL5 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.171 0.843 0.366 0.412 1.726 -0.468 0.640 Age 0.008 1.008 0.058 0.901 1.129 0.142 0.887 RaceBlack 15.058 3463200.282 6708.838 0.000 Inf 0.002 0.998 RaceWhite 16.219 11057914.578 6708.838 0.000 Inf 0.002 0.998 Purity 1.085 2.958 1.404 0.189 46.402 0.772 0.440 Rsquare = 0.007 (max possible = 1.83e-01 ) Likelihood ratio test p = 7.12e-01 Wald test p = 8.34e-01 Score (logrank) test p = 7.77e-01 ELOVL5 in READ (n=166): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.070 1.072 0.468 0.429 2.681 0.149 0.881 Age 0.111 1.118 0.045 1.023 1.221 2.460 0.014 * Gendermale -0.391 0.677 0.738 0.159 2.875 -0.529 0.597 RaceBlack 13.251 568775.293 10360.684 0.000 Inf 0.001 0.999 RaceWhite 12.238 206462.358 10360.684 0.000 Inf 0.001 0.999 Stage2 -1.878 0.153 1.271 0.013 1.846 -1.478 0.139 Stage3 -0.471 0.625 0.905 0.106 3.681 -0.520 0.603 Stage4 -0.171 0.843 0.967 0.127 5.612 -0.176 0.860 Purity 0.184 1.201 1.374 0.081 17.762 0.134 0.894 Rsquare = 0.209 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.68e-02 Wald test p = 2.47e-01 Score (logrank) test p = 4.47e-02 ELOVL5 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.248 1.281 0.151 0.954 1.722 1.646 0.100 Age 0.021 1.021 0.008 1.004 1.038 2.475 0.013 * Gendermale 0.031 1.031 0.224 0.664 1.600 0.137 0.891 RaceBlack -0.199 0.819 1.088 0.097 6.914 -0.183 0.855 RaceWhite -0.604 0.546 1.027 0.073 4.089 -0.588 0.556 Purity 1.020 2.774 0.580 0.890 8.646 1.759 0.079 · Rsquare = 0.054 (max possible = 9.75e-01 ) Likelihood ratio test p = 4.49e-02 Wald test p = 6.95e-02 Score (logrank) test p = 7.01e-02 ELOVL5 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.283 0.754 0.104 0.615 0.923 -2.729 0.006 ** Age 0.018 1.019 0.005 1.008 1.029 3.515 0.000 *** Gendermale -0.072 0.931 0.158 0.683 1.268 -0.456 0.649 RaceWhite -1.243 0.289 0.403 0.131 0.635 -3.087 0.002 ** Stage2 0.247 1.280 0.219 0.834 1.967 1.129 0.259 Stage3 0.570 1.768 0.205 1.182 2.642 2.777 0.005 ** Stage4 1.318 3.737 0.351 1.878 7.434 3.755 0.000 *** Purity 1.031 2.805 0.343 1.431 5.499 3.003 0.003 ** Rsquare = 0.14 (max possible = 9.92e-01 ) Likelihood ratio test p = 8.75e-10 Wald test p = 4.65e-10 Score (logrank) test p = 5.12e-11 ELOVL5 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.054 9.480000e-01 0.268 0.561 1.601 -0.201 0.840 Age 0.012 1.012000e+00 0.016 0.981 1.045 0.766 0.444 Gendermale 0.218 1.244000e+00 0.434 0.531 2.911 0.503 0.615 RaceWhite -1.294 2.740000e-01 0.640 0.078 0.960 -2.023 0.043 * Stage2 17.481 3.907133e+07 6194.232 0.000 Inf 0.003 0.998 Stage3 17.959 6.299423e+07 6194.232 0.000 Inf 0.003 0.998 Stage4 20.130 5.522472e+08 6194.232 0.000 Inf 0.003 0.997 Purity 0.358 1.430000e+00 1.039 0.186 10.968 0.344 0.731 Rsquare = 0.147 (max possible = 8.69e-01 ) Likelihood ratio test p = 6.06e-02 Wald test p = 5.46e-02 Score (logrank) test p = 4.54e-03 ELOVL5 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.278 0.757 0.120 0.598 0.958 -2.315 0.021 * Age 0.021 1.021 0.006 1.010 1.032 3.645 0.000 *** Gendermale -0.091 0.913 0.173 0.650 1.282 -0.524 0.600 RaceWhite -0.957 0.384 0.602 0.118 1.249 -1.591 0.112 Stage2 0.128 1.137 0.231 0.723 1.788 0.555 0.579 Stage3 0.530 1.699 0.210 1.127 2.563 2.530 0.011 * Stage4 1.079 2.943 0.399 1.346 6.436 2.703 0.007 ** Purity 1.123 3.073 0.373 1.479 6.385 3.009 0.003 ** Rsquare = 0.149 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.08e-07 Wald test p = 1.69e-07 Score (logrank) test p = 6.07e-08 ELOVL5 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.013 1.013 0.094 0.842 1.219 0.140 0.888 Age 0.026 1.027 0.010 1.006 1.048 2.586 0.010 * Gendermale 0.122 1.129 0.207 0.752 1.696 0.586 0.558 RaceBlack 0.268 1.307 0.447 0.544 3.141 0.598 0.550 RaceWhite 0.099 1.105 0.247 0.681 1.791 0.403 0.687 Stage2 0.482 1.619 0.392 0.752 3.488 1.231 0.218 Stage3 0.913 2.491 0.366 1.216 5.106 2.493 0.013 * Stage4 1.316 3.728 0.505 1.385 10.031 2.605 0.009 ** Purity -0.546 0.579 0.387 0.271 1.236 -1.412 0.158 Rsquare = 0.069 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.36e-02 Wald test p = 1.86e-02 Score (logrank) test p = 1.52e-02 ELOVL5 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 3.475 32.293 20647.999 0 Inf 0.000 1.000 Age -1.639 0.194 1778.142 0 Inf -0.001 0.999 RaceBlack 11.277 78961.078 18253286.271 0 Inf 0.000 1.000 RaceWhite -30.047 0.000 18446134.145 0 Inf 0.000 1.000 Stage2 -6.494 0.002 46489.837 0 Inf 0.000 1.000 Stage3 14.145 1390472.615 108249.169 0 Inf 0.000 1.000 Purity 17.282 32014463.425 207749.733 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.05e-03 ELOVL5 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.730 2.076 0.404 0.941 4.577 1.810 0.070 · Age 0.145 1.156 0.028 1.093 1.222 5.095 0.000 *** Gendermale -0.085 0.919 0.633 0.266 3.179 -0.134 0.893 RaceBlack 16.784 19453716.278 7388.286 0.000 Inf 0.002 0.998 RaceWhite 16.497 14608247.685 7388.286 0.000 Inf 0.002 0.998 Stage2 0.932 2.541 1.162 0.260 24.793 0.802 0.422 Stage3 0.391 1.479 0.867 0.270 8.088 0.451 0.652 Stage4 1.968 7.154 1.006 0.995 51.425 1.955 0.051 · Purity 2.797 16.392 1.174 1.642 163.611 2.383 0.017 * Rsquare = 0.157 (max possible = 3.47e-01 ) Likelihood ratio test p = 4.94e-11 Wald test p = 9.49e-05 Score (logrank) test p = 1.82e-11 ELOVL5 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.751 0.472 0.388 0.220 1.010 -1.934 0.053 · Age 0.051 1.052 0.033 0.986 1.123 1.547 0.122 Gendermale -0.389 0.677 0.743 0.158 2.908 -0.524 0.600 RaceBlack -16.432 0.000 11699.356 0.000 Inf -0.001 0.999 RaceWhite 0.502 1.652 1.105 0.189 14.415 0.454 0.650 Purity -0.040 0.961 1.103 0.111 8.341 -0.036 0.971 Rsquare = 0.073 (max possible = 4.51e-01 ) Likelihood ratio test p = 1.96e-01 Wald test p = 3.12e-01 Score (logrank) test p = 1.84e-01 ELOVL5 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.214 1.239 0.164 0.898 1.710 1.304 0.192 Age 0.053 1.055 0.016 1.022 1.088 3.363 0.001 ** RaceBlack -0.405 0.667 0.793 0.141 3.155 -0.511 0.609 RaceWhite -0.562 0.570 0.747 0.132 2.464 -0.753 0.452 Purity 0.566 1.762 0.661 0.482 6.441 0.856 0.392 Rsquare = 0.044 (max possible = 7.81e-01 ) Likelihood ratio test p = 2.55e-02 Wald test p = 2.85e-02 Score (logrank) test p = 2.77e-02 ELOVL5 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 -0.010 0.990 0.290 0.560 1.749 -0.035 0.972 Age 0.044 1.045 0.024 0.996 1.095 1.813 0.070 · RaceBlack 17.587 43445081.953 6473.902 0.000 Inf 0.003 0.998 RaceWhite 17.834 55643509.123 6473.902 0.000 Inf 0.003 0.998 Purity -0.873 0.418 1.059 0.052 3.331 -0.824 0.410 Rsquare = 0.119 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.53e-01 Wald test p = 3.6e-01 Score (logrank) test p = 2.66e-01 ELOVL5 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ELOVL5` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL5 0.348 1.417 0.275 0.826 2.429 1.266 0.206 Age 0.043 1.044 0.019 1.006 1.083 2.268 0.023 * Gendermale 0.302 1.353 0.472 0.536 3.414 0.640 0.522 Stage3 0.283 1.327 0.500 0.498 3.533 0.566 0.571 Stage4 3.910 49.899 1.222 4.547 547.611 3.199 0.001 ** Purity 1.899 6.682 1.268 0.557 80.237 1.498 0.134 Rsquare = 0.269 (max possible = 8.72e-01 ) Likelihood ratio test p = 4.96e-04 Wald test p = 2.94e-03 Score (logrank) test p = 1.88e-09 ELOVL6 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.077 1.080 0.162 0.787 1.483 0.476 0.634 Age 0.006 1.006 0.014 0.978 1.034 0.411 0.681 Gendermale 0.379 1.461 0.417 0.645 3.311 0.909 0.364 RaceBlack 0.032 1.032 11990.945 0.000 Inf 0.000 1.000 RaceWhite 16.935 22629693.568 10211.896 0.000 Inf 0.002 0.999 Purity 2.956 19.219 2.362 0.188 1968.986 1.251 0.211 Rsquare = 0.07 (max possible = 9.38e-01 ) Likelihood ratio test p = 5.94e-01 Wald test p = 8.86e-01 Score (logrank) test p = 7.36e-01 ELOVL6 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.007 1.007 0.077 0.866 1.172 0.094 0.925 Age 0.033 1.034 0.009 1.017 1.052 3.877 0.000 *** Gendermale -0.175 0.840 0.182 0.588 1.200 -0.959 0.337 RaceBlack 0.711 2.036 0.446 0.849 4.882 1.594 0.111 RaceWhite 0.117 1.124 0.355 0.561 2.252 0.330 0.741 Stage2 14.518 2019295.276 1861.989 0.000 Inf 0.008 0.994 Stage3 14.955 3124083.955 1861.989 0.000 Inf 0.008 0.994 Stage4 15.495 5363196.984 1861.989 0.000 Inf 0.008 0.993 Purity 0.130 1.139 0.360 0.563 2.305 0.362 0.717 Rsquare = 0.13 (max possible = 9.91e-01 ) Likelihood ratio test p = 2.02e-07 Wald test p = 1.23e-06 Score (logrank) test p = 3.38e-07 ELOVL6 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.294 1.342 0.099 1.106 1.628 2.980 0.003 ** Age 0.040 1.041 0.008 1.026 1.057 5.241 0.000 *** Gendermale 0.076 1.079 1.007 0.150 7.770 0.075 0.940 RaceBlack -0.158 0.854 0.624 0.252 2.898 -0.254 0.800 RaceWhite -0.353 0.702 0.599 0.217 2.270 -0.590 0.555 Stage2 0.418 1.519 0.304 0.837 2.759 1.374 0.169 Stage3 1.228 3.415 0.314 1.844 6.323 3.908 0.000 *** Stage4 2.585 13.259 0.391 6.164 28.518 6.614 0.000 *** Purity 0.222 1.248 0.434 0.533 2.920 0.511 0.609 Rsquare = 0.09 (max possible = 7.85e-01 ) Likelihood ratio test p = 4.25e-14 Wald test p = 1.33e-17 Score (logrank) test p = 1.89e-23 ELOVL6 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.047 1.048000e+00 0.214 0.688 1.595 0.217 0.828 Age 0.010 1.010000e+00 0.018 0.976 1.046 0.580 0.562 RaceBlack -0.967 3.800000e-01 1.132 0.041 3.498 -0.854 0.393 RaceWhite -1.285 2.770000e-01 1.137 0.030 2.569 -1.130 0.258 Stage2 18.688 1.306233e+08 6470.098 0.000 Inf 0.003 0.998 Stage3 20.107 5.400056e+08 6470.098 0.000 Inf 0.003 0.998 Stage4 21.428 2.022777e+09 6470.098 0.000 Inf 0.003 0.997 Purity 0.737 2.089000e+00 0.962 0.317 13.779 0.766 0.444 Rsquare = 0.157 (max possible = 7.18e-01 ) Likelihood ratio test p = 5.12e-04 Wald test p = 6.71e-03 Score (logrank) test p = 4.58e-06 ELOVL6 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.364 1.439000e+00 0.397 0.661 3.131 0.918 0.359 Age 0.034 1.035000e+00 0.029 0.978 1.095 1.182 0.237 RaceBlack -3.060 4.700000e-02 1.825 0.001 1.677 -1.677 0.094 · RaceWhite -1.605 2.010000e-01 1.456 0.012 3.485 -1.102 0.270 Stage2 18.198 8.001231e+07 14753.824 0.000 Inf 0.001 0.999 Stage3 19.889 4.343759e+08 14753.824 0.000 Inf 0.001 0.999 Stage4 52.366 5.526554e+22 1859055.363 0.000 Inf 0.000 1.000 Purity 3.458 3.175300e+01 2.380 0.299 3370.752 1.453 0.146 Rsquare = 0.379 (max possible = 6.68e-01 ) Likelihood ratio test p = 4.49e-04 Wald test p = 1e+00 Score (logrank) test p = 3.85e-14 ELOVL6 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.547 1.728 0.179 1.216 2.455 3.053 0.002 ** Age 0.062 1.064 0.013 1.037 1.091 4.840 0.000 *** Gendermale -15.208 0.000 3462.455 0.000 Inf -0.004 0.996 RaceBlack -0.899 0.407 1.190 0.039 4.193 -0.756 0.450 RaceWhite -0.265 0.767 1.050 0.098 6.008 -0.252 0.801 Stage2 0.321 1.378 0.376 0.659 2.879 0.853 0.394 Stage3 1.162 3.195 0.409 1.434 7.123 2.841 0.005 ** Stage4 2.695 14.807 0.625 4.346 50.451 4.309 0.000 *** Purity -0.061 0.941 0.629 0.274 3.228 -0.097 0.922 Rsquare = 0.088 (max possible = 6.81e-01 ) Likelihood ratio test p = 2.28e-06 Wald test p = 1.24e-06 Score (logrank) test p = 1.94e-08 ELOVL6 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.769 2.159 0.298 1.203 3.874 2.579 0.010 * Age 0.063 1.065 0.022 1.020 1.112 2.858 0.004 ** Gendermale 1.176 3.240 1.146 0.343 30.627 1.026 0.305 RaceBlack 16.874 21295694.279 6509.147 0.000 Inf 0.003 0.998 RaceWhite 16.240 11295199.035 6509.147 0.000 Inf 0.002 0.998 Stage2 0.126 1.134 1.106 0.130 9.912 0.114 0.910 Stage3 0.975 2.650 1.079 0.320 21.946 0.903 0.366 Stage4 1.857 6.407 1.178 0.637 64.418 1.577 0.115 Purity 0.208 1.231 1.421 0.076 19.940 0.147 0.883 Rsquare = 0.146 (max possible = 6.98e-01 ) Likelihood ratio test p = 3.15e-03 Wald test p = 1.76e-02 Score (logrank) test p = 2.77e-03 ELOVL6 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.074 0.928 0.130 0.719 1.199 -0.571 0.568 Age 0.012 1.012 0.010 0.993 1.032 1.228 0.220 RaceBlack 1.019 2.770 1.069 0.340 22.530 0.953 0.341 RaceWhite 0.822 2.275 1.015 0.311 16.632 0.810 0.418 Purity 0.584 1.793 0.740 0.420 7.650 0.789 0.430 Rsquare = 0.015 (max possible = 8.91e-01 ) Likelihood ratio test p = 6.3e-01 Wald test p = 6.64e-01 Score (logrank) test p = 6.56e-01 ELOVL6 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.475 1.607 0.294 0.903 2.863 1.612 0.107 Age 0.021 1.021 0.021 0.980 1.065 1.000 0.317 Gendermale 0.522 1.685 0.584 0.537 5.290 0.894 0.371 RaceBlack -0.697 0.498 1.484 0.027 9.134 -0.470 0.639 RaceWhite -1.003 0.367 0.863 0.068 1.992 -1.162 0.245 Stage2 0.894 2.446 0.692 0.631 9.486 1.293 0.196 Stage3 -14.355 0.000 7182.517 0.000 Inf -0.002 0.998 Stage4 0.997 2.710 0.701 0.686 10.705 1.423 0.155 Purity 2.531 12.569 1.564 0.586 269.614 1.618 0.106 Rsquare = 0.269 (max possible = 9.46e-01 ) Likelihood ratio test p = 2.58e-01 Wald test p = 4.34e-01 Score (logrank) test p = 2.61e-01 ELOVL6 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.246 0.782 0.181 0.548 1.115 -1.359 0.174 Age 0.024 1.024 0.012 1.001 1.048 2.083 0.037 * Gendermale 0.234 1.264 0.272 0.742 2.153 0.862 0.388 RaceBlack -0.510 0.600 0.829 0.118 3.049 -0.615 0.538 RaceWhite -0.522 0.593 0.777 0.129 2.722 -0.672 0.502 Stage2 0.198 1.219 0.563 0.404 3.675 0.351 0.725 Stage3 0.786 2.195 0.549 0.749 6.437 1.432 0.152 Stage4 1.853 6.377 0.552 2.159 18.832 3.353 0.001 ** Purity -0.173 0.841 0.596 0.262 2.705 -0.290 0.772 Rsquare = 0.116 (max possible = 9.04e-01 ) Likelihood ratio test p = 2.26e-04 Wald test p = 7.49e-05 Score (logrank) test p = 1.1e-05 ELOVL6 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 1.338 3.812 0.820 0.764 19.033 1.631 0.103 Age 0.002 1.002 0.047 0.914 1.097 0.039 0.969 Gendermale 0.621 1.861 1.012 0.256 13.526 0.614 0.539 RaceBlack 1.585 4.880 2.010 0.095 250.928 0.789 0.430 RaceWhite -1.858 0.156 1.419 0.010 2.515 -1.310 0.190 Purity -3.449 0.032 2.620 0.000 5.393 -1.317 0.188 Rsquare = 0.197 (max possible = 5.58e-01 ) Likelihood ratio test p = 1.73e-01 Wald test p = 3.77e-01 Score (logrank) test p = 1.13e-01 ELOVL6 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.030 0.971 0.136 0.744 1.267 -0.219 0.826 Age 0.010 1.010 0.014 0.982 1.038 0.684 0.494 Gendermale 0.490 1.632 0.539 0.568 4.691 0.909 0.363 RaceBlack 0.354 1.424 1.071 0.175 11.612 0.330 0.741 RaceWhite -0.065 0.937 0.451 0.387 2.269 -0.143 0.886 Stage2 0.674 1.961 0.662 0.536 7.177 1.017 0.309 Stage3 1.414 4.113 0.694 1.056 16.015 2.039 0.041 * Stage4 2.848 17.253 0.776 3.773 78.890 3.672 0.000 *** Purity 0.233 1.262 0.776 0.276 5.777 0.300 0.764 Rsquare = 0.141 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.13e-02 Wald test p = 5.08e-03 Score (logrank) test p = 4.24e-04 ELOVL6 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.013 0.987 0.179 0.695 1.402 -0.073 0.942 Age 0.030 1.030 0.008 1.013 1.047 3.537 0.000 *** Gendermale -0.097 0.907 0.215 0.596 1.382 -0.452 0.651 RaceBlack 0.534 1.705 0.731 0.407 7.150 0.730 0.465 RaceWhite -0.241 0.786 0.614 0.236 2.620 -0.392 0.695 Purity -1.089 0.337 0.535 0.118 0.960 -2.036 0.042 * Rsquare = 0.129 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.79e-03 Wald test p = 6.93e-03 Score (logrank) test p = 5.98e-03 ELOVL6 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.172 1.188 0.077 1.021 1.381 2.233 0.026 * Age 0.021 1.021 0.008 1.006 1.036 2.728 0.006 ** Gendermale -0.270 0.764 0.171 0.546 1.068 -1.574 0.116 RaceBlack 0.036 1.036 0.560 0.346 3.106 0.064 0.949 RaceWhite -0.306 0.736 0.511 0.270 2.006 -0.599 0.549 Stage2 0.586 1.796 0.544 0.618 5.215 1.076 0.282 Stage3 0.844 2.327 0.537 0.813 6.659 1.574 0.116 Stage4 1.212 3.359 0.510 1.236 9.131 2.374 0.018 * Purity -0.108 0.898 0.368 0.436 1.847 -0.293 0.769 Rsquare = 0.081 (max possible = 9.89e-01 ) Likelihood ratio test p = 7.11e-05 Wald test p = 1.8e-04 Score (logrank) test p = 1.17e-04 ELOVL6 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.545 1.725000e+00 0.244 1.069 2.781 2.235 0.025 * Age 0.015 1.015000e+00 0.026 0.965 1.068 0.572 0.567 Gendermale -0.451 6.370000e-01 0.549 0.217 1.869 -0.821 0.411 RaceBlack 18.777 1.427961e+08 12832.300 0.000 Inf 0.001 0.999 RaceWhite 17.676 4.750478e+07 12832.300 0.000 Inf 0.001 0.999 Stage2 17.097 2.661156e+07 5693.093 0.000 Inf 0.003 0.998 Stage3 16.658 1.715763e+07 5693.093 0.000 Inf 0.003 0.998 Stage4 17.329 3.355632e+07 5693.092 0.000 Inf 0.003 0.998 Purity -1.794 1.660000e-01 1.128 0.018 1.517 -1.590 0.112 Rsquare = 0.158 (max possible = 9.17e-01 ) Likelihood ratio test p = 2.65e-01 Wald test p = 5.12e-01 Score (logrank) test p = 3.25e-01 ELOVL6 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.099 1.104 0.083 0.938 1.298 1.190 0.234 Age 0.026 1.026 0.008 1.009 1.043 3.044 0.002 ** Gendermale -0.289 0.749 0.182 0.524 1.071 -1.586 0.113 RaceBlack -0.070 0.933 0.566 0.308 2.826 -0.123 0.902 RaceWhite -0.414 0.661 0.512 0.242 1.804 -0.809 0.419 Stage2 0.360 1.433 0.554 0.484 4.242 0.649 0.516 Stage3 0.727 2.069 0.541 0.717 5.971 1.345 0.179 Stage4 1.125 3.080 0.512 1.129 8.406 2.196 0.028 * Purity 0.150 1.162 0.404 0.527 2.566 0.372 0.710 Rsquare = 0.089 (max possible = 9.89e-01 ) Likelihood ratio test p = 1.94e-04 Wald test p = 5.31e-04 Score (logrank) test p = 3.82e-04 ELOVL6 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ELOVL6 2.097 8.140000e+00 0.848 1.544 4.292400e+01 2.472 0.013 Age 0.099 1.104000e+00 0.029 1.043 1.169000e+00 3.402 0.001 Gendermale -1.589 2.040000e-01 0.733 0.049 8.590000e-01 -2.167 0.030 RaceBlack -19.702 0.000000e+00 5372.987 0.000 Inf -0.004 0.997 RaceWhite -3.118 4.400000e-02 1.157 0.005 4.270000e-01 -2.695 0.007 Stage2 18.205 8.058350e+07 0.841 15494477.174 4.190978e+08 21.640 0.000 Stage3 19.092 1.956695e+08 0.802 40600314.323 9.430113e+08 23.794 0.000 Stage4 20.084 5.276403e+08 0.913 88172923.687 3.157481e+09 22.002 0.000 Purity -0.047 9.540000e-01 3.279 0.002 5.893490e+02 -0.014 0.989 signif ELOVL6 * Age ** Gendermale * RaceBlack RaceWhite ** Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.399 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.97e-04 Wald test p = 0e+00 Score (logrank) test p = 4.13e-09 ELOVL6 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.152 1.165 0.111 0.937 1.448 1.372 0.170 Age 0.034 1.034 0.008 1.017 1.052 4.008 0.000 *** Gendermale -0.032 0.968 0.187 0.671 1.397 -0.173 0.863 RaceBlack 0.248 1.282 1.059 0.161 10.213 0.234 0.815 RaceWhite 0.263 1.301 1.019 0.177 9.581 0.258 0.796 Stage2 0.164 1.178 0.347 0.597 2.323 0.473 0.636 Stage3 0.827 2.286 0.230 1.456 3.590 3.590 0.000 *** Stage4 1.749 5.747 0.215 3.767 8.766 8.117 0.000 *** Purity 0.082 1.085 0.373 0.523 2.253 0.220 0.826 Rsquare = 0.177 (max possible = 9.65e-01 ) Likelihood ratio test p = 4.36e-15 Wald test p = 3.46e-15 Score (logrank) test p = 1.82e-18 ELOVL6 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.174 1.190 0.251 0.727 1.946 0.691 0.489 Age 0.008 1.008 0.016 0.977 1.039 0.494 0.621 Gendermale -0.446 0.640 0.390 0.298 1.374 -1.144 0.253 RaceBlack -2.062 0.127 1.198 0.012 1.333 -1.720 0.085 · RaceWhite -2.137 0.118 1.183 0.012 1.200 -1.806 0.071 · Stage2 -0.438 0.646 1.056 0.081 5.118 -0.414 0.679 Stage3 1.591 4.910 0.432 2.107 11.441 3.687 0.000 *** Stage4 2.697 14.830 0.509 5.472 40.189 5.302 0.000 *** Purity -0.340 0.712 0.753 0.163 3.115 -0.451 0.652 Rsquare = 0.165 (max possible = 7.58e-01 ) Likelihood ratio test p = 9.5e-06 Wald test p = 3.54e-06 Score (logrank) test p = 6.03e-10 ELOVL6 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.085 1.089 0.089 0.914 1.297 0.956 0.339 Age 0.038 1.039 0.008 1.022 1.056 4.690 0.000 *** Gendermale -0.153 0.858 0.213 0.565 1.303 -0.719 0.472 RaceBlack -0.269 0.764 1.108 0.087 6.699 -0.243 0.808 RaceWhite -0.676 0.509 1.018 0.069 3.742 -0.664 0.507 Rsquare = 0.161 (max possible = 9.96e-01 ) Likelihood ratio test p = 8.46e-05 Wald test p = 2.7e-04 Score (logrank) test p = 1.86e-04 ELOVL6 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.301 1.351 0.155 0.998 1.830 1.948 0.051 · Age 0.060 1.061 0.008 1.045 1.078 7.690 0.000 *** Gendermale 0.156 1.169 0.198 0.792 1.725 0.787 0.431 RaceBlack 15.516 5478820.862 1999.557 0.000 Inf 0.008 0.994 RaceWhite 15.538 5597970.504 1999.557 0.000 Inf 0.008 0.994 Purity -1.026 0.358 0.404 0.162 0.790 -2.543 0.011 * Rsquare = 0.143 (max possible = 9.07e-01 ) Likelihood ratio test p = 1.92e-13 Wald test p = 3.16e-13 Score (logrank) test p = 1.24e-14 ELOVL6 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.010 1.010 0.078 0.867 1.177 0.126 0.900 Age 0.011 1.011 0.008 0.995 1.027 1.323 0.186 Gendermale -0.143 0.867 0.227 0.556 1.351 -0.630 0.528 RaceBlack 0.892 2.440 0.489 0.936 6.361 1.824 0.068 · RaceWhite 0.000 1.000 0.238 0.628 1.594 0.001 0.999 Stage2 0.314 1.369 0.261 0.821 2.283 1.202 0.229 Stage3 0.948 2.579 0.235 1.627 4.089 4.030 0.000 *** Stage4 1.592 4.916 0.618 1.463 16.522 2.575 0.010 * Purity 0.579 1.784 0.458 0.727 4.374 1.264 0.206 Rsquare = 0.085 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.2e-03 Wald test p = 7.2e-04 Score (logrank) test p = 2.73e-04 ELOVL6 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.174 1.190 0.062 1.054 1.343 2.809 0.005 ** Age 0.008 1.008 0.009 0.991 1.027 0.928 0.354 Gendermale 0.009 1.009 0.169 0.724 1.405 0.052 0.959 RaceBlack 16.156 10382908.605 1850.058 0.000 Inf 0.009 0.993 RaceWhite 16.322 12265988.188 1850.058 0.000 Inf 0.009 0.993 Stage2 0.841 2.319 0.202 1.561 3.443 4.168 0.000 *** Stage3 0.946 2.575 0.220 1.674 3.961 4.306 0.000 *** Stage4 0.940 2.560 0.335 1.329 4.933 2.810 0.005 ** Purity 0.732 2.078 0.344 1.058 4.083 2.124 0.034 * Rsquare = 0.113 (max possible = 9.74e-01 ) Likelihood ratio test p = 8.35e-08 Wald test p = 1.69e-06 Score (logrank) test p = 1.66e-07 ELOVL6 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.123 0.885 0.082 0.753 1.039 -1.493 0.135 Age 0.016 1.016 0.009 0.998 1.035 1.734 0.083 · Gendermale 0.483 1.621 0.195 1.105 2.377 2.471 0.013 * RaceBlack 0.039 1.040 0.602 0.320 3.383 0.066 0.948 RaceWhite -0.511 0.600 0.559 0.201 1.794 -0.914 0.361 Stage2 0.241 1.273 0.188 0.881 1.839 1.284 0.199 Stage3 0.635 1.887 0.216 1.237 2.879 2.945 0.003 ** Stage4 0.771 2.162 0.788 0.461 10.138 0.978 0.328 Purity -0.248 0.781 0.373 0.376 1.622 -0.663 0.507 Rsquare = 0.056 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.13e-02 Wald test p = 8.81e-03 Score (logrank) test p = 7.66e-03 ELOVL6 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.616 1.851 0.216 1.211 2.828 2.846 0.004 ** Age 0.015 1.015 0.016 0.984 1.048 0.941 0.347 Gendermale -0.376 0.687 0.330 0.360 1.311 -1.140 0.254 RaceBlack 0.014 1.014 1.530 0.051 20.331 0.009 0.993 RaceWhite -0.413 0.662 1.047 0.085 5.146 -0.395 0.693 Stage2 -0.220 0.803 0.464 0.323 1.995 -0.473 0.636 Stage3 -0.337 0.714 0.426 0.310 1.646 -0.790 0.429 Stage4 -0.370 0.691 0.481 0.269 1.772 -0.770 0.441 Purity -0.544 0.580 0.561 0.193 1.741 -0.971 0.332 Rsquare = 0.142 (max possible = 9.98e-01 ) Likelihood ratio test p = 1.63e-01 Wald test p = 1.47e-01 Score (logrank) test p = 1.41e-01 ELOVL6 in OV (n=303): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.001 1.001 0.105 0.814 1.229 0.005 0.996 Age 0.036 1.037 0.008 1.020 1.053 4.416 0.000 *** RaceBlack -0.053 0.948 0.577 0.306 2.936 -0.092 0.927 RaceWhite -0.157 0.855 0.516 0.311 2.349 -0.304 0.761 Purity -0.548 0.578 0.674 0.154 2.168 -0.812 0.417 Rsquare = 0.081 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.16e-03 Wald test p = 1e-03 Score (logrank) test p = 8.33e-04 ELOVL6 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.153 1.165 0.141 0.884 1.535 1.083 0.279 Age 0.025 1.025 0.011 1.003 1.048 2.226 0.026 * Gendermale -0.218 0.804 0.217 0.525 1.231 -1.004 0.315 RaceBlack -0.098 0.906 0.742 0.212 3.878 -0.133 0.895 RaceWhite 0.348 1.416 0.474 0.559 3.590 0.734 0.463 Stage2 0.512 1.669 0.447 0.695 4.009 1.145 0.252 Stage3 -0.295 0.744 1.093 0.087 6.338 -0.270 0.787 Stage4 0.085 1.089 0.834 0.212 5.584 0.102 0.918 Purity -0.641 0.527 0.413 0.235 1.182 -1.554 0.120 Rsquare = 0.095 (max possible = 9.91e-01 ) Likelihood ratio test p = 5.74e-02 Wald test p = 9.7e-02 Score (logrank) test p = 9.09e-02 ELOVL6 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.620 1.859 0.489 0.713 4.846 1.268 0.205 Age 0.048 1.049 0.031 0.988 1.114 1.559 0.119 Gendermale 1.446 4.246 0.915 0.707 25.491 1.581 0.114 RaceBlack -0.419 0.657 18451.908 0.000 Inf 0.000 1.000 RaceWhite 17.153 28160807.970 14588.975 0.000 Inf 0.001 0.999 Purity 6.378 588.586 3.720 0.401 864264.059 1.714 0.086 · Rsquare = 0.062 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.03e-01 Wald test p = 3.91e-01 Score (logrank) test p = 2.38e-01 ELOVL6 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.708 2.030 0.366 0.991 4.161 1.934 0.053 · Age 0.008 1.008 0.054 0.907 1.121 0.147 0.883 RaceBlack 15.360 4687854.684 7252.572 0.000 Inf 0.002 0.998 RaceWhite 16.404 13306461.316 7252.572 0.000 Inf 0.002 0.998 Purity 0.200 1.222 1.538 0.060 24.874 0.130 0.896 Rsquare = 0.016 (max possible = 1.83e-01 ) Likelihood ratio test p = 2.59e-01 Wald test p = 2.96e-01 Score (logrank) test p = 2.27e-01 ELOVL6 in READ (n=166): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.841 0.431 0.480 0.168 1.105 -1.751 0.080 · Age 0.111 1.117 0.043 1.027 1.215 2.571 0.010 * Gendermale -0.054 0.948 0.765 0.211 4.246 -0.070 0.944 RaceBlack 14.014 1219588.804 10829.023 0.000 Inf 0.001 0.999 RaceWhite 12.974 431165.598 10829.023 0.000 Inf 0.001 0.999 Stage2 -2.170 0.114 1.310 0.009 1.487 -1.657 0.097 · Stage3 -0.692 0.500 0.949 0.078 3.211 -0.730 0.465 Stage4 -0.062 0.940 0.942 0.148 5.951 -0.066 0.947 Purity -0.197 0.821 1.335 0.060 11.237 -0.148 0.882 Rsquare = 0.242 (max possible = 7.22e-01 ) Likelihood ratio test p = 1.23e-02 Wald test p = 1.17e-01 Score (logrank) test p = 1.87e-02 ELOVL6 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.191 1.211 0.105 0.986 1.486 1.828 0.068 · Age 0.022 1.022 0.008 1.006 1.039 2.654 0.008 ** Gendermale 0.015 1.015 0.223 0.655 1.571 0.065 0.948 RaceBlack 0.059 1.061 1.090 0.125 8.993 0.054 0.957 RaceWhite -0.379 0.685 1.023 0.092 5.087 -0.370 0.711 Purity 1.031 2.803 0.588 0.885 8.876 1.752 0.080 · Rsquare = 0.056 (max possible = 9.75e-01 ) Likelihood ratio test p = 3.65e-02 Wald test p = 4.98e-02 Score (logrank) test p = 4.72e-02 ELOVL6 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.028 0.972 0.071 0.846 1.117 -0.400 0.689 Age 0.018 1.018 0.005 1.008 1.029 3.525 0.000 *** Gendermale -0.047 0.954 0.157 0.701 1.299 -0.301 0.764 RaceWhite -1.260 0.284 0.407 0.128 0.629 -3.100 0.002 ** Stage2 0.276 1.317 0.218 0.859 2.020 1.263 0.207 Stage3 0.615 1.850 0.204 1.240 2.762 3.011 0.003 ** Stage4 1.355 3.878 0.352 1.946 7.727 3.852 0.000 *** Purity 1.029 2.798 0.341 1.435 5.453 3.021 0.003 ** Rsquare = 0.124 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.08e-08 Wald test p = 1.12e-08 Score (logrank) test p = 1.35e-09 ELOVL6 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.081 1.084000e+00 0.238 0.680 1.728 0.339 0.734 Age 0.012 1.013000e+00 0.016 0.981 1.045 0.781 0.435 Gendermale 0.207 1.230000e+00 0.435 0.525 2.883 0.476 0.634 RaceWhite -1.258 2.840000e-01 0.621 0.084 0.959 -2.027 0.043 * Stage2 17.412 3.648188e+07 6211.845 0.000 Inf 0.003 0.998 Stage3 17.975 6.402384e+07 6211.845 0.000 Inf 0.003 0.998 Stage4 20.027 4.986736e+08 6211.845 0.000 Inf 0.003 0.997 Purity 0.219 1.245000e+00 0.953 0.192 8.061 0.230 0.818 Rsquare = 0.148 (max possible = 8.69e-01 ) Likelihood ratio test p = 5.91e-02 Wald test p = 5.59e-02 Score (logrank) test p = 4.48e-03 ELOVL6 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.032 0.969 0.076 0.834 1.124 -0.419 0.675 Age 0.020 1.021 0.006 1.009 1.032 3.626 0.000 *** Gendermale -0.054 0.947 0.172 0.676 1.328 -0.314 0.753 RaceWhite -1.011 0.364 0.609 0.110 1.202 -1.659 0.097 · Stage2 0.152 1.165 0.230 0.742 1.829 0.662 0.508 Stage3 0.571 1.770 0.210 1.173 2.669 2.721 0.007 ** Stage4 1.139 3.125 0.400 1.428 6.841 2.850 0.004 ** Purity 1.154 3.171 0.370 1.535 6.552 3.117 0.002 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.02e-06 Wald test p = 1.61e-06 Score (logrank) test p = 6.21e-07 ELOVL6 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.001 0.999 0.096 0.827 1.207 -0.005 0.996 Age 0.026 1.027 0.010 1.006 1.047 2.583 0.010 * Gendermale 0.122 1.130 0.208 0.752 1.697 0.588 0.557 RaceBlack 0.268 1.307 0.454 0.537 3.182 0.590 0.555 RaceWhite 0.094 1.099 0.244 0.681 1.774 0.387 0.699 Stage2 0.487 1.628 0.390 0.758 3.495 1.250 0.211 Stage3 0.919 2.507 0.364 1.229 5.114 2.527 0.011 * Stage4 1.321 3.746 0.504 1.395 10.058 2.620 0.009 ** Purity -0.556 0.573 0.381 0.272 1.209 -1.461 0.144 Rsquare = 0.069 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.37e-02 Wald test p = 1.88e-02 Score (logrank) test p = 1.53e-02 ELOVL6 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -1.268 0.281 12446.891 0 Inf 0.000 1.000 Age -1.668 0.189 1761.954 0 Inf -0.001 0.999 RaceBlack 8.793 6584.681 16863999.294 0 Inf 0.000 1.000 RaceWhite -34.182 0.000 16583411.008 0 Inf 0.000 1.000 Stage2 -2.197 0.111 41709.776 0 Inf 0.000 1.000 Stage3 15.196 3978183.761 112930.235 0 Inf 0.000 1.000 Purity 12.613 300445.731 192248.040 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.21e-03 ELOVL6 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.207 1.230 0.377 0.588 2.574 0.549 0.583 Age 0.144 1.155 0.028 1.092 1.220 5.069 0.000 *** Gendermale -0.101 0.904 0.639 0.258 3.166 -0.157 0.875 RaceBlack 17.003 24216965.453 6752.311 0.000 Inf 0.003 0.998 RaceWhite 16.726 18361263.936 6752.311 0.000 Inf 0.002 0.998 Stage2 -0.033 0.967 1.122 0.107 8.714 -0.030 0.976 Stage3 0.158 1.171 0.869 0.213 6.430 0.181 0.856 Stage4 1.596 4.934 0.989 0.710 34.302 1.613 0.107 Purity 2.342 10.400 1.159 1.072 100.925 2.020 0.043 * Rsquare = 0.15 (max possible = 3.47e-01 ) Likelihood ratio test p = 2.22e-10 Wald test p = 2.34e-04 Score (logrank) test p = 4.28e-11 ELOVL6 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 1.057 2.879 0.491 1.100 7.538 2.153 0.031 * Age 0.050 1.051 0.030 0.991 1.115 1.645 0.100 Gendermale -0.188 0.828 0.737 0.195 3.514 -0.255 0.798 RaceBlack -15.828 0.000 11069.959 0.000 Inf -0.001 0.999 RaceWhite 0.903 2.466 1.132 0.268 22.694 0.797 0.425 Purity 0.398 1.489 1.135 0.161 13.761 0.351 0.726 Rsquare = 0.079 (max possible = 4.51e-01 ) Likelihood ratio test p = 1.54e-01 Wald test p = 3e-01 Score (logrank) test p = 2.08e-01 ELOVL6 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.393 1.482 0.158 1.087 2.020 2.491 0.013 * Age 0.052 1.053 0.016 1.021 1.086 3.235 0.001 ** RaceBlack -0.832 0.435 0.814 0.088 2.146 -1.022 0.307 RaceWhite -0.903 0.405 0.763 0.091 1.809 -1.183 0.237 Purity 0.520 1.682 0.639 0.480 5.887 0.813 0.416 Rsquare = 0.06 (max possible = 7.81e-01 ) Likelihood ratio test p = 3.65e-03 Wald test p = 6.76e-03 Score (logrank) test p = 5.34e-03 ELOVL6 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 -0.365 0.694 0.233 0.439 1.097 -1.564 0.118 Age 0.054 1.055 0.025 1.004 1.108 2.136 0.033 * RaceBlack 17.488 39358604.448 6560.623 0.000 Inf 0.003 0.998 RaceWhite 17.736 50444352.158 6560.623 0.000 Inf 0.003 0.998 Purity -1.372 0.254 1.134 0.027 2.339 -1.211 0.226 Rsquare = 0.16 (max possible = 9.83e-01 ) Likelihood ratio test p = 1.06e-01 Wald test p = 1.84e-01 Score (logrank) test p = 1.31e-01 ELOVL6 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ELOVL6` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL6 0.526 1.692 0.296 0.948 3.020 1.778 0.075 · Age 0.036 1.037 0.019 1.000 1.076 1.939 0.052 · Gendermale 0.402 1.495 0.484 0.579 3.862 0.830 0.406 Stage3 0.245 1.277 0.499 0.481 3.395 0.491 0.624 Stage4 3.979 53.476 1.226 4.839 590.953 3.246 0.001 ** Purity 1.902 6.702 1.275 0.551 81.522 1.492 0.136 Rsquare = 0.284 (max possible = 8.72e-01 ) Likelihood ratio test p = 2.52e-04 Wald test p = 2.12e-03 Score (logrank) test p = 1.04e-09 ELOVL7 in ACC (n=79): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.558 0.573 0.177 0.405 0.809 -3.158 0.002 ** Age 0.010 1.010 0.013 0.986 1.036 0.818 0.414 Gendermale 0.707 2.028 0.425 0.882 4.663 1.664 0.096 · RaceBlack -1.232 0.292 14000.194 0.000 Inf 0.000 1.000 RaceWhite 15.656 6301216.903 12097.650 0.000 Inf 0.001 0.999 Purity 1.679 5.358 2.198 0.072 398.210 0.764 0.445 Rsquare = 0.217 (max possible = 9.38e-01 ) Likelihood ratio test p = 1.56e-02 Wald test p = 4.92e-02 Score (logrank) test p = 1.44e-02 ELOVL7 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.016 0.984 0.091 0.824 1.176 -0.173 0.862 Age 0.033 1.034 0.009 1.017 1.052 3.889 0.000 *** Gendermale -0.173 0.841 0.179 0.593 1.194 -0.968 0.333 RaceBlack 0.720 2.054 0.449 0.852 4.954 1.602 0.109 RaceWhite 0.123 1.131 0.356 0.562 2.273 0.344 0.731 Stage2 14.497 1976032.412 1862.305 0.000 Inf 0.008 0.994 Stage3 14.930 3047913.084 1862.305 0.000 Inf 0.008 0.994 Stage4 15.473 5247740.582 1862.305 0.000 Inf 0.008 0.993 Purity 0.146 1.157 0.339 0.595 2.247 0.429 0.668 Rsquare = 0.13 (max possible = 9.91e-01 ) Likelihood ratio test p = 2e-07 Wald test p = 1.24e-06 Score (logrank) test p = 3.39e-07 ELOVL7 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.159 0.853 0.100 0.701 1.037 -1.593 0.111 Age 0.036 1.037 0.008 1.021 1.052 4.738 0.000 *** Gendermale -0.010 0.990 1.008 0.137 7.141 -0.010 0.992 RaceBlack 0.050 1.051 0.619 0.312 3.540 0.081 0.936 RaceWhite -0.149 0.862 0.597 0.267 2.779 -0.249 0.803 Stage2 0.422 1.524 0.304 0.840 2.764 1.388 0.165 Stage3 1.201 3.322 0.313 1.798 6.138 3.834 0.000 *** Stage4 2.572 13.088 0.391 6.086 28.145 6.583 0.000 *** Purity 0.529 1.697 0.422 0.741 3.884 1.252 0.211 Rsquare = 0.084 (max possible = 7.85e-01 ) Likelihood ratio test p = 7.68e-13 Wald test p = 3.64e-16 Score (logrank) test p = 3.3e-22 ELOVL7 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.145 8.650000e-01 0.225 0.556 1.346 -0.643 0.520 Age 0.011 1.011000e+00 0.017 0.977 1.046 0.637 0.524 RaceBlack -0.961 3.830000e-01 1.118 0.043 3.423 -0.859 0.390 RaceWhite -1.263 2.830000e-01 1.129 0.031 2.587 -1.118 0.264 Stage2 18.687 1.305283e+08 6497.575 0.000 Inf 0.003 0.998 Stage3 20.019 4.945494e+08 6497.575 0.000 Inf 0.003 0.998 Stage4 21.414 1.994563e+09 6497.575 0.000 Inf 0.003 0.997 Purity 0.772 2.165000e+00 0.959 0.330 14.185 0.805 0.421 Rsquare = 0.159 (max possible = 7.18e-01 ) Likelihood ratio test p = 4.42e-04 Wald test p = 5.87e-03 Score (logrank) test p = 3.52e-06 ELOVL7 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.347 7.060000e-01 0.593 0.221 2.260 -0.586 0.558 Age 0.036 1.037000e+00 0.029 0.979 1.098 1.227 0.220 RaceBlack -2.770 6.300000e-02 1.835 0.002 2.283 -1.510 0.131 RaceWhite -1.524 2.180000e-01 1.485 0.012 4.002 -1.026 0.305 Stage2 18.456 1.035669e+08 14717.521 0.000 Inf 0.001 0.999 Stage3 20.013 4.916189e+08 14717.521 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 2.639 1.399800e+01 2.340 0.143 1373.122 1.128 0.259 Rsquare = 0.374 (max possible = 6.68e-01 ) Likelihood ratio test p = 2.56e-04 Wald test p = 2.48e-01 Score (logrank) test p = 1.17e-14 ELOVL7 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.240 0.787 0.160 0.575 1.077 -1.496 0.135 Age 0.051 1.053 0.012 1.028 1.078 4.256 0.000 *** Gendermale -15.567 0.000 3483.206 0.000 Inf -0.004 0.996 RaceBlack -0.428 0.652 1.176 0.065 6.528 -0.364 0.716 RaceWhite 0.334 1.397 1.033 0.185 10.577 0.324 0.746 Stage2 0.323 1.382 0.373 0.665 2.873 0.866 0.386 Stage3 0.934 2.545 0.397 1.168 5.546 2.351 0.019 * Stage4 2.248 9.469 0.597 2.940 30.496 3.767 0.000 *** Purity 0.298 1.348 0.612 0.406 4.472 0.488 0.626 Rsquare = 0.075 (max possible = 6.81e-01 ) Likelihood ratio test p = 4.09e-05 Wald test p = 1.42e-05 Score (logrank) test p = 2.03e-07 ELOVL7 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.023 0.977 0.207 0.651 1.467 -0.111 0.912 Age 0.050 1.051 0.021 1.008 1.095 2.347 0.019 * Gendermale 0.983 2.674 1.106 0.306 23.344 0.890 0.374 RaceBlack 16.557 15513456.271 6466.880 0.000 Inf 0.003 0.998 RaceWhite 15.954 8484222.116 6466.880 0.000 Inf 0.002 0.998 Stage2 0.690 1.993 1.074 0.243 16.368 0.642 0.521 Stage3 1.600 4.952 1.060 0.620 39.566 1.509 0.131 Stage4 2.099 8.159 1.174 0.818 81.403 1.789 0.074 · Purity 1.061 2.890 1.330 0.213 39.182 0.798 0.425 Rsquare = 0.105 (max possible = 6.98e-01 ) Likelihood ratio test p = 4.19e-02 Wald test p = 7.13e-02 Score (logrank) test p = 2.46e-02 ELOVL7 in CESC (n=306): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.319 0.727 0.156 0.535 0.988 -2.039 0.041 * Age 0.014 1.014 0.010 0.994 1.034 1.350 0.177 RaceBlack 0.997 2.710 1.069 0.333 22.034 0.932 0.351 RaceWhite 0.837 2.308 1.015 0.316 16.883 0.824 0.410 Purity 0.647 1.910 0.749 0.440 8.286 0.864 0.388 Rsquare = 0.031 (max possible = 8.91e-01 ) Likelihood ratio test p = 2.05e-01 Wald test p = 2.25e-01 Score (logrank) test p = 2.16e-01 ELOVL7 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.230 0.795 0.269 0.469 1.346 -0.855 0.392 Age 0.015 1.015 0.021 0.973 1.058 0.696 0.486 Gendermale 0.023 1.023 0.642 0.291 3.603 0.036 0.972 RaceBlack -0.433 0.648 1.460 0.037 11.339 -0.297 0.767 RaceWhite -1.041 0.353 0.878 0.063 1.974 -1.186 0.236 Stage2 0.631 1.880 0.670 0.506 6.994 0.942 0.346 Stage3 -16.802 0.000 7005.655 0.000 Inf -0.002 0.998 Stage4 0.659 1.933 0.696 0.494 7.558 0.947 0.343 Purity 1.584 4.874 1.567 0.226 105.119 1.011 0.312 Rsquare = 0.227 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.13e-01 Wald test p = 5.81e-01 Score (logrank) test p = 4.09e-01 ELOVL7 in COAD (n=458): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.006 1.006 0.151 0.749 1.352 0.041 0.967 Age 0.024 1.024 0.011 1.001 1.047 2.074 0.038 * Gendermale 0.213 1.237 0.269 0.730 2.098 0.789 0.430 RaceBlack -0.416 0.660 0.828 0.130 3.343 -0.502 0.615 RaceWhite -0.443 0.642 0.775 0.141 2.930 -0.572 0.567 Stage2 0.211 1.235 0.562 0.410 3.718 0.375 0.708 Stage3 0.807 2.242 0.550 0.763 6.589 1.468 0.142 Stage4 1.890 6.619 0.562 2.198 19.932 3.361 0.001 ** Purity -0.221 0.802 0.601 0.247 2.605 -0.367 0.713 Rsquare = 0.109 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.64e-04 Wald test p = 1.61e-04 Score (logrank) test p = 2.37e-05 ELOVL7 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.143 0.866 0.640 0.247 3.036 -0.224 0.823 Age -0.001 0.999 0.042 0.919 1.086 -0.023 0.982 Gendermale 0.664 1.943 1.046 0.250 15.104 0.635 0.525 RaceBlack 0.397 1.488 1.575 0.068 32.604 0.252 0.801 RaceWhite -2.026 0.132 1.330 0.010 1.786 -1.524 0.128 Purity -2.008 0.134 2.070 0.002 7.763 -0.970 0.332 Rsquare = 0.132 (max possible = 5.58e-01 ) Likelihood ratio test p = 4.46e-01 Wald test p = 5.8e-01 Score (logrank) test p = 3.28e-01 ELOVL7 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.072 1.075 0.148 0.805 1.436 0.489 0.625 Age 0.008 1.008 0.014 0.980 1.037 0.563 0.573 Gendermale 0.446 1.562 0.543 0.539 4.530 0.821 0.411 RaceBlack 0.342 1.407 1.069 0.173 11.425 0.320 0.749 RaceWhite -0.089 0.914 0.447 0.381 2.195 -0.200 0.841 Stage2 0.704 2.023 0.654 0.561 7.288 1.077 0.281 Stage3 1.449 4.259 0.671 1.144 15.853 2.161 0.031 * Stage4 2.865 17.556 0.774 3.851 80.037 3.702 0.000 *** Purity 0.261 1.298 0.777 0.283 5.954 0.336 0.737 Rsquare = 0.142 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.06e-02 Wald test p = 4.76e-03 Score (logrank) test p = 3.91e-04 ELOVL7 in GBM (n=153): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.013 0.988 0.138 0.754 1.294 -0.091 0.927 Age 0.030 1.030 0.008 1.013 1.047 3.568 0.000 *** Gendermale -0.093 0.911 0.214 0.599 1.385 -0.437 0.662 RaceBlack 0.524 1.689 0.728 0.406 7.030 0.720 0.471 RaceWhite -0.241 0.786 0.614 0.236 2.618 -0.393 0.695 Purity -1.100 0.333 0.556 0.112 0.988 -1.981 0.048 * Rsquare = 0.129 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.79e-03 Wald test p = 6.83e-03 Score (logrank) test p = 5.98e-03 ELOVL7 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.026 1.026 0.082 0.874 1.205 0.314 0.754 Age 0.022 1.022 0.008 1.007 1.038 2.895 0.004 ** Gendermale -0.246 0.782 0.172 0.558 1.095 -1.431 0.152 RaceBlack 0.145 1.156 0.560 0.386 3.462 0.259 0.796 RaceWhite -0.240 0.787 0.511 0.289 2.142 -0.470 0.639 Stage2 0.616 1.852 0.544 0.638 5.375 1.134 0.257 Stage3 0.853 2.347 0.537 0.820 6.720 1.590 0.112 Stage4 1.259 3.522 0.510 1.296 9.570 2.468 0.014 * Purity -0.033 0.967 0.366 0.472 1.984 -0.090 0.928 Rsquare = 0.07 (max possible = 9.89e-01 ) Likelihood ratio test p = 5.07e-04 Wald test p = 1.39e-03 Score (logrank) test p = 1e-03 ELOVL7 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.164 8.490000e-01 0.256 0.513 1.403 -0.640 0.522 Age 0.009 1.009000e+00 0.026 0.960 1.061 0.342 0.732 Gendermale -0.126 8.820000e-01 0.545 0.303 2.564 -0.231 0.817 RaceBlack 18.714 1.340548e+08 12128.545 0.000 Inf 0.002 0.999 RaceWhite 17.975 6.404582e+07 12128.545 0.000 Inf 0.001 0.999 Stage2 17.383 3.542482e+07 5201.672 0.000 Inf 0.003 0.997 Stage3 16.541 1.525882e+07 5201.672 0.000 Inf 0.003 0.997 Stage4 17.373 3.507839e+07 5201.672 0.000 Inf 0.003 0.997 Purity -1.528 2.170000e-01 1.048 0.028 1.692 -1.458 0.145 Rsquare = 0.093 (max possible = 9.17e-01 ) Likelihood ratio test p = 7.07e-01 Wald test p = 9.29e-01 Score (logrank) test p = 8.29e-01 ELOVL7 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.045 1.046 0.088 0.881 1.243 0.512 0.609 Age 0.027 1.027 0.008 1.010 1.044 3.165 0.002 ** Gendermale -0.278 0.757 0.183 0.529 1.084 -1.518 0.129 RaceBlack 0.004 1.004 0.565 0.331 3.039 0.007 0.995 RaceWhite -0.382 0.683 0.513 0.250 1.865 -0.745 0.456 Stage2 0.363 1.438 0.554 0.486 4.258 0.656 0.512 Stage3 0.729 2.074 0.541 0.718 5.986 1.349 0.177 Stage4 1.151 3.163 0.512 1.160 8.627 2.249 0.025 * Purity 0.232 1.261 0.403 0.573 2.775 0.576 0.565 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.07e-04 Wald test p = 9.4e-04 Score (logrank) test p = 6.89e-04 ELOVL7 in KICH (n=66): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p ELOVL7 -0.196 8.220000e-01 0.248 0.506 1.337000e+00 -0.790 0.430 Age 0.066 1.068000e+00 0.029 1.010 1.130000e+00 2.311 0.021 Gendermale -0.848 4.280000e-01 0.733 0.102 1.799000e+00 -1.158 0.247 RaceBlack -16.697 0.000000e+00 5479.450 0.000 Inf -0.003 0.998 RaceWhite -1.636 1.950000e-01 1.172 0.020 1.937000e+00 -1.396 0.163 Stage2 15.518 5.486101e+06 0.851 1035331.045 2.907022e+07 18.239 0.000 Stage3 16.824 2.026391e+07 0.779 4403789.724 9.324383e+07 21.604 0.000 Stage4 19.371 2.587480e+08 0.911 43371342.350 1.543658e+09 21.258 0.000 Purity 1.618 5.041000e+00 4.117 0.002 1.610133e+04 0.393 0.694 signif ELOVL7 Age * Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.351 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.3e-03 Wald test p = 9.59e-266 Score (logrank) test p = 6.15e-09 ELOVL7 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.311 0.733 0.070 0.639 0.841 -4.428 0.000 *** Age 0.032 1.032 0.008 1.015 1.049 3.744 0.000 *** Gendermale -0.233 0.792 0.190 0.546 1.150 -1.226 0.220 RaceBlack 1.079 2.941 1.078 0.355 24.336 1.000 0.317 RaceWhite 1.081 2.948 1.041 0.383 22.704 1.038 0.299 Stage2 0.193 1.213 0.346 0.616 2.391 0.559 0.576 Stage3 0.745 2.107 0.231 1.341 3.311 3.230 0.001 ** Stage4 1.650 5.209 0.218 3.397 7.988 7.565 0.000 *** Purity 0.415 1.515 0.366 0.739 3.103 1.135 0.257 Rsquare = 0.207 (max possible = 9.65e-01 ) Likelihood ratio test p = 2.04e-18 Wald test p = 3.05e-19 Score (logrank) test p = 1.33e-22 ELOVL7 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.050 0.952 0.197 0.647 1.399 -0.252 0.801 Age 0.007 1.007 0.015 0.977 1.038 0.465 0.642 Gendermale -0.497 0.608 0.383 0.287 1.288 -1.299 0.194 RaceBlack -2.046 0.129 1.204 0.012 1.369 -1.699 0.089 · RaceWhite -2.104 0.122 1.193 0.012 1.265 -1.763 0.078 · Stage2 -0.398 0.671 1.055 0.085 5.312 -0.378 0.706 Stage3 1.630 5.102 0.427 2.211 11.773 3.819 0.000 *** Stage4 2.698 14.856 0.508 5.494 40.173 5.317 0.000 *** Purity -0.261 0.770 0.757 0.175 3.394 -0.345 0.730 Rsquare = 0.163 (max possible = 7.58e-01 ) Likelihood ratio test p = 1.13e-05 Wald test p = 3.55e-06 Score (logrank) test p = 6.63e-10 ELOVL7 in LAML (n=173): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.091 1.096 0.087 0.925 1.299 1.055 0.291 Age 0.038 1.039 0.008 1.022 1.055 4.645 0.000 *** Gendermale -0.160 0.852 0.213 0.561 1.294 -0.751 0.453 RaceBlack -0.247 0.781 1.110 0.089 6.878 -0.222 0.824 RaceWhite -0.639 0.528 1.019 0.072 3.894 -0.627 0.531 Rsquare = 0.162 (max possible = 9.96e-01 ) Likelihood ratio test p = 7.9e-05 Wald test p = 2.76e-04 Score (logrank) test p = 2.02e-04 ELOVL7 in LGG (n=516): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.023 1.024 0.142 0.775 1.351 0.165 0.869 Age 0.062 1.063 0.008 1.048 1.080 8.027 0.000 *** Gendermale 0.085 1.089 0.196 0.741 1.599 0.434 0.664 RaceBlack 15.387 4814160.137 1995.997 0.000 Inf 0.008 0.994 RaceWhite 15.414 4944686.321 1995.997 0.000 Inf 0.008 0.994 Purity -0.942 0.390 0.414 0.173 0.877 -2.276 0.023 * Rsquare = 0.136 (max possible = 9.07e-01 ) Likelihood ratio test p = 1.13e-12 Wald test p = 1.1e-12 Score (logrank) test p = 9.6e-14 ELOVL7 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.067 1.069 0.068 0.937 1.220 0.989 0.323 Age 0.012 1.012 0.008 0.996 1.028 1.430 0.153 Gendermale -0.066 0.936 0.239 0.586 1.496 -0.275 0.783 RaceBlack 0.892 2.440 0.489 0.936 6.364 1.824 0.068 · RaceWhite 0.008 1.008 0.238 0.632 1.608 0.034 0.973 Stage2 0.296 1.344 0.262 0.805 2.245 1.130 0.258 Stage3 0.930 2.535 0.236 1.596 4.026 3.939 0.000 *** Stage4 1.662 5.270 0.624 1.552 17.890 2.665 0.008 ** Purity 0.572 1.771 0.459 0.720 4.355 1.245 0.213 Rsquare = 0.087 (max possible = 9.66e-01 ) Likelihood ratio test p = 8.36e-04 Wald test p = 4.44e-04 Score (logrank) test p = 1.62e-04 ELOVL7 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.149 1.161 0.080 0.993 1.357 1.873 0.061 · Age 0.009 1.009 0.009 0.991 1.027 0.937 0.349 Gendermale 0.044 1.045 0.169 0.750 1.456 0.260 0.795 RaceBlack 16.025 9111473.614 1935.124 0.000 Inf 0.008 0.993 RaceWhite 16.192 10768613.682 1935.124 0.000 Inf 0.008 0.993 Stage2 0.869 2.385 0.201 1.608 3.538 4.319 0.000 *** Stage3 1.043 2.838 0.219 1.849 4.356 4.770 0.000 *** Stage4 0.996 2.708 0.332 1.412 5.196 2.997 0.003 ** Purity 0.631 1.879 0.345 0.955 3.698 1.827 0.068 · Rsquare = 0.104 (max possible = 9.74e-01 ) Likelihood ratio test p = 5.41e-07 Wald test p = 9.13e-06 Score (logrank) test p = 8.31e-07 ELOVL7 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.071 1.074 0.109 0.868 1.328 0.655 0.513 Age 0.017 1.017 0.009 0.998 1.036 1.762 0.078 · Gendermale 0.448 1.565 0.194 1.069 2.291 2.304 0.021 * RaceBlack -0.009 0.991 0.609 0.301 3.268 -0.014 0.988 RaceWhite -0.525 0.591 0.565 0.195 1.791 -0.929 0.353 Stage2 0.198 1.219 0.188 0.843 1.761 1.054 0.292 Stage3 0.600 1.821 0.215 1.196 2.773 2.795 0.005 ** Stage4 0.793 2.210 0.799 0.461 10.585 0.992 0.321 Purity -0.365 0.695 0.366 0.339 1.423 -0.996 0.319 Rsquare = 0.051 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.09e-02 Wald test p = 1.65e-02 Score (logrank) test p = 1.4e-02 ELOVL7 in MESO (n=87): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.234 0.791 0.152 0.588 1.065 -1.543 0.123 Age 0.020 1.020 0.016 0.989 1.052 1.278 0.201 Gendermale -0.283 0.753 0.331 0.394 1.441 -0.856 0.392 RaceBlack 0.511 1.666 1.549 0.080 34.658 0.330 0.742 RaceWhite -0.271 0.762 1.054 0.097 6.021 -0.257 0.797 Stage2 -0.242 0.785 0.471 0.312 1.977 -0.514 0.607 Stage3 -0.143 0.867 0.424 0.377 1.991 -0.336 0.737 Stage4 -0.231 0.793 0.484 0.307 2.047 -0.478 0.632 Purity -0.842 0.431 0.555 0.145 1.280 -1.515 0.130 Rsquare = 0.086 (max possible = 9.98e-01 ) Likelihood ratio test p = 5.69e-01 Wald test p = 5.21e-01 Score (logrank) test p = 5.07e-01 ELOVL7 in OV (n=303): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.034 1.034 0.102 0.847 1.264 0.331 0.740 Age 0.036 1.037 0.008 1.020 1.053 4.432 0.000 *** RaceBlack -0.046 0.955 0.577 0.308 2.958 -0.080 0.936 RaceWhite -0.151 0.860 0.515 0.313 2.362 -0.293 0.770 Purity -0.572 0.564 0.672 0.151 2.108 -0.851 0.395 Rsquare = 0.082 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.1e-03 Wald test p = 9.59e-04 Score (logrank) test p = 8.05e-04 ELOVL7 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.012 0.988 0.135 0.758 1.287 -0.091 0.927 Age 0.022 1.022 0.011 1.000 1.044 1.970 0.049 * Gendermale -0.215 0.806 0.217 0.527 1.232 -0.995 0.320 RaceBlack -0.013 0.987 0.746 0.229 4.257 -0.017 0.986 RaceWhite 0.367 1.443 0.482 0.561 3.714 0.760 0.447 Stage2 0.631 1.879 0.444 0.787 4.487 1.421 0.155 Stage3 -0.237 0.789 1.092 0.093 6.704 -0.217 0.828 Stage4 0.244 1.277 0.828 0.252 6.467 0.295 0.768 Purity -0.676 0.509 0.412 0.227 1.141 -1.639 0.101 Rsquare = 0.089 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.32e-02 Wald test p = 1.2e-01 Score (logrank) test p = 1.15e-01 ELOVL7 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.763 2.144 0.450 0.887 5.181 1.695 0.090 · Age 0.044 1.045 0.028 0.988 1.105 1.540 0.124 Gendermale 1.407 4.085 0.902 0.698 23.914 1.561 0.119 RaceBlack -0.577 0.562 20928.808 0.000 Inf 0.000 1.000 RaceWhite 16.724 18327682.017 16983.479 0.000 Inf 0.001 0.999 Purity 6.989 1084.765 3.962 0.460 2556183.562 1.764 0.078 · Rsquare = 0.074 (max possible = 3.07e-01 ) Likelihood ratio test p = 4.83e-02 Wald test p = 2.87e-01 Score (logrank) test p = 1.74e-01 ELOVL7 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.149 1.160 0.327 0.611 2.204 0.454 0.650 Age 0.011 1.011 0.057 0.905 1.130 0.194 0.846 RaceBlack 14.984 3217500.354 6777.224 0.000 Inf 0.002 0.998 RaceWhite 16.355 12678036.614 6777.224 0.000 Inf 0.002 0.998 Purity 1.068 2.908 1.373 0.197 42.857 0.778 0.437 Rsquare = 0.007 (max possible = 1.83e-01 ) Likelihood ratio test p = 7.13e-01 Wald test p = 8.4e-01 Score (logrank) test p = 7.86e-01 ELOVL7 in READ (n=166): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.543 0.581 0.525 0.208 1.624 -1.036 0.300 Age 0.108 1.114 0.044 1.022 1.214 2.449 0.014 * Gendermale -0.166 0.847 0.713 0.209 3.428 -0.233 0.816 RaceBlack 12.571 288130.039 10278.554 0.000 Inf 0.001 0.999 RaceWhite 11.718 122778.514 10278.554 0.000 Inf 0.001 0.999 Stage2 -1.811 0.164 1.270 0.014 1.971 -1.426 0.154 Stage3 -0.244 0.783 0.911 0.131 4.674 -0.268 0.789 Stage4 0.114 1.120 0.978 0.165 7.612 0.116 0.907 Purity 0.285 1.330 1.396 0.086 20.501 0.204 0.838 Rsquare = 0.22 (max possible = 7.22e-01 ) Likelihood ratio test p = 2.64e-02 Wald test p = 2.32e-01 Score (logrank) test p = 4.45e-02 ELOVL7 in SARC (n=260): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.093 0.911 0.126 0.711 1.167 -0.737 0.461 Age 0.022 1.022 0.008 1.006 1.039 2.626 0.009 ** Gendermale -0.020 0.980 0.222 0.634 1.515 -0.090 0.928 RaceBlack -0.081 0.922 1.088 0.109 7.780 -0.075 0.940 RaceWhite -0.441 0.643 1.022 0.087 4.772 -0.432 0.666 Purity 1.001 2.722 0.580 0.873 8.482 1.727 0.084 · Rsquare = 0.045 (max possible = 9.75e-01 ) Likelihood ratio test p = 9.86e-02 Wald test p = 1.36e-01 Score (logrank) test p = 1.39e-01 ELOVL7 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.023 1.023 0.071 0.891 1.175 0.322 0.747 Age 0.018 1.018 0.005 1.008 1.029 3.491 0.000 *** Gendermale -0.058 0.944 0.159 0.691 1.289 -0.364 0.716 RaceWhite -1.297 0.273 0.403 0.124 0.602 -3.219 0.001 ** Stage2 0.270 1.310 0.219 0.853 2.012 1.232 0.218 Stage3 0.613 1.846 0.204 1.237 2.754 3.001 0.003 ** Stage4 1.350 3.856 0.352 1.935 7.684 3.835 0.000 *** Purity 1.029 2.797 0.341 1.434 5.456 3.017 0.003 ** Rsquare = 0.124 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.13e-08 Wald test p = 1.2e-08 Score (logrank) test p = 1.42e-09 ELOVL7 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.165 1.180000e+00 0.228 0.755 1.843 0.727 0.467 Age 0.013 1.013000e+00 0.016 0.982 1.046 0.812 0.417 Gendermale 0.252 1.286000e+00 0.439 0.544 3.043 0.573 0.567 RaceWhite -1.276 2.790000e-01 0.630 0.081 0.960 -2.025 0.043 * Stage2 17.674 4.739183e+07 6193.268 0.000 Inf 0.003 0.998 Stage3 18.227 8.237120e+07 6193.268 0.000 Inf 0.003 0.998 Stage4 20.080 5.256329e+08 6193.268 0.000 Inf 0.003 0.997 Purity 0.578 1.783000e+00 1.039 0.233 13.671 0.557 0.578 Rsquare = 0.151 (max possible = 8.69e-01 ) Likelihood ratio test p = 5.16e-02 Wald test p = 4.69e-02 Score (logrank) test p = 3.79e-03 ELOVL7 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -0.022 0.978 0.078 0.839 1.140 -0.285 0.776 Age 0.021 1.021 0.006 1.010 1.032 3.665 0.000 *** Gendermale -0.049 0.952 0.175 0.676 1.341 -0.281 0.778 RaceWhite -1.038 0.354 0.603 0.109 1.154 -1.722 0.085 · Stage2 0.158 1.171 0.231 0.744 1.842 0.683 0.494 Stage3 0.561 1.753 0.209 1.164 2.640 2.686 0.007 ** Stage4 1.133 3.104 0.399 1.418 6.790 2.835 0.005 ** Purity 1.138 3.120 0.371 1.509 6.453 3.070 0.002 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.06e-06 Wald test p = 1.62e-06 Score (logrank) test p = 6.21e-07 ELOVL7 in STAD (n=415): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.104 1.110 0.094 0.922 1.335 1.102 0.271 Age 0.026 1.027 0.010 1.006 1.047 2.572 0.010 * Gendermale 0.099 1.105 0.209 0.734 1.663 0.476 0.634 RaceBlack 0.210 1.234 0.450 0.511 2.980 0.468 0.640 RaceWhite 0.085 1.089 0.244 0.675 1.757 0.349 0.727 Stage2 0.475 1.608 0.390 0.748 3.456 1.217 0.224 Stage3 0.924 2.518 0.364 1.234 5.140 2.537 0.011 * Stage4 1.387 4.005 0.510 1.475 10.873 2.723 0.006 ** Purity -0.566 0.568 0.383 0.268 1.203 -1.478 0.140 Rsquare = 0.073 (max possible = 9.79e-01 ) Likelihood ratio test p = 8.9e-03 Wald test p = 1.24e-02 Score (logrank) test p = 1e-02 ELOVL7 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 -98.152 0.000000e+00 24666.946 0 Inf -0.004 0.997 Age 2.335 1.032600e+01 896.954 0 Inf 0.003 0.998 RaceBlack 18.842 1.523232e+08 1274250.732 0 Inf 0.000 1.000 RaceWhite -123.349 0.000000e+00 2056117.747 0 Inf 0.000 1.000 Stage2 48.775 1.523791e+21 17319.952 0 Inf 0.003 0.998 Stage3 -13.142 0.000000e+00 93530.970 0 Inf 0.000 1.000 Purity 212.815 2.657332e+92 107996.067 0 Inf 0.002 0.998 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 2.05e-03 ELOVL7 in THCA (n=509): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.499 1.647 0.335 0.854 3.176 1.488 0.137 Age 0.159 1.172 0.031 1.104 1.245 5.180 0.000 *** Gendermale 0.222 1.248 0.642 0.354 4.396 0.345 0.730 RaceBlack 17.130 27510130.576 5849.100 0.000 Inf 0.003 0.998 RaceWhite 16.754 18880684.533 5849.100 0.000 Inf 0.003 0.998 Stage2 0.217 1.242 1.122 0.138 11.191 0.193 0.847 Stage3 0.329 1.390 0.868 0.253 7.624 0.379 0.705 Stage4 1.656 5.237 0.976 0.774 35.448 1.697 0.090 · Purity 2.794 16.344 1.152 1.708 156.355 2.425 0.015 * Rsquare = 0.154 (max possible = 3.47e-01 ) Likelihood ratio test p = 9.12e-11 Wald test p = 4.07e-04 Score (logrank) test p = 1.22e-10 ELOVL7 in THYM (n=120): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.761 2.141 0.447 0.892 5.139 1.705 0.088 · Age 0.041 1.042 0.031 0.980 1.109 1.320 0.187 Gendermale -0.073 0.929 0.725 0.224 3.849 -0.101 0.919 RaceBlack -16.627 0.000 11954.890 0.000 Inf -0.001 0.999 RaceWhite 0.238 1.269 1.098 0.148 10.915 0.217 0.828 Purity 0.241 1.272 1.130 0.139 11.664 0.213 0.831 Rsquare = 0.066 (max possible = 4.51e-01 ) Likelihood ratio test p = 2.58e-01 Wald test p = 3.37e-01 Score (logrank) test p = 2.06e-01 ELOVL7 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.367 1.444 0.140 1.097 1.900 2.617 0.009 ** Age 0.042 1.043 0.016 1.011 1.077 2.628 0.009 ** RaceBlack -0.379 0.684 0.811 0.140 3.355 -0.468 0.640 RaceWhite -0.386 0.680 0.763 0.152 3.030 -0.506 0.613 Purity 0.444 1.559 0.664 0.424 5.729 0.669 0.504 Rsquare = 0.06 (max possible = 7.81e-01 ) Likelihood ratio test p = 3.77e-03 Wald test p = 3.16e-03 Score (logrank) test p = 2.75e-03 ELOVL7 in UCS (n=57): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.080 1.083 0.225 0.697 1.685 0.356 0.722 Age 0.042 1.043 0.025 0.993 1.094 1.691 0.091 · RaceBlack 17.642 45910858.789 6480.651 0.000 Inf 0.003 0.998 RaceWhite 17.884 58447038.244 6480.651 0.000 Inf 0.003 0.998 Purity -0.780 0.458 1.090 0.054 3.882 -0.716 0.474 Rsquare = 0.121 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.43e-01 Wald test p = 3.46e-01 Score (logrank) test p = 2.53e-01 ELOVL7 in UVM (n=80): Model: Surv(OS, EVENT) ~ `ELOVL7` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif ELOVL7 0.061 1.063 0.294 0.597 1.892 0.208 0.835 Age 0.040 1.041 0.019 1.002 1.081 2.070 0.038 * Gendermale 0.269 1.309 0.482 0.509 3.368 0.558 0.577 Stage3 0.275 1.316 0.502 0.492 3.524 0.546 0.585 Stage4 3.757 42.816 1.216 3.953 463.776 3.091 0.002 ** Purity 1.973 7.190 1.235 0.639 80.869 1.598 0.110 Rsquare = 0.253 (max possible = 8.72e-01 ) Likelihood ratio test p = 9.9e-04 Wald test p = 3.5e-03 Score (logrank) test p = 2.64e-09 FADS1 in ACC (n=79): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.305 1.357 0.169 0.975 1.888 1.809 0.070 · Age 0.012 1.012 0.015 0.984 1.042 0.836 0.403 Gendermale 0.480 1.616 0.420 0.710 3.679 1.143 0.253 RaceBlack -0.735 0.480 12475.182 0.000 Inf 0.000 1.000 RaceWhite 16.057 9404432.020 10650.786 0.000 Inf 0.002 0.999 Purity 2.421 11.255 2.244 0.138 915.589 1.079 0.281 Rsquare = 0.12 (max possible = 9.38e-01 ) Likelihood ratio test p = 2.26e-01 Wald test p = 4.46e-01 Score (logrank) test p = 3.05e-01 FADS1 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.142 1.152 0.065 1.014 1.310 2.170 0.030 * Age 0.033 1.033 0.009 1.016 1.051 3.831 0.000 *** Gendermale -0.158 0.854 0.178 0.602 1.212 -0.883 0.377 RaceBlack 0.476 1.610 0.459 0.655 3.959 1.038 0.299 RaceWhite -0.036 0.965 0.362 0.474 1.962 -0.100 0.921 Stage2 14.519 2021542.754 1868.945 0.000 Inf 0.008 0.994 Stage3 14.947 3101724.601 1868.945 0.000 Inf 0.008 0.994 Stage4 15.446 5105478.356 1868.945 0.000 Inf 0.008 0.993 Purity 0.080 1.083 0.341 0.555 2.114 0.234 0.815 Rsquare = 0.142 (max possible = 9.91e-01 ) Likelihood ratio test p = 2.65e-08 Wald test p = 2.23e-07 Score (logrank) test p = 5.7e-08 FADS1 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.030 1.031 0.079 0.883 1.204 0.381 0.703 Age 0.036 1.037 0.008 1.021 1.053 4.726 0.000 *** Gendermale 0.024 1.024 1.008 0.142 7.390 0.024 0.981 RaceBlack -0.020 0.980 0.621 0.290 3.312 -0.032 0.974 RaceWhite -0.243 0.784 0.598 0.243 2.532 -0.407 0.684 Stage2 0.405 1.500 0.304 0.827 2.720 1.334 0.182 Stage3 1.185 3.272 0.313 1.772 6.042 3.789 0.000 *** Stage4 2.485 12.004 0.396 5.525 26.083 6.277 0.000 *** Purity 0.495 1.640 0.424 0.715 3.763 1.167 0.243 Rsquare = 0.081 (max possible = 7.85e-01 ) Likelihood ratio test p = 2.33e-12 Wald test p = 6.29e-16 Score (logrank) test p = 7.49e-22 FADS1 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.097 1.102000e+00 0.272 0.647 1.878 0.358 0.720 Age 0.010 1.010000e+00 0.018 0.976 1.046 0.585 0.559 RaceBlack -0.855 4.250000e-01 1.121 0.047 3.825 -0.763 0.446 RaceWhite -1.189 3.050000e-01 1.124 0.034 2.756 -1.058 0.290 Stage2 18.715 1.341920e+08 6454.963 0.000 Inf 0.003 0.998 Stage3 20.211 5.993305e+08 6454.963 0.000 Inf 0.003 0.998 Stage4 21.486 2.143630e+09 6454.963 0.000 Inf 0.003 0.997 Purity 0.799 2.223000e+00 0.972 0.331 14.941 0.822 0.411 Rsquare = 0.157 (max possible = 7.18e-01 ) Likelihood ratio test p = 4.96e-04 Wald test p = 6.75e-03 Score (logrank) test p = 4.57e-06 FADS1 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.350 7.050000e-01 0.327 0.371 1.339 -1.069 0.285 Age 0.032 1.032000e+00 0.029 0.975 1.092 1.094 0.274 RaceBlack -2.651 7.100000e-02 1.774 0.002 2.286 -1.494 0.135 RaceWhite -1.720 1.790000e-01 1.458 0.010 3.120 -1.180 0.238 Stage2 16.986 2.381877e+07 9740.692 0.000 Inf 0.002 0.999 Stage3 19.279 2.359306e+08 9740.692 0.000 Inf 0.002 0.998 Stage4 NA NA 0.000 NA NA NA NA Purity 2.694 1.479100e+01 2.394 0.136 1613.454 1.125 0.260 Rsquare = 0.383 (max possible = 6.68e-01 ) Likelihood ratio test p = 1.8e-04 Wald test p = 2.34e-01 Score (logrank) test p = 5.89e-15 FADS1 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.164 1.179 0.146 0.886 1.567 1.129 0.259 Age 0.050 1.052 0.012 1.027 1.076 4.235 0.000 *** Gendermale -15.374 0.000 3450.717 0.000 Inf -0.004 0.996 RaceBlack -0.505 0.603 1.174 0.060 6.023 -0.431 0.667 RaceWhite 0.106 1.112 1.039 0.145 8.520 0.102 0.919 Stage2 0.292 1.339 0.376 0.641 2.799 0.776 0.438 Stage3 0.875 2.398 0.393 1.110 5.181 2.225 0.026 * Stage4 1.938 6.946 0.620 2.059 23.427 3.124 0.002 ** Purity 0.311 1.365 0.616 0.409 4.562 0.506 0.613 Rsquare = 0.072 (max possible = 6.81e-01 ) Likelihood ratio test p = 6.3e-05 Wald test p = 8.77e-06 Score (logrank) test p = 1.83e-07 FADS1 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.026 0.975 0.163 0.709 1.340 -0.159 0.874 Age 0.049 1.051 0.021 1.008 1.095 2.348 0.019 * Gendermale 1.018 2.767 1.134 0.300 25.535 0.898 0.369 RaceBlack 16.578 15845070.085 6474.827 0.000 Inf 0.003 0.998 RaceWhite 15.968 8604659.208 6474.827 0.000 Inf 0.002 0.998 Stage2 0.672 1.959 1.073 0.239 16.050 0.626 0.531 Stage3 1.610 5.003 1.062 0.624 40.101 1.516 0.129 Stage4 2.093 8.107 1.171 0.816 80.523 1.787 0.074 · Purity 1.093 2.984 1.363 0.206 43.166 0.802 0.423 Rsquare = 0.105 (max possible = 6.98e-01 ) Likelihood ratio test p = 4.17e-02 Wald test p = 7.2e-02 Score (logrank) test p = 2.44e-02 FADS1 in CESC (n=306): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.011 0.989 0.096 0.820 1.192 -0.120 0.905 Age 0.011 1.011 0.010 0.992 1.031 1.127 0.260 RaceBlack 1.042 2.836 1.069 0.349 23.033 0.975 0.329 RaceWhite 0.818 2.267 1.015 0.310 16.583 0.806 0.420 Purity 0.595 1.813 0.756 0.412 7.972 0.787 0.431 Rsquare = 0.014 (max possible = 8.91e-01 ) Likelihood ratio test p = 6.77e-01 Wald test p = 7.12e-01 Score (logrank) test p = 7.04e-01 FADS1 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.009 0.991 0.271 0.583 1.684 -0.034 0.973 Age 0.017 1.018 0.022 0.974 1.063 0.779 0.436 Gendermale 0.252 1.286 0.563 0.427 3.876 0.447 0.655 RaceBlack -0.358 0.699 1.512 0.036 13.532 -0.237 0.813 RaceWhite -1.078 0.340 0.902 0.058 1.994 -1.195 0.232 Stage2 0.658 1.931 0.671 0.519 7.193 0.981 0.326 Stage3 -15.542 0.000 6945.196 0.000 Inf -0.002 0.998 Stage4 0.822 2.275 0.670 0.612 8.450 1.227 0.220 Purity 2.035 7.653 1.556 0.362 161.668 1.308 0.191 Rsquare = 0.211 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.8e-01 Wald test p = 6.51e-01 Score (logrank) test p = 4.87e-01 FADS1 in COAD (n=458): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.192 1.211 0.115 0.967 1.518 1.664 0.096 · Age 0.028 1.028 0.012 1.005 1.052 2.388 0.017 * Gendermale 0.262 1.299 0.270 0.765 2.206 0.968 0.333 RaceBlack -0.337 0.714 0.827 0.141 3.611 -0.407 0.684 RaceWhite -0.417 0.659 0.775 0.144 3.012 -0.538 0.591 Stage2 0.197 1.218 0.562 0.405 3.664 0.350 0.726 Stage3 0.761 2.140 0.552 0.726 6.309 1.379 0.168 Stage4 1.820 6.174 0.555 2.081 18.312 3.281 0.001 ** Purity -0.075 0.928 0.610 0.281 3.066 -0.123 0.902 Rsquare = 0.119 (max possible = 9.04e-01 ) Likelihood ratio test p = 1.54e-04 Wald test p = 5.58e-05 Score (logrank) test p = 8.31e-06 FADS1 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.784 2.190 0.705 0.550 8.721 1.112 0.266 Age -0.012 0.989 0.046 0.904 1.081 -0.252 0.801 Gendermale 0.665 1.945 1.057 0.245 15.432 0.630 0.529 RaceBlack 0.520 1.682 1.673 0.063 44.656 0.311 0.756 RaceWhite -3.082 0.046 1.622 0.002 1.101 -1.900 0.057 · Purity -1.587 0.204 2.134 0.003 13.402 -0.744 0.457 Rsquare = 0.157 (max possible = 5.58e-01 ) Likelihood ratio test p = 3.21e-01 Wald test p = 4.7e-01 Score (logrank) test p = 2.78e-01 FADS1 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.145 1.156 0.117 0.918 1.455 1.233 0.217 Age 0.014 1.014 0.014 0.986 1.043 0.950 0.342 Gendermale 0.594 1.811 0.545 0.623 5.270 1.090 0.276 RaceBlack 0.366 1.442 1.068 0.178 11.692 0.343 0.732 RaceWhite 0.015 1.015 0.453 0.418 2.466 0.033 0.973 Stage2 0.505 1.657 0.669 0.447 6.144 0.755 0.450 Stage3 1.361 3.900 0.674 1.040 14.624 2.018 0.044 * Stage4 2.637 13.972 0.793 2.951 66.157 3.324 0.001 ** Purity 0.201 1.222 0.767 0.272 5.495 0.261 0.794 Rsquare = 0.15 (max possible = 9.32e-01 ) Likelihood ratio test p = 6.72e-03 Wald test p = 3.5e-03 Score (logrank) test p = 2.63e-04 FADS1 in GBM (n=153): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.108 0.898 0.149 0.671 1.203 -0.722 0.471 Age 0.030 1.030 0.008 1.014 1.048 3.569 0.000 *** Gendermale -0.109 0.897 0.214 0.590 1.364 -0.510 0.610 RaceBlack 0.521 1.684 0.726 0.406 6.986 0.718 0.473 RaceWhite -0.234 0.791 0.614 0.238 2.634 -0.382 0.703 Purity -0.942 0.390 0.569 0.128 1.188 -1.657 0.098 · Rsquare = 0.132 (max possible = 9.98e-01 ) Likelihood ratio test p = 3.89e-03 Wald test p = 6.5e-03 Score (logrank) test p = 5.43e-03 FADS1 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.046 1.047 0.065 0.922 1.188 0.702 0.483 Age 0.022 1.022 0.008 1.007 1.038 2.897 0.004 ** Gendermale -0.269 0.764 0.174 0.543 1.074 -1.547 0.122 RaceBlack 0.069 1.071 0.567 0.353 3.251 0.121 0.904 RaceWhite -0.287 0.751 0.514 0.274 2.056 -0.558 0.577 Stage2 0.620 1.860 0.544 0.641 5.397 1.142 0.254 Stage3 0.855 2.351 0.537 0.821 6.728 1.593 0.111 Stage4 1.248 3.484 0.510 1.283 9.466 2.448 0.014 * Purity -0.085 0.918 0.369 0.446 1.892 -0.232 0.817 Rsquare = 0.07 (max possible = 9.89e-01 ) Likelihood ratio test p = 4.35e-04 Wald test p = 1.12e-03 Score (logrank) test p = 8.28e-04 FADS1 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.157 1.170000e+00 0.210 0.775 1.765 0.746 0.456 Age 0.012 1.012000e+00 0.024 0.965 1.062 0.502 0.615 Gendermale -0.313 7.310000e-01 0.569 0.240 2.229 -0.551 0.582 RaceBlack 18.926 1.657336e+08 12094.265 0.000 Inf 0.002 0.999 RaceWhite 18.209 8.091454e+07 12094.265 0.000 Inf 0.002 0.999 Stage2 17.552 4.193575e+07 5369.533 0.000 Inf 0.003 0.997 Stage3 16.473 1.426123e+07 5369.533 0.000 Inf 0.003 0.998 Stage4 17.530 4.101791e+07 5369.533 0.000 Inf 0.003 0.997 Purity -1.756 1.730000e-01 1.109 0.020 1.520 -1.583 0.113 Rsquare = 0.095 (max possible = 9.17e-01 ) Likelihood ratio test p = 6.9e-01 Wald test p = 9.39e-01 Score (logrank) test p = 8.35e-01 FADS1 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.039 1.039 0.070 0.906 1.192 0.553 0.580 Age 0.027 1.027 0.008 1.010 1.044 3.162 0.002 ** Gendermale -0.298 0.742 0.184 0.517 1.065 -1.620 0.105 RaceBlack -0.076 0.927 0.574 0.301 2.855 -0.132 0.895 RaceWhite -0.435 0.648 0.517 0.235 1.784 -0.840 0.401 Stage2 0.370 1.447 0.554 0.489 4.283 0.668 0.504 Stage3 0.733 2.082 0.541 0.721 6.011 1.356 0.175 Stage4 1.139 3.123 0.512 1.145 8.522 2.224 0.026 * Purity 0.170 1.185 0.407 0.534 2.631 0.418 0.676 Rsquare = 0.086 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.02e-04 Wald test p = 8.06e-04 Score (logrank) test p = 6.14e-04 FADS1 in KICH (n=66): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p FADS1 0.762 2.142000e+00 0.316 1.152 3.983000e+00 2.409 0.016 Age 0.093 1.098000e+00 0.028 1.039 1.160000e+00 3.318 0.001 Gendermale -1.149 3.170000e-01 0.741 0.074 1.354000e+00 -1.551 0.121 RaceBlack -16.065 0.000000e+00 5545.175 0.000 Inf -0.003 0.998 RaceWhite -1.694 1.840000e-01 1.184 0.018 1.870000e+00 -1.431 0.152 Stage2 15.140 3.760535e+06 0.855 703759.170 2.009441e+07 17.707 0.000 Stage3 17.240 3.071281e+07 0.783 6625472.119 1.423713e+08 22.031 0.000 Stage4 18.573 1.164100e+08 0.929 18846804.718 7.190234e+08 19.992 0.000 Purity 1.374 3.953000e+00 3.850 0.002 7.478556e+03 0.357 0.721 signif FADS1 * Age ** Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.375 (max possible = 6.71e-01 ) Likelihood ratio test p = 5.01e-04 Wald test p = 5.93e-257 Score (logrank) test p = 4.23e-09 FADS1 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.178 1.195 0.135 0.917 1.558 1.319 0.187 Age 0.034 1.035 0.008 1.018 1.052 4.056 0.000 *** Gendermale -0.090 0.914 0.184 0.638 1.310 -0.489 0.625 RaceBlack 0.280 1.323 1.058 0.166 10.527 0.265 0.791 RaceWhite 0.179 1.195 1.015 0.164 8.734 0.176 0.860 Stage2 0.239 1.270 0.345 0.646 2.495 0.693 0.488 Stage3 0.856 2.354 0.232 1.493 3.713 3.685 0.000 *** Stage4 1.731 5.645 0.217 3.692 8.633 7.986 0.000 *** Purity 0.038 1.038 0.370 0.503 2.143 0.102 0.919 Rsquare = 0.177 (max possible = 9.65e-01 ) Likelihood ratio test p = 4.59e-15 Wald test p = 5.29e-15 Score (logrank) test p = 2.8e-18 FADS1 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.036 0.965 0.229 0.616 1.512 -0.156 0.876 Age 0.007 1.007 0.016 0.976 1.038 0.433 0.665 Gendermale -0.504 0.604 0.387 0.283 1.290 -1.302 0.193 RaceBlack -2.010 0.134 1.193 0.013 1.388 -1.685 0.092 · RaceWhite -2.050 0.129 1.172 0.013 1.281 -1.748 0.080 · Stage2 -0.406 0.666 1.055 0.084 5.264 -0.385 0.700 Stage3 1.654 5.230 0.440 2.207 12.394 3.758 0.000 *** Stage4 2.699 14.868 0.508 5.493 40.239 5.313 0.000 *** Purity -0.282 0.754 0.753 0.172 3.301 -0.374 0.708 Rsquare = 0.163 (max possible = 7.58e-01 ) Likelihood ratio test p = 1.15e-05 Wald test p = 3.53e-06 Score (logrank) test p = 6.59e-10 FADS1 in LAML (n=173): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.243 1.275 0.139 0.971 1.673 1.748 0.081 · Age 0.036 1.036 0.008 1.020 1.053 4.358 0.000 *** Gendermale -0.235 0.790 0.220 0.513 1.217 -1.069 0.285 RaceBlack -0.381 0.683 1.105 0.078 5.956 -0.345 0.730 RaceWhite -0.773 0.462 1.019 0.063 3.402 -0.758 0.448 Rsquare = 0.174 (max possible = 9.96e-01 ) Likelihood ratio test p = 2.95e-05 Wald test p = 1.23e-04 Score (logrank) test p = 7.99e-05 FADS1 in LGG (n=516): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.564 0.569 0.156 0.419 0.773 -3.613 0.000 *** Age 0.061 1.062 0.008 1.047 1.079 7.913 0.000 *** Gendermale 0.083 1.087 0.195 0.742 1.592 0.427 0.670 RaceBlack 15.890 7957635.615 1991.347 0.000 Inf 0.008 0.994 RaceWhite 15.751 6925529.928 1991.347 0.000 Inf 0.008 0.994 Purity -0.701 0.496 0.406 0.224 1.100 -1.726 0.084 · Rsquare = 0.159 (max possible = 9.07e-01 ) Likelihood ratio test p = 3.34e-15 Wald test p = 7.72e-15 Score (logrank) test p = 4.41e-16 FADS1 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.049 1.051 0.063 0.929 1.188 0.788 0.431 Age 0.011 1.011 0.008 0.995 1.027 1.356 0.175 Gendermale -0.124 0.883 0.227 0.566 1.378 -0.547 0.584 RaceBlack 0.845 2.328 0.492 0.888 6.107 1.718 0.086 · RaceWhite -0.013 0.987 0.238 0.619 1.574 -0.054 0.957 Stage2 0.333 1.395 0.262 0.835 2.333 1.271 0.204 Stage3 0.946 2.576 0.234 1.627 4.079 4.035 0.000 *** Stage4 1.603 4.966 0.619 1.476 16.705 2.589 0.010 * Purity 0.555 1.742 0.454 0.715 4.243 1.222 0.222 Rsquare = 0.086 (max possible = 9.66e-01 ) Likelihood ratio test p = 9.49e-04 Wald test p = 5.75e-04 Score (logrank) test p = 2.21e-04 FADS1 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.064 1.066 0.082 0.908 1.251 0.781 0.435 Age 0.008 1.008 0.009 0.990 1.026 0.861 0.389 Gendermale 0.012 1.012 0.169 0.727 1.409 0.070 0.944 RaceBlack 16.081 9637019.119 1886.979 0.000 Inf 0.009 0.993 RaceWhite 16.264 11576410.186 1886.979 0.000 Inf 0.009 0.993 Stage2 0.858 2.359 0.201 1.590 3.499 4.266 0.000 *** Stage3 0.995 2.704 0.219 1.760 4.156 4.537 0.000 *** Stage4 0.994 2.701 0.334 1.404 5.196 2.976 0.003 ** Purity 0.599 1.820 0.344 0.928 3.572 1.741 0.082 · Rsquare = 0.098 (max possible = 9.74e-01 ) Likelihood ratio test p = 1.85e-06 Wald test p = 2.61e-05 Score (logrank) test p = 2.95e-06 FADS1 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.084 1.087 0.072 0.945 1.251 1.168 0.243 Age 0.016 1.016 0.009 0.998 1.035 1.743 0.081 · Gendermale 0.403 1.497 0.195 1.021 2.194 2.068 0.039 * RaceBlack -0.032 0.968 0.606 0.295 3.178 -0.053 0.958 RaceWhite -0.560 0.571 0.562 0.190 1.718 -0.997 0.319 Stage2 0.224 1.251 0.187 0.867 1.806 1.197 0.231 Stage3 0.587 1.798 0.215 1.180 2.739 2.731 0.006 ** Stage4 0.822 2.275 0.793 0.481 10.773 1.036 0.300 Purity -0.381 0.683 0.366 0.333 1.401 -1.040 0.298 Rsquare = 0.054 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.51e-02 Wald test p = 1.13e-02 Score (logrank) test p = 9.6e-03 FADS1 in MESO (n=87): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.432 1.540 0.122 1.212 1.956 3.538 0.000 *** Age 0.014 1.014 0.016 0.983 1.046 0.880 0.379 Gendermale -0.224 0.799 0.335 0.415 1.540 -0.670 0.503 RaceBlack -0.767 0.464 1.544 0.022 9.579 -0.497 0.619 RaceWhite -0.895 0.408 1.054 0.052 3.221 -0.850 0.395 Stage2 -0.212 0.809 0.451 0.334 1.959 -0.470 0.638 Stage3 -0.109 0.897 0.406 0.405 1.988 -0.268 0.789 Stage4 -0.177 0.838 0.462 0.339 2.071 -0.383 0.702 Purity -0.664 0.515 0.548 0.176 1.506 -1.212 0.225 Rsquare = 0.195 (max possible = 9.98e-01 ) Likelihood ratio test p = 3.05e-02 Wald test p = 4.35e-02 Score (logrank) test p = 3.46e-02 FADS1 in OV (n=303): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.087 0.917 0.077 0.789 1.065 -1.134 0.257 Age 0.038 1.038 0.008 1.022 1.055 4.574 0.000 *** RaceBlack -0.044 0.957 0.576 0.309 2.963 -0.076 0.940 RaceWhite -0.146 0.864 0.515 0.315 2.370 -0.284 0.777 Purity -0.645 0.525 0.673 0.140 1.962 -0.958 0.338 Rsquare = 0.086 (max possible = 9.97e-01 ) Likelihood ratio test p = 6.61e-04 Wald test p = 5.69e-04 Score (logrank) test p = 4.74e-04 FADS1 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.008 0.992 0.147 0.744 1.324 -0.052 0.958 Age 0.022 1.022 0.011 1.000 1.044 1.978 0.048 * Gendermale -0.217 0.805 0.221 0.522 1.241 -0.982 0.326 RaceBlack -0.016 0.984 0.749 0.227 4.269 -0.021 0.983 RaceWhite 0.363 1.437 0.481 0.560 3.688 0.754 0.451 Stage2 0.620 1.859 0.444 0.779 4.436 1.396 0.163 Stage3 -0.245 0.783 1.101 0.091 6.768 -0.223 0.824 Stage4 0.239 1.270 0.825 0.252 6.403 0.290 0.772 Purity -0.678 0.507 0.434 0.217 1.188 -1.563 0.118 Rsquare = 0.088 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.33e-02 Wald test p = 1.2e-01 Score (logrank) test p = 1.15e-01 FADS1 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 1.159 3.187 0.704 0.803 12.653 1.647 0.099 · Age 0.039 1.040 0.028 0.985 1.098 1.427 0.154 Gendermale 1.145 3.142 0.874 0.566 17.437 1.310 0.190 RaceBlack -1.097 0.334 31200.139 0.000 Inf 0.000 1.000 RaceWhite 18.227 82395309.608 27142.170 0.000 Inf 0.001 0.999 Purity 6.272 529.782 3.543 0.511 549072.074 1.771 0.077 · Rsquare = 0.07 (max possible = 3.07e-01 ) Likelihood ratio test p = 6.36e-02 Wald test p = 2.74e-01 Score (logrank) test p = 1.89e-01 FADS1 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.220 1.246 0.306 0.684 2.269 0.719 0.472 Age 0.011 1.011 0.057 0.905 1.130 0.197 0.844 RaceBlack 15.134 3738582.676 6769.154 0.000 Inf 0.002 0.998 RaceWhite 16.323 12275306.230 6769.153 0.000 Inf 0.002 0.998 Purity 1.045 2.845 1.379 0.190 42.484 0.758 0.449 Rsquare = 0.008 (max possible = 1.83e-01 ) Likelihood ratio test p = 6.64e-01 Wald test p = 7.8e-01 Score (logrank) test p = 7.15e-01 FADS1 in READ (n=166): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.387 1.473 0.282 0.847 2.562 1.372 0.170 Age 0.133 1.143 0.051 1.033 1.264 2.597 0.009 ** Gendermale -0.248 0.780 0.728 0.187 3.248 -0.341 0.733 RaceBlack 12.691 324863.441 10725.997 0.000 Inf 0.001 0.999 RaceWhite 11.526 101338.679 10725.997 0.000 Inf 0.001 0.999 Stage2 -1.747 0.174 1.274 0.014 2.119 -1.371 0.170 Stage3 -0.328 0.720 0.957 0.110 4.701 -0.343 0.732 Stage4 -0.189 0.828 0.972 0.123 5.562 -0.194 0.846 Purity 0.417 1.517 1.378 0.102 22.573 0.303 0.762 Rsquare = 0.23 (max possible = 7.22e-01 ) Likelihood ratio test p = 1.9e-02 Wald test p = 1.73e-01 Score (logrank) test p = 2.94e-02 FADS1 in SARC (n=260): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.003 0.997 0.104 0.813 1.223 -0.028 0.977 Age 0.023 1.023 0.008 1.006 1.040 2.716 0.007 ** Gendermale -0.011 0.989 0.227 0.634 1.544 -0.049 0.961 RaceBlack -0.123 0.884 1.087 0.105 7.446 -0.113 0.910 RaceWhite -0.464 0.629 1.024 0.085 4.678 -0.453 0.651 Purity 0.952 2.591 0.602 0.797 8.423 1.583 0.113 Rsquare = 0.043 (max possible = 9.75e-01 ) Likelihood ratio test p = 1.2e-01 Wald test p = 1.6e-01 Score (logrank) test p = 1.6e-01 FADS1 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.072 0.931 0.076 0.802 1.081 -0.942 0.346 Age 0.018 1.018 0.005 1.008 1.029 3.472 0.001 ** Gendermale -0.049 0.953 0.157 0.700 1.297 -0.309 0.758 RaceWhite -1.268 0.281 0.402 0.128 0.619 -3.153 0.002 ** Stage2 0.286 1.331 0.219 0.866 2.046 1.306 0.191 Stage3 0.615 1.850 0.204 1.239 2.761 3.008 0.003 ** Stage4 1.335 3.800 0.352 1.907 7.573 3.794 0.000 *** Purity 1.014 2.757 0.339 1.418 5.360 2.989 0.003 ** Rsquare = 0.125 (max possible = 9.92e-01 ) Likelihood ratio test p = 1.52e-08 Wald test p = 7.44e-09 Score (logrank) test p = 9.01e-10 FADS1 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.059 1.061000e+00 0.212 0.700 1.609 0.279 0.780 Age 0.012 1.012000e+00 0.016 0.981 1.044 0.744 0.457 Gendermale 0.215 1.240000e+00 0.435 0.529 2.907 0.495 0.620 RaceWhite -1.247 2.870000e-01 0.624 0.085 0.976 -1.998 0.046 * Stage2 17.439 3.746310e+07 6204.322 0.000 Inf 0.003 0.998 Stage3 17.962 6.323292e+07 6204.322 0.000 Inf 0.003 0.998 Stage4 20.063 5.165687e+08 6204.322 0.000 Inf 0.003 0.997 Purity 0.168 1.183000e+00 1.015 0.162 8.654 0.166 0.868 Rsquare = 0.147 (max possible = 8.69e-01 ) Likelihood ratio test p = 5.98e-02 Wald test p = 5.4e-02 Score (logrank) test p = 4.41e-03 FADS1 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.058 0.944 0.084 0.800 1.113 -0.689 0.491 Age 0.020 1.021 0.006 1.009 1.032 3.597 0.000 *** Gendermale -0.058 0.944 0.172 0.673 1.323 -0.335 0.737 RaceWhite -1.029 0.357 0.601 0.110 1.160 -1.712 0.087 · Stage2 0.162 1.176 0.231 0.747 1.851 0.702 0.483 Stage3 0.568 1.765 0.209 1.171 2.660 2.713 0.007 ** Stage4 1.117 3.055 0.400 1.394 6.692 2.790 0.005 ** Purity 1.132 3.101 0.369 1.503 6.396 3.063 0.002 ** Rsquare = 0.135 (max possible = 9.95e-01 ) Likelihood ratio test p = 9e-07 Wald test p = 1.28e-06 Score (logrank) test p = 5.05e-07 FADS1 in STAD (n=415): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.115 1.122 0.090 0.941 1.338 1.278 0.201 Age 0.026 1.027 0.010 1.006 1.048 2.567 0.010 * Gendermale 0.112 1.119 0.208 0.745 1.680 0.540 0.589 RaceBlack 0.223 1.250 0.449 0.518 3.016 0.497 0.619 RaceWhite 0.079 1.083 0.244 0.671 1.747 0.325 0.745 Stage2 0.494 1.640 0.391 0.762 3.528 1.264 0.206 Stage3 0.898 2.455 0.364 1.204 5.010 2.469 0.014 * Stage4 1.268 3.555 0.505 1.320 9.571 2.510 0.012 * Purity -0.559 0.572 0.380 0.272 1.204 -1.472 0.141 Rsquare = 0.075 (max possible = 9.79e-01 ) Likelihood ratio test p = 7.74e-03 Wald test p = 1.12e-02 Score (logrank) test p = 8.8e-03 FADS1 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 1.870 6.490 18425.729 0 Inf 0.000 1.000 Age -1.765 0.171 1691.674 0 Inf -0.001 0.999 RaceBlack 9.424 12385.042 19261709.247 0 Inf 0.000 1.000 RaceWhite -32.246 0.000 19138885.391 0 Inf 0.000 1.000 Stage2 -0.496 0.609 40950.913 0 Inf 0.000 1.000 Stage3 13.759 945148.792 127386.996 0 Inf 0.000 1.000 Purity 11.358 85610.327 207744.347 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.27e-03 FADS1 in THCA (n=509): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 2.419 11.235 0.593 3.511 35.954 4.076 0.000 *** Age 0.187 1.206 0.038 1.119 1.300 4.877 0.000 *** Gendermale -0.689 0.502 0.679 0.133 1.901 -1.014 0.310 RaceBlack 14.688 2393125.333 8066.098 0.000 Inf 0.002 0.999 RaceWhite 15.203 4005712.781 8066.098 0.000 Inf 0.002 0.998 Stage2 0.252 1.287 1.217 0.118 13.979 0.207 0.836 Stage3 -0.347 0.707 0.889 0.124 4.036 -0.390 0.697 Stage4 1.926 6.864 1.024 0.922 51.070 1.881 0.060 · Purity 3.798 44.631 1.351 3.157 631.006 2.811 0.005 ** Rsquare = 0.19 (max possible = 3.47e-01 ) Likelihood ratio test p = 3.38e-14 Wald test p = 2.31e-04 Score (logrank) test p = 1.32e-13 FADS1 in THYM (n=120): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.676 0.509 0.419 0.224 1.156 -1.614 0.106 Age 0.047 1.048 0.032 0.984 1.116 1.462 0.144 Gendermale -0.047 0.954 0.788 0.204 4.468 -0.059 0.953 RaceBlack -16.145 0.000 10481.252 0.000 Inf -0.002 0.999 RaceWhite 0.753 2.122 1.146 0.225 20.049 0.657 0.511 Purity 0.208 1.232 1.142 0.131 11.547 0.183 0.855 Rsquare = 0.066 (max possible = 4.51e-01 ) Likelihood ratio test p = 2.56e-01 Wald test p = 3.59e-01 Score (logrank) test p = 2.39e-01 FADS1 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 0.269 1.308 0.171 0.936 1.828 1.573 0.116 Age 0.051 1.053 0.016 1.021 1.085 3.300 0.001 ** RaceBlack -0.716 0.489 0.820 0.098 2.437 -0.873 0.383 RaceWhite -0.806 0.447 0.770 0.099 2.022 -1.046 0.296 Purity 0.348 1.416 0.662 0.387 5.182 0.525 0.599 Rsquare = 0.047 (max possible = 7.81e-01 ) Likelihood ratio test p = 1.87e-02 Wald test p = 1.95e-02 Score (logrank) test p = 1.85e-02 FADS1 in UCS (n=57): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 -0.125 0.882 0.195 0.602 1.292 -0.644 0.520 Age 0.044 1.045 0.024 0.997 1.096 1.827 0.068 · RaceBlack 17.476 38895230.548 6502.846 0.000 Inf 0.003 0.998 RaceWhite 17.720 49648980.156 6502.846 0.000 Inf 0.003 0.998 Purity -0.983 0.374 1.070 0.046 3.048 -0.919 0.358 Rsquare = 0.126 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.22e-01 Wald test p = 3.19e-01 Score (logrank) test p = 2.33e-01 FADS1 in UVM (n=80): Model: Surv(OS, EVENT) ~ `FADS1` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS1 1.266 3.547 0.359 1.754 7.173 3.524 0.000 *** Age 0.037 1.038 0.021 0.996 1.082 1.752 0.080 · Gendermale 0.660 1.935 0.508 0.716 5.233 1.301 0.193 Stage3 0.086 1.090 0.530 0.386 3.079 0.163 0.871 Stage4 4.137 62.601 1.243 5.481 714.939 3.329 0.001 ** Purity 1.310 3.706 1.349 0.264 52.114 0.971 0.331 Rsquare = 0.408 (max possible = 8.72e-01 ) Likelihood ratio test p = 3.92e-07 Wald test p = 3.03e-04 Score (logrank) test p = 1.83e-11 FADS2 in ACC (n=79): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.006 1.006 0.174 0.716 1.415 0.037 0.971 Age 0.004 1.004 0.014 0.977 1.032 0.310 0.756 Gendermale 0.370 1.448 0.421 0.634 3.305 0.878 0.380 RaceBlack 0.048 1.050 11955.055 0.000 Inf 0.000 1.000 RaceWhite 16.879 21399680.450 10179.961 0.000 Inf 0.002 0.999 Purity 2.988 19.851 2.395 0.181 2171.410 1.248 0.212 Rsquare = 0.066 (max possible = 9.38e-01 ) Likelihood ratio test p = 6.24e-01 Wald test p = 9.07e-01 Score (logrank) test p = 7.69e-01 FADS2 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.039 1.040 0.047 0.950 1.140 0.848 0.396 Age 0.033 1.033 0.009 1.016 1.051 3.774 0.000 *** Gendermale -0.169 0.845 0.179 0.595 1.198 -0.946 0.344 RaceBlack 0.654 1.924 0.451 0.795 4.657 1.451 0.147 RaceWhite 0.094 1.099 0.355 0.548 2.205 0.265 0.791 Stage2 14.470 1923677.569 1862.629 0.000 Inf 0.008 0.994 Stage3 14.895 2943360.813 1862.629 0.000 Inf 0.008 0.994 Stage4 15.415 4951625.912 1862.629 0.000 Inf 0.008 0.993 Purity 0.132 1.141 0.338 0.588 2.215 0.390 0.697 Rsquare = 0.132 (max possible = 9.91e-01 ) Likelihood ratio test p = 1.48e-07 Wald test p = 8.74e-07 Score (logrank) test p = 2.5e-07 FADS2 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.024 1.024 0.051 0.928 1.131 0.478 0.632 Age 0.036 1.037 0.008 1.022 1.053 4.756 0.000 *** Gendermale 0.037 1.038 1.007 0.144 7.470 0.037 0.971 RaceBlack -0.022 0.978 0.621 0.290 3.303 -0.035 0.972 RaceWhite -0.245 0.783 0.598 0.243 2.526 -0.409 0.682 Stage2 0.414 1.512 0.304 0.833 2.744 1.360 0.174 Stage3 1.192 3.294 0.313 1.784 6.083 3.810 0.000 *** Stage4 2.483 11.971 0.394 5.529 25.919 6.299 0.000 *** Purity 0.495 1.640 0.424 0.715 3.762 1.168 0.243 Rsquare = 0.081 (max possible = 7.85e-01 ) Likelihood ratio test p = 2.24e-12 Wald test p = 5.39e-16 Score (logrank) test p = 6.38e-22 FADS2 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.190 8.270000e-01 0.193 0.566 1.207 -0.984 0.325 Age 0.012 1.012000e+00 0.018 0.978 1.048 0.684 0.494 RaceBlack -1.187 3.050000e-01 1.139 0.033 2.845 -1.042 0.297 RaceWhite -1.464 2.310000e-01 1.133 0.025 2.132 -1.292 0.196 Stage2 18.596 1.191459e+08 6477.461 0.000 Inf 0.003 0.998 Stage3 19.853 4.186956e+08 6477.461 0.000 Inf 0.003 0.998 Stage4 21.369 1.907375e+09 6477.461 0.000 Inf 0.003 0.997 Purity 0.795 2.214000e+00 0.928 0.359 13.663 0.856 0.392 Rsquare = 0.162 (max possible = 7.18e-01 ) Likelihood ratio test p = 3.54e-04 Wald test p = 6.52e-03 Score (logrank) test p = 3.66e-06 FADS2 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.200 8.190000e-01 0.177 0.579 1.158 -1.130 0.258 Age 0.029 1.029000e+00 0.030 0.971 1.091 0.965 0.334 RaceBlack -3.283 3.800000e-02 1.790 0.001 1.253 -1.834 0.067 · RaceWhite -2.057 1.280000e-01 1.500 0.007 2.419 -1.371 0.170 Stage2 17.773 5.230580e+07 15750.604 0.000 Inf 0.001 0.999 Stage3 19.805 3.991310e+08 15750.604 0.000 Inf 0.001 0.999 Stage4 52.862 9.069918e+22 1819181.331 0.000 Inf 0.000 1.000 Purity 2.511 1.231700e+01 2.461 0.099 1533.009 1.020 0.308 Rsquare = 0.384 (max possible = 6.68e-01 ) Likelihood ratio test p = 3.71e-04 Wald test p = 1e+00 Score (logrank) test p = 2.17e-14 FADS2 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.024 1.024 0.083 0.870 1.206 0.287 0.774 Age 0.049 1.050 0.012 1.026 1.075 4.101 0.000 *** Gendermale -15.382 0.000 3458.675 0.000 Inf -0.004 0.996 RaceBlack -0.450 0.638 1.175 0.064 6.375 -0.383 0.702 RaceWhite 0.217 1.243 1.036 0.163 9.474 0.210 0.834 Stage2 0.339 1.404 0.377 0.670 2.939 0.900 0.368 Stage3 0.872 2.391 0.395 1.103 5.184 2.208 0.027 * Stage4 2.100 8.162 0.619 2.426 27.459 3.392 0.001 ** Purity 0.284 1.329 0.620 0.394 4.481 0.458 0.647 Rsquare = 0.07 (max possible = 6.81e-01 ) Likelihood ratio test p = 1.01e-04 Wald test p = 1.77e-05 Score (logrank) test p = 3.45e-07 FADS2 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.024 1.024 0.101 0.840 1.249 0.237 0.812 Age 0.051 1.052 0.021 1.010 1.096 2.420 0.016 * Gendermale 0.968 2.634 1.105 0.302 22.983 0.876 0.381 RaceBlack 16.525 15027827.817 6392.428 0.000 Inf 0.003 0.998 RaceWhite 15.896 8011611.594 6392.428 0.000 Inf 0.002 0.998 Stage2 0.695 2.003 1.074 0.244 16.430 0.647 0.517 Stage3 1.594 4.924 1.061 0.616 39.361 1.503 0.133 Stage4 2.077 7.977 1.171 0.804 79.105 1.774 0.076 · Purity 1.029 2.798 1.311 0.214 36.516 0.785 0.432 Rsquare = 0.106 (max possible = 6.98e-01 ) Likelihood ratio test p = 4.13e-02 Wald test p = 6.99e-02 Score (logrank) test p = 2.37e-02 FADS2 in CESC (n=306): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.008 0.992 0.081 0.847 1.162 -0.097 0.923 Age 0.011 1.011 0.010 0.992 1.031 1.142 0.253 RaceBlack 1.041 2.831 1.070 0.348 23.049 0.973 0.331 RaceWhite 0.816 2.262 1.016 0.309 16.583 0.803 0.422 Purity 0.588 1.800 0.749 0.415 7.819 0.785 0.433 Rsquare = 0.014 (max possible = 8.91e-01 ) Likelihood ratio test p = 6.78e-01 Wald test p = 7.13e-01 Score (logrank) test p = 7.05e-01 FADS2 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.120 0.887 0.274 0.518 1.517 -0.438 0.661 Age 0.015 1.015 0.023 0.970 1.062 0.644 0.520 Gendermale 0.274 1.315 0.565 0.434 3.981 0.484 0.628 RaceBlack -0.644 0.525 1.641 0.021 13.101 -0.392 0.695 RaceWhite -1.275 0.279 1.019 0.038 2.059 -1.251 0.211 Stage2 0.721 2.057 0.679 0.544 7.782 1.063 0.288 Stage3 -15.446 0.000 6992.658 0.000 Inf -0.002 0.998 Stage4 0.886 2.426 0.681 0.638 9.223 1.301 0.193 Purity 2.115 8.288 1.577 0.377 182.181 1.341 0.180 Rsquare = 0.216 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.62e-01 Wald test p = 6.36e-01 Score (logrank) test p = 4.63e-01 FADS2 in COAD (n=458): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.003 1.003 0.092 0.838 1.200 0.030 0.976 Age 0.024 1.024 0.012 1.001 1.048 2.052 0.040 * Gendermale 0.214 1.239 0.271 0.729 2.107 0.792 0.428 RaceBlack -0.413 0.661 0.828 0.130 3.354 -0.499 0.618 RaceWhite -0.444 0.642 0.775 0.140 2.931 -0.572 0.567 Stage2 0.210 1.234 0.562 0.410 3.714 0.374 0.708 Stage3 0.805 2.236 0.552 0.759 6.592 1.459 0.145 Stage4 1.885 6.583 0.554 2.222 19.505 3.401 0.001 ** Purity -0.219 0.803 0.608 0.244 2.643 -0.361 0.718 Rsquare = 0.109 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.64e-04 Wald test p = 1.61e-04 Score (logrank) test p = 2.37e-05 FADS2 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.165 0.848 0.723 0.205 3.498 -0.229 0.819 Age -0.003 0.997 0.041 0.920 1.081 -0.064 0.949 Gendermale 0.624 1.866 1.062 0.233 14.970 0.587 0.557 RaceBlack 0.268 1.308 1.651 0.051 33.251 0.163 0.871 RaceWhite -2.013 0.134 1.360 0.009 1.921 -1.480 0.139 Purity -2.266 0.104 2.334 0.001 10.065 -0.971 0.332 Rsquare = 0.132 (max possible = 5.58e-01 ) Likelihood ratio test p = 4.46e-01 Wald test p = 5.99e-01 Score (logrank) test p = 3.35e-01 FADS2 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.002 0.998 0.105 0.812 1.227 -0.020 0.984 Age 0.009 1.010 0.014 0.982 1.038 0.674 0.501 Gendermale 0.480 1.616 0.543 0.558 4.680 0.884 0.376 RaceBlack 0.337 1.401 1.069 0.173 11.381 0.316 0.752 RaceWhite -0.080 0.923 0.452 0.381 2.236 -0.178 0.859 Stage2 0.700 2.015 0.678 0.534 7.606 1.033 0.301 Stage3 1.456 4.287 0.674 1.144 16.068 2.159 0.031 * Stage4 2.866 17.560 0.790 3.736 82.532 3.629 0.000 *** Purity 0.215 1.240 0.768 0.275 5.590 0.280 0.779 Rsquare = 0.141 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.15e-02 Wald test p = 5.31e-03 Score (logrank) test p = 4.41e-04 FADS2 in GBM (n=153): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.032 1.033 0.098 0.852 1.253 0.329 0.742 Age 0.030 1.030 0.008 1.014 1.047 3.620 0.000 *** Gendermale -0.098 0.907 0.213 0.597 1.377 -0.460 0.645 RaceBlack 0.508 1.662 0.729 0.398 6.935 0.697 0.486 RaceWhite -0.275 0.760 0.623 0.224 2.577 -0.441 0.659 Purity -1.162 0.313 0.580 0.100 0.974 -2.005 0.045 * Rsquare = 0.13 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.6e-03 Wald test p = 6.34e-03 Score (logrank) test p = 5.5e-03 FADS2 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.048 0.953 0.051 0.862 1.053 -0.951 0.342 Age 0.022 1.023 0.008 1.007 1.038 2.932 0.003 ** Gendermale -0.216 0.806 0.175 0.571 1.136 -1.233 0.218 RaceBlack 0.204 1.226 0.563 0.406 3.700 0.362 0.717 RaceWhite -0.195 0.823 0.514 0.301 2.253 -0.379 0.705 Stage2 0.604 1.829 0.544 0.630 5.313 1.111 0.267 Stage3 0.831 2.296 0.537 0.801 6.580 1.548 0.122 Stage4 1.256 3.512 0.510 1.292 9.543 2.463 0.014 * Purity 0.008 1.008 0.367 0.491 2.068 0.022 0.983 Rsquare = 0.071 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.7e-04 Wald test p = 1.01e-03 Score (logrank) test p = 7.38e-04 FADS2 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.071 9.310000e-01 0.159 0.682 1.272 -0.447 0.655 Age 0.008 1.008000e+00 0.026 0.958 1.062 0.315 0.753 Gendermale -0.069 9.340000e-01 0.582 0.298 2.923 -0.118 0.906 RaceBlack 18.840 1.520809e+08 12062.744 0.000 Inf 0.002 0.999 RaceWhite 18.083 7.136880e+07 12062.744 0.000 Inf 0.001 0.999 Stage2 17.396 3.588878e+07 5239.865 0.000 Inf 0.003 0.997 Stage3 16.682 1.757472e+07 5239.865 0.000 Inf 0.003 0.997 Stage4 17.418 3.668573e+07 5239.865 0.000 Inf 0.003 0.997 Purity -1.513 2.200000e-01 1.069 0.027 1.788 -1.416 0.157 Rsquare = 0.09 (max possible = 9.17e-01 ) Likelihood ratio test p = 7.28e-01 Wald test p = 9.4e-01 Score (logrank) test p = 8.47e-01 FADS2 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.058 0.944 0.056 0.845 1.054 -1.030 0.303 Age 0.028 1.028 0.009 1.011 1.046 3.283 0.001 ** Gendermale -0.254 0.776 0.185 0.540 1.115 -1.370 0.171 RaceBlack 0.069 1.071 0.570 0.350 3.276 0.121 0.904 RaceWhite -0.332 0.717 0.516 0.261 1.972 -0.644 0.519 Stage2 0.349 1.418 0.554 0.478 4.200 0.630 0.529 Stage3 0.695 2.003 0.542 0.693 5.791 1.282 0.200 Stage4 1.157 3.181 0.512 1.166 8.680 2.259 0.024 * Purity 0.294 1.342 0.408 0.603 2.985 0.721 0.471 Rsquare = 0.088 (max possible = 9.89e-01 ) Likelihood ratio test p = 2.23e-04 Wald test p = 7.01e-04 Score (logrank) test p = 5.12e-04 FADS2 in KICH (n=66): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p FADS2 0.367 1.444000e+00 0.199 0.977 2.133000e+00 1.843 0.065 Age 0.095 1.099000e+00 0.030 1.036 1.166000e+00 3.140 0.002 Gendermale -0.870 4.190000e-01 0.734 0.099 1.768000e+00 -1.184 0.236 RaceBlack -16.229 0.000000e+00 6176.482 0.000 Inf -0.003 0.998 RaceWhite -1.309 2.700000e-01 1.166 0.027 2.654000e+00 -1.123 0.261 Stage2 15.338 4.584590e+06 0.843 878140.890 2.393518e+07 18.190 0.000 Stage3 16.791 1.959497e+07 0.784 4217221.564 9.104641e+07 21.424 0.000 Stage4 18.622 1.222848e+08 0.893 21252398.112 7.036180e+08 20.857 0.000 Purity 3.473 3.222300e+01 4.650 0.004 2.926746e+05 0.747 0.455 signif FADS2 · Age ** Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.365 (max possible = 6.71e-01 ) Likelihood ratio test p = 7.47e-04 Wald test p = 1.4e-261 Score (logrank) test p = 5.78e-09 FADS2 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.048 1.049 0.075 0.906 1.215 0.641 0.522 Age 0.035 1.036 0.008 1.019 1.053 4.171 0.000 *** Gendermale -0.083 0.921 0.184 0.642 1.319 -0.451 0.652 RaceBlack 0.205 1.228 1.056 0.155 9.732 0.194 0.846 RaceWhite 0.118 1.125 1.016 0.154 8.234 0.116 0.908 Stage2 0.226 1.253 0.345 0.638 2.463 0.656 0.512 Stage3 0.832 2.298 0.232 1.459 3.621 3.588 0.000 *** Stage4 1.764 5.836 0.216 3.821 8.915 8.163 0.000 *** Purity 0.032 1.033 0.372 0.498 2.141 0.087 0.931 Rsquare = 0.175 (max possible = 9.65e-01 ) Likelihood ratio test p = 8.57e-15 Wald test p = 1.23e-14 Score (logrank) test p = 5.62e-18 FADS2 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.283 1.327 0.137 1.014 1.736 2.059 0.039 * Age 0.018 1.018 0.016 0.986 1.052 1.092 0.275 Gendermale -0.426 0.653 0.383 0.308 1.385 -1.111 0.267 RaceBlack -2.300 0.100 1.208 0.009 1.069 -1.905 0.057 · RaceWhite -2.558 0.077 1.211 0.007 0.832 -2.112 0.035 * Stage2 -0.401 0.670 1.059 0.084 5.338 -0.379 0.705 Stage3 1.486 4.419 0.425 1.923 10.157 3.499 0.000 *** Stage4 2.618 13.706 0.506 5.089 36.914 5.179 0.000 *** Purity -0.167 0.846 0.720 0.207 3.468 -0.232 0.817 Rsquare = 0.179 (max possible = 7.58e-01 ) Likelihood ratio test p = 2.07e-06 Wald test p = 1.83e-06 Score (logrank) test p = 1.72e-10 FADS2 in LAML (n=173): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.148 1.159 0.105 0.945 1.423 1.414 0.157 Age 0.037 1.038 0.008 1.021 1.054 4.563 0.000 *** Gendermale -0.204 0.815 0.218 0.532 1.248 -0.940 0.347 RaceBlack -0.349 0.705 1.104 0.081 6.144 -0.316 0.752 RaceWhite -0.733 0.480 1.018 0.065 3.534 -0.720 0.471 Rsquare = 0.168 (max possible = 9.96e-01 ) Likelihood ratio test p = 4.92e-05 Wald test p = 1.54e-04 Score (logrank) test p = 1.01e-04 FADS2 in LGG (n=516): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.352 0.703 0.132 0.543 0.910 -2.676 0.007 ** Age 0.060 1.062 0.008 1.046 1.078 7.829 0.000 *** Gendermale 0.097 1.102 0.194 0.753 1.613 0.500 0.617 RaceBlack 15.961 8543417.016 2010.447 0.000 Inf 0.008 0.994 RaceWhite 15.866 7770514.618 2010.447 0.000 Inf 0.008 0.994 Purity -0.894 0.409 0.396 0.188 0.889 -2.256 0.024 * Rsquare = 0.149 (max possible = 9.07e-01 ) Likelihood ratio test p = 4.54e-14 Wald test p = 6.73e-14 Score (logrank) test p = 4.82e-15 FADS2 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.029 1.030 0.053 0.929 1.142 0.553 0.580 Age 0.011 1.011 0.008 0.995 1.027 1.330 0.183 Gendermale -0.142 0.868 0.226 0.557 1.350 -0.629 0.529 RaceBlack 0.879 2.409 0.490 0.923 6.289 1.795 0.073 · RaceWhite -0.018 0.982 0.240 0.613 1.572 -0.076 0.939 Stage2 0.329 1.390 0.262 0.831 2.324 1.253 0.210 Stage3 0.942 2.566 0.235 1.619 4.066 4.011 0.000 *** Stage4 1.581 4.860 0.619 1.445 16.343 2.555 0.011 * Purity 0.575 1.778 0.456 0.727 4.345 1.261 0.207 Rsquare = 0.085 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.07e-03 Wald test p = 6.33e-04 Score (logrank) test p = 2.43e-04 FADS2 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.068 1.071 0.060 0.951 1.205 1.131 0.258 Age 0.008 1.008 0.009 0.990 1.026 0.892 0.372 Gendermale 0.007 1.007 0.169 0.723 1.403 0.042 0.967 RaceBlack 16.139 10214428.758 1886.331 0.000 Inf 0.009 0.993 RaceWhite 16.322 12265774.410 1886.331 0.000 Inf 0.009 0.993 Stage2 0.850 2.340 0.201 1.577 3.472 4.222 0.000 *** Stage3 0.980 2.665 0.220 1.732 4.101 4.460 0.000 *** Stage4 1.024 2.785 0.334 1.448 5.356 3.070 0.002 ** Purity 0.609 1.838 0.343 0.938 3.601 1.773 0.076 · Rsquare = 0.099 (max possible = 9.74e-01 ) Likelihood ratio test p = 1.39e-06 Wald test p = 1.97e-05 Score (logrank) test p = 2.21e-06 FADS2 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.105 1.111 0.060 0.988 1.249 1.756 0.079 · Age 0.016 1.016 0.009 0.998 1.035 1.710 0.087 · Gendermale 0.429 1.536 0.193 1.053 2.240 2.226 0.026 * RaceBlack 0.034 1.034 0.608 0.314 3.403 0.056 0.956 RaceWhite -0.547 0.579 0.563 0.192 1.746 -0.970 0.332 Stage2 0.233 1.262 0.187 0.874 1.822 1.241 0.215 Stage3 0.563 1.757 0.215 1.152 2.678 2.618 0.009 ** Stage4 0.845 2.327 0.797 0.488 11.099 1.060 0.289 Purity -0.377 0.686 0.366 0.335 1.405 -1.030 0.303 Rsquare = 0.058 (max possible = 9.87e-01 ) Likelihood ratio test p = 8.08e-03 Wald test p = 6.23e-03 Score (logrank) test p = 5.36e-03 FADS2 in MESO (n=87): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.358 1.431 0.095 1.189 1.723 3.782 0.000 *** Age 0.022 1.023 0.016 0.991 1.055 1.408 0.159 Gendermale -0.096 0.909 0.336 0.471 1.754 -0.285 0.776 RaceBlack -0.086 0.918 1.529 0.046 18.392 -0.056 0.955 RaceWhite -0.355 0.701 1.047 0.090 5.451 -0.340 0.734 Stage2 -0.208 0.812 0.455 0.333 1.980 -0.458 0.647 Stage3 -0.256 0.774 0.413 0.344 1.740 -0.620 0.535 Stage4 -0.221 0.802 0.465 0.322 1.995 -0.475 0.635 Purity -0.286 0.751 0.563 0.249 2.262 -0.509 0.611 Rsquare = 0.217 (max possible = 9.98e-01 ) Likelihood ratio test p = 1.38e-02 Wald test p = 1.93e-02 Score (logrank) test p = 1.64e-02 FADS2 in OV (n=303): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.041 0.960 0.058 0.857 1.076 -0.696 0.486 Age 0.037 1.038 0.008 1.021 1.054 4.491 0.000 *** RaceBlack -0.046 0.955 0.577 0.309 2.957 -0.079 0.937 RaceWhite -0.147 0.863 0.515 0.315 2.369 -0.285 0.776 Purity -0.634 0.530 0.678 0.140 2.004 -0.935 0.350 Rsquare = 0.083 (max possible = 9.97e-01 ) Likelihood ratio test p = 9.39e-04 Wald test p = 8.2e-04 Score (logrank) test p = 6.87e-04 FADS2 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.087 0.917 0.113 0.734 1.144 -0.769 0.442 Age 0.020 1.020 0.011 0.998 1.043 1.774 0.076 · Gendermale -0.254 0.776 0.222 0.502 1.200 -1.141 0.254 RaceBlack 0.045 1.047 0.743 0.244 4.492 0.061 0.951 RaceWhite 0.411 1.508 0.478 0.591 3.847 0.860 0.390 Stage2 0.533 1.704 0.451 0.704 4.123 1.181 0.238 Stage3 -0.344 0.709 1.099 0.082 6.108 -0.313 0.754 Stage4 0.236 1.266 0.823 0.252 6.357 0.287 0.774 Purity -0.747 0.474 0.422 0.207 1.084 -1.770 0.077 · Rsquare = 0.092 (max possible = 9.91e-01 ) Likelihood ratio test p = 6.96e-02 Wald test p = 1.06e-01 Score (logrank) test p = 1e-01 FADS2 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 1.169 3.219 0.653 0.895 11.576 1.790 0.073 · Age 0.043 1.044 0.028 0.988 1.103 1.518 0.129 Gendermale 1.569 4.802 0.913 0.803 28.721 1.719 0.086 · RaceBlack -1.675 0.187 30239.716 0.000 Inf 0.000 1.000 RaceWhite 17.941 61876820.278 26972.290 0.000 Inf 0.001 0.999 Purity 6.870 962.707 3.873 0.486 1906890.732 1.774 0.076 · Rsquare = 0.078 (max possible = 3.07e-01 ) Likelihood ratio test p = 3.87e-02 Wald test p = 3.74e-01 Score (logrank) test p = 1.6e-01 FADS2 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.136 0.873 0.182 0.611 1.247 -0.749 0.454 Age 0.005 1.005 0.057 0.899 1.123 0.089 0.929 RaceBlack 14.892 2934624.116 6819.437 0.000 Inf 0.002 0.998 RaceWhite 16.250 11411730.873 6819.437 0.000 Inf 0.002 0.998 Purity 0.863 2.370 1.454 0.137 40.970 0.593 0.553 Rsquare = 0.008 (max possible = 1.83e-01 ) Likelihood ratio test p = 6.55e-01 Wald test p = 7.75e-01 Score (logrank) test p = 7.16e-01 FADS2 in READ (n=166): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.211 1.235 0.207 0.823 1.854 1.018 0.309 Age 0.126 1.135 0.049 1.030 1.249 2.570 0.010 * Gendermale -0.210 0.811 0.700 0.206 3.194 -0.300 0.764 RaceBlack 13.276 583288.045 10317.187 0.000 Inf 0.001 0.999 RaceWhite 11.982 159875.453 10317.187 0.000 Inf 0.001 0.999 Stage2 -1.721 0.179 1.263 0.015 2.126 -1.363 0.173 Stage3 -0.305 0.737 0.937 0.118 4.628 -0.325 0.745 Stage4 -0.138 0.871 0.966 0.131 5.786 -0.143 0.887 Purity 0.631 1.880 1.445 0.111 31.934 0.437 0.662 Rsquare = 0.22 (max possible = 7.22e-01 ) Likelihood ratio test p = 2.62e-02 Wald test p = 2.03e-01 Score (logrank) test p = 4.17e-02 FADS2 in SARC (n=260): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.176 1.193 0.100 0.980 1.453 1.757 0.079 · Age 0.022 1.023 0.008 1.006 1.039 2.682 0.007 ** Gendermale 0.071 1.074 0.228 0.686 1.679 0.311 0.756 RaceBlack -0.118 0.889 1.086 0.106 7.476 -0.108 0.914 RaceWhite -0.538 0.584 1.023 0.079 4.335 -0.526 0.599 Purity 0.650 1.915 0.592 0.600 6.116 1.097 0.273 Rsquare = 0.056 (max possible = 9.75e-01 ) Likelihood ratio test p = 3.81e-02 Wald test p = 5.53e-02 Score (logrank) test p = 5.66e-02 FADS2 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.007 0.993 0.049 0.902 1.093 -0.152 0.879 Age 0.018 1.019 0.005 1.008 1.029 3.543 0.000 *** Gendermale -0.050 0.951 0.157 0.699 1.294 -0.320 0.749 RaceWhite -1.287 0.276 0.401 0.126 0.607 -3.206 0.001 ** Stage2 0.275 1.316 0.218 0.858 2.020 1.259 0.208 Stage3 0.610 1.840 0.204 1.233 2.745 2.984 0.003 ** Stage4 1.350 3.857 0.352 1.936 7.684 3.838 0.000 *** Purity 1.015 2.759 0.341 1.414 5.386 2.974 0.003 ** Rsquare = 0.123 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.21e-08 Wald test p = 1.19e-08 Score (logrank) test p = 1.43e-09 FADS2 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.224 1.251000e+00 0.157 0.919 1.702 1.426 0.154 Age 0.013 1.013000e+00 0.016 0.982 1.045 0.817 0.414 Gendermale 0.222 1.248000e+00 0.435 0.532 2.930 0.510 0.610 RaceWhite -1.224 2.940000e-01 0.624 0.087 1.000 -1.959 0.050 · Stage2 17.393 3.577574e+07 6261.971 0.000 Inf 0.003 0.998 Stage3 17.957 6.292047e+07 6261.971 0.000 Inf 0.003 0.998 Stage4 20.586 8.719682e+08 6261.971 0.000 Inf 0.003 0.997 Purity -0.174 8.410000e-01 0.986 0.122 5.804 -0.176 0.860 Rsquare = 0.165 (max possible = 8.69e-01 ) Likelihood ratio test p = 3.1e-02 Wald test p = 3.07e-02 Score (logrank) test p = 1.99e-03 FADS2 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.006 1.006 0.053 0.907 1.115 0.105 0.916 Age 0.021 1.021 0.006 1.010 1.032 3.657 0.000 *** Gendermale -0.058 0.944 0.172 0.674 1.323 -0.335 0.737 RaceWhite -1.055 0.348 0.600 0.107 1.128 -1.758 0.079 · Stage2 0.152 1.164 0.230 0.741 1.828 0.660 0.509 Stage3 0.564 1.758 0.209 1.167 2.648 2.697 0.007 ** Stage4 1.134 3.107 0.400 1.420 6.802 2.837 0.005 ** Purity 1.148 3.151 0.372 1.521 6.530 3.087 0.002 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.1e-06 Wald test p = 1.71e-06 Score (logrank) test p = 6.6e-07 FADS2 in STAD (n=415): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.029 1.029 0.072 0.893 1.186 0.397 0.691 Age 0.026 1.027 0.010 1.006 1.048 2.581 0.010 * Gendermale 0.114 1.121 0.208 0.745 1.686 0.546 0.585 RaceBlack 0.268 1.307 0.447 0.544 3.140 0.598 0.550 RaceWhite 0.086 1.089 0.245 0.674 1.761 0.350 0.727 Stage2 0.478 1.613 0.390 0.750 3.466 1.224 0.221 Stage3 0.900 2.460 0.366 1.200 5.044 2.458 0.014 * Stage4 1.307 3.695 0.505 1.373 9.941 2.588 0.010 * Purity -0.561 0.570 0.380 0.271 1.202 -1.476 0.140 Rsquare = 0.07 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.3e-02 Wald test p = 1.74e-02 Score (logrank) test p = 1.41e-02 FADS2 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 2.538 12.649 17773.492 0 Inf 0.000 1.000 Age -1.638 0.194 1805.359 0 Inf -0.001 0.999 RaceBlack 3.969 52.908 20555916.823 0 Inf 0.000 1.000 RaceWhite -36.746 0.000 21375335.557 0 Inf 0.000 1.000 Stage2 1.492 4.445 38113.928 0 Inf 0.000 1.000 Stage3 14.170 1425797.853 120276.130 0 Inf 0.000 1.000 Purity 6.898 989.994 223132.560 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 2.72e-03 FADS2 in THCA (n=509): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.441 1.554 0.293 0.875 2.759 1.505 0.132 Age 0.146 1.158 0.029 1.093 1.226 4.992 0.000 *** Gendermale -0.483 0.617 0.721 0.150 2.535 -0.670 0.503 RaceBlack 16.199 10847496.131 6106.033 0.000 Inf 0.003 0.998 RaceWhite 16.041 9259601.983 6106.033 0.000 Inf 0.003 0.998 Stage2 0.426 1.531 1.119 0.171 13.726 0.381 0.703 Stage3 0.385 1.469 0.865 0.270 8.002 0.445 0.656 Stage4 2.079 7.993 1.060 1.000 63.856 1.960 0.050 · Purity 2.170 8.761 1.102 1.010 75.966 1.969 0.049 * Rsquare = 0.154 (max possible = 3.47e-01 ) Likelihood ratio test p = 8.81e-11 Wald test p = 2.95e-04 Score (logrank) test p = 5.88e-12 FADS2 in THYM (n=120): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.211 0.810 0.283 0.465 1.410 -0.746 0.456 Age 0.046 1.047 0.031 0.985 1.114 1.477 0.140 Gendermale -0.193 0.824 0.736 0.195 3.489 -0.262 0.793 RaceBlack -16.348 0.000 10145.107 0.000 Inf -0.002 0.999 RaceWhite 0.627 1.871 1.116 0.210 16.682 0.561 0.574 Purity 0.395 1.484 1.093 0.174 12.644 0.361 0.718 Rsquare = 0.049 (max possible = 4.51e-01 ) Likelihood ratio test p = 4.67e-01 Wald test p = 5.88e-01 Score (logrank) test p = 4.79e-01 FADS2 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.058 1.059 0.114 0.846 1.326 0.502 0.615 Age 0.051 1.052 0.016 1.020 1.085 3.202 0.001 ** RaceBlack -0.456 0.634 0.797 0.133 3.026 -0.571 0.568 RaceWhite -0.583 0.558 0.753 0.128 2.441 -0.775 0.439 Purity 0.414 1.513 0.650 0.423 5.404 0.637 0.524 Rsquare = 0.039 (max possible = 7.81e-01 ) Likelihood ratio test p = 4.55e-02 Wald test p = 5.23e-02 Score (logrank) test p = 5.08e-02 FADS2 in UCS (n=57): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 -0.176 0.839 0.187 0.582 1.209 -0.941 0.347 Age 0.048 1.049 0.024 1.000 1.100 1.959 0.050 · RaceBlack 17.458 38177374.047 6564.584 0.000 Inf 0.003 0.998 RaceWhite 17.709 49104604.070 6564.584 0.000 Inf 0.003 0.998 Purity -0.975 0.377 1.061 0.047 3.016 -0.919 0.358 Rsquare = 0.133 (max possible = 9.83e-01 ) Likelihood ratio test p = 1.89e-01 Wald test p = 2.66e-01 Score (logrank) test p = 1.92e-01 FADS2 in UVM (n=80): Model: Surv(OS, EVENT) ~ `FADS2` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FADS2 0.479 1.614 0.208 1.074 2.425 2.304 0.021 * Age 0.039 1.040 0.020 1.000 1.081 1.970 0.049 * Gendermale 0.369 1.446 0.508 0.535 3.909 0.726 0.468 Stage3 -0.085 0.918 0.551 0.312 2.702 -0.155 0.877 Stage4 3.888 48.789 1.221 4.459 533.865 3.185 0.001 ** Purity 1.966 7.144 1.224 0.649 78.629 1.607 0.108 Rsquare = 0.304 (max possible = 8.72e-01 ) Likelihood ratio test p = 9.61e-05 Wald test p = 1.12e-03 Score (logrank) test p = 4.21e-10 FASN in ACC (n=79): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.430 1.538 0.177 1.087 2.176 2.429 0.015 * Age 0.016 1.017 0.015 0.988 1.046 1.116 0.265 Gendermale 0.804 2.234 0.461 0.906 5.512 1.745 0.081 · RaceBlack -0.153 0.858 12852.991 0.000 Inf 0.000 1.000 RaceWhite 15.971 8629428.854 11005.122 0.000 Inf 0.001 0.999 Purity 1.041 2.832 2.400 0.026 312.506 0.434 0.664 Rsquare = 0.154 (max possible = 9.38e-01 ) Likelihood ratio test p = 9.75e-02 Wald test p = 2.17e-01 Score (logrank) test p = 1.32e-01 FASN in BLCA (n=408): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.222 1.248 0.083 1.061 1.468 2.681 0.007 ** Age 0.029 1.029 0.009 1.012 1.047 3.335 0.001 ** Gendermale -0.261 0.770 0.182 0.539 1.100 -1.434 0.151 RaceBlack 0.664 1.943 0.448 0.807 4.677 1.481 0.139 RaceWhite 0.138 1.148 0.355 0.572 2.302 0.387 0.698 Stage2 14.636 2272525.006 1867.292 0.000 Inf 0.008 0.994 Stage3 15.125 3702607.690 1867.292 0.000 Inf 0.008 0.994 Stage4 15.571 5789035.837 1867.292 0.000 Inf 0.008 0.993 Purity -0.147 0.863 0.356 0.430 1.733 -0.414 0.679 Rsquare = 0.148 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.8e-09 Wald test p = 4.8e-08 Score (logrank) test p = 1.53e-08 FASN in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.065 0.937 0.072 0.814 1.080 -0.898 0.369 Age 0.035 1.035 0.008 1.020 1.051 4.519 0.000 *** Gendermale 0.118 1.125 1.011 0.155 8.161 0.117 0.907 RaceBlack 0.004 1.004 0.619 0.299 3.377 0.007 0.995 RaceWhite -0.211 0.810 0.596 0.252 2.603 -0.354 0.723 Stage2 0.399 1.490 0.304 0.822 2.703 1.313 0.189 Stage3 1.189 3.284 0.313 1.780 6.062 3.803 0.000 *** Stage4 2.526 12.500 0.389 5.833 26.788 6.495 0.000 *** Purity 0.552 1.736 0.421 0.760 3.966 1.309 0.191 Rsquare = 0.082 (max possible = 7.85e-01 ) Likelihood ratio test p = 1.72e-12 Wald test p = 5.47e-16 Score (logrank) test p = 6.04e-22 FASN in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `FASN` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.134 8.750000e-01 0.232 0.555 1.378 -0.578 0.563 Age 0.013 1.013000e+00 0.018 0.978 1.049 0.706 0.480 RaceBlack -0.913 4.010000e-01 1.107 0.046 3.514 -0.825 0.410 RaceWhite -1.304 2.710000e-01 1.119 0.030 2.431 -1.166 0.244 Stage2 18.714 1.341153e+08 6474.077 0.000 Inf 0.003 0.998 Stage3 20.110 5.415547e+08 6474.077 0.000 Inf 0.003 0.998 Stage4 21.497 2.168078e+09 6474.077 0.000 Inf 0.003 0.997 Purity 0.759 2.136000e+00 0.951 0.331 13.782 0.798 0.425 Rsquare = 0.158 (max possible = 7.18e-01 ) Likelihood ratio test p = 4.57e-04 Wald test p = 7.89e-03 Score (logrank) test p = 4.6e-06 FASN in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `FASN` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.794 4.520000e-01 0.510 0.167 1.227 -1.558 0.119 Age 0.036 1.037000e+00 0.030 0.977 1.100 1.204 0.229 RaceBlack -3.650 2.600000e-02 1.937 0.001 1.158 -1.884 0.060 · RaceWhite -2.603 7.400000e-02 1.615 0.003 1.756 -1.612 0.107 Stage2 18.102 7.269678e+07 14943.052 0.000 Inf 0.001 0.999 Stage3 20.114 5.435637e+08 14943.052 0.000 Inf 0.001 0.999 Stage4 55.173 9.149229e+23 2584579.719 0.000 Inf 0.000 1.000 Purity 3.606 3.682600e+01 2.396 0.336 4036.802 1.505 0.132 Rsquare = 0.4 (max possible = 6.68e-01 ) Likelihood ratio test p = 1.96e-04 Wald test p = 1e+00 Score (logrank) test p = 3.33e-14 FASN in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.082 0.921 0.115 0.735 1.155 -0.712 0.476 Age 0.046 1.047 0.012 1.022 1.073 3.701 0.000 *** Gendermale -15.216 0.000 3463.728 0.000 Inf -0.004 0.996 RaceBlack -0.387 0.679 1.175 0.068 6.798 -0.330 0.742 RaceWhite 0.334 1.397 1.038 0.183 10.682 0.322 0.748 Stage2 0.300 1.349 0.376 0.646 2.817 0.798 0.425 Stage3 0.813 2.254 0.399 1.031 4.931 2.036 0.042 * Stage4 2.187 8.905 0.594 2.780 28.525 3.681 0.000 *** Purity 0.374 1.453 0.621 0.430 4.904 0.602 0.547 Rsquare = 0.071 (max possible = 6.81e-01 ) Likelihood ratio test p = 8.49e-05 Wald test p = 1.96e-05 Score (logrank) test p = 3.71e-07 FASN in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.050 1.052 0.173 0.749 1.475 0.291 0.771 Age 0.052 1.053 0.022 1.009 1.100 2.352 0.019 * Gendermale 1.003 2.727 1.110 0.310 24.014 0.904 0.366 RaceBlack 16.634 16744353.014 6507.667 0.000 Inf 0.003 0.998 RaceWhite 16.017 9039818.937 6507.667 0.000 Inf 0.002 0.998 Stage2 0.639 1.895 1.083 0.227 15.826 0.590 0.555 Stage3 1.560 4.759 1.068 0.586 38.632 1.460 0.144 Stage4 2.069 7.917 1.173 0.794 78.898 1.764 0.078 · Purity 1.088 2.967 1.337 0.216 40.736 0.814 0.416 Rsquare = 0.106 (max possible = 6.98e-01 ) Likelihood ratio test p = 4.09e-02 Wald test p = 7.15e-02 Score (logrank) test p = 2.38e-02 FASN in CESC (n=306): Model: Surv(OS, EVENT) ~ `FASN` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.260 1.297 0.128 1.008 1.667 2.024 0.043 * Age 0.008 1.008 0.010 0.988 1.028 0.770 0.441 RaceBlack 1.062 2.893 1.069 0.356 23.490 0.994 0.320 RaceWhite 0.932 2.541 1.016 0.347 18.628 0.917 0.359 Purity 0.554 1.740 0.749 0.401 7.553 0.740 0.459 Rsquare = 0.031 (max possible = 8.91e-01 ) Likelihood ratio test p = 2.09e-01 Wald test p = 2.17e-01 Score (logrank) test p = 2.1e-01 FASN in CHOL (n=36): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.593 1.809 0.390 0.842 3.886 1.519 0.129 Age 0.021 1.021 0.023 0.977 1.068 0.922 0.357 Gendermale 0.126 1.135 0.565 0.375 3.433 0.224 0.823 RaceBlack -0.480 0.619 1.515 0.032 12.048 -0.317 0.751 RaceWhite -1.167 0.311 0.919 0.051 1.887 -1.269 0.204 Stage2 0.678 1.970 0.674 0.526 7.381 1.007 0.314 Stage3 -13.622 0.000 7084.183 0.000 Inf -0.002 0.998 Stage4 0.786 2.195 0.684 0.575 8.387 1.150 0.250 Purity 3.034 20.778 1.819 0.588 733.819 1.668 0.095 · Rsquare = 0.262 (max possible = 9.46e-01 ) Likelihood ratio test p = 2.8e-01 Wald test p = 5.13e-01 Score (logrank) test p = 3.34e-01 FASN in COAD (n=458): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.093 0.911 0.165 0.659 1.259 -0.565 0.572 Age 0.024 1.024 0.012 1.002 1.048 2.103 0.035 * Gendermale 0.193 1.212 0.271 0.713 2.060 0.712 0.477 RaceBlack -0.441 0.643 0.830 0.126 3.272 -0.532 0.595 RaceWhite -0.473 0.623 0.777 0.136 2.856 -0.609 0.542 Stage2 0.201 1.223 0.562 0.406 3.682 0.357 0.721 Stage3 0.819 2.269 0.550 0.773 6.663 1.491 0.136 Stage4 1.904 6.710 0.554 2.267 19.857 3.439 0.001 ** Purity -0.161 0.852 0.608 0.258 2.806 -0.264 0.792 Rsquare = 0.11 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.11e-04 Wald test p = 1.44e-04 Score (logrank) test p = 2.06e-05 FASN in DLBC (n=48): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 1.803 6.066 0.901 1.037 35.492 2.000 0.045 * Age -0.026 0.975 0.046 0.890 1.067 -0.552 0.581 Gendermale 0.898 2.456 1.183 0.242 24.933 0.760 0.447 RaceBlack 3.247 25.725 2.641 0.145 4556.021 1.230 0.219 RaceWhite -2.561 0.077 1.598 0.003 1.771 -1.602 0.109 Purity -3.217 0.040 2.761 0.000 8.968 -1.165 0.244 Rsquare = 0.237 (max possible = 5.58e-01 ) Likelihood ratio test p = 8.52e-02 Wald test p = 3.26e-01 Score (logrank) test p = 1.28e-01 FASN in ESCA (n=185): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.042 1.043 0.226 0.669 1.625 0.185 0.853 Age 0.010 1.010 0.014 0.982 1.038 0.701 0.484 Gendermale 0.495 1.640 0.543 0.566 4.749 0.912 0.362 RaceBlack 0.322 1.379 1.071 0.169 11.247 0.300 0.764 RaceWhite -0.073 0.930 0.449 0.386 2.241 -0.162 0.871 Stage2 0.715 2.044 0.661 0.560 7.468 1.082 0.279 Stage3 1.467 4.334 0.674 1.158 16.228 2.177 0.029 * Stage4 2.853 17.343 0.777 3.780 79.566 3.671 0.000 *** Purity 0.177 1.194 0.793 0.252 5.650 0.224 0.823 Rsquare = 0.141 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.14e-02 Wald test p = 5.3e-03 Score (logrank) test p = 4.39e-04 FASN in GBM (n=153): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.044 1.045 0.121 0.825 1.324 0.367 0.714 Age 0.030 1.030 0.008 1.014 1.047 3.606 0.000 *** Gendermale -0.097 0.907 0.213 0.598 1.377 -0.457 0.648 RaceBlack 0.535 1.707 0.727 0.411 7.100 0.736 0.462 RaceWhite -0.231 0.793 0.615 0.238 2.647 -0.377 0.706 Purity -1.174 0.309 0.581 0.099 0.965 -2.020 0.043 * Rsquare = 0.13 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.55e-03 Wald test p = 6.04e-03 Score (logrank) test p = 5.22e-03 FASN in HNSC (n=522): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.065 1.067 0.103 0.872 1.307 0.633 0.527 Age 0.022 1.022 0.008 1.007 1.037 2.819 0.005 ** Gendermale -0.255 0.775 0.172 0.553 1.086 -1.480 0.139 RaceBlack 0.125 1.134 0.559 0.379 3.389 0.224 0.822 RaceWhite -0.241 0.786 0.511 0.289 2.139 -0.471 0.637 Stage2 0.617 1.854 0.544 0.639 5.380 1.136 0.256 Stage3 0.866 2.377 0.537 0.830 6.807 1.612 0.107 Stage4 1.252 3.496 0.510 1.287 9.496 2.455 0.014 * Purity -0.068 0.934 0.367 0.455 1.916 -0.186 0.853 Rsquare = 0.07 (max possible = 9.89e-01 ) Likelihood ratio test p = 4.5e-04 Wald test p = 1.19e-03 Score (logrank) test p = 8.57e-04 FASN in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.302 1.353000e+00 0.308 0.740 2.474 0.981 0.326 Age 0.006 1.006000e+00 0.026 0.957 1.058 0.240 0.810 Gendermale -0.200 8.190000e-01 0.550 0.279 2.406 -0.363 0.716 RaceBlack 18.817 1.486685e+08 12163.900 0.000 Inf 0.002 0.999 RaceWhite 18.081 7.120790e+07 12163.900 0.000 Inf 0.001 0.999 Stage2 17.348 3.421626e+07 5402.806 0.000 Inf 0.003 0.997 Stage3 16.805 1.987055e+07 5402.806 0.000 Inf 0.003 0.998 Stage4 17.484 3.918816e+07 5402.806 0.000 Inf 0.003 0.997 Purity -1.480 2.280000e-01 1.078 0.028 1.884 -1.373 0.170 Rsquare = 0.101 (max possible = 9.17e-01 ) Likelihood ratio test p = 6.45e-01 Wald test p = 9.02e-01 Score (logrank) test p = 7.79e-01 FASN in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.001 1.001 0.112 0.803 1.246 0.005 0.996 Age 0.027 1.027 0.008 1.010 1.044 3.181 0.001 ** Gendermale -0.285 0.752 0.183 0.525 1.076 -1.558 0.119 RaceBlack -0.017 0.983 0.564 0.325 2.970 -0.031 0.975 RaceWhite -0.396 0.673 0.512 0.247 1.837 -0.773 0.440 Stage2 0.366 1.443 0.554 0.487 4.270 0.662 0.508 Stage3 0.727 2.069 0.541 0.716 5.975 1.343 0.179 Stage4 1.147 3.149 0.512 1.154 8.590 2.240 0.025 * Purity 0.210 1.233 0.403 0.560 2.717 0.520 0.603 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.4e-04 Wald test p = 9.52e-04 Score (logrank) test p = 7.21e-04 FASN in KICH (n=66): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p FASN 0.976 2.653000e+00 0.547 0.909 7.743000e+00 1.785 0.074 Age 0.071 1.074000e+00 0.030 1.013 1.138000e+00 2.405 0.016 Gendermale -0.972 3.790000e-01 0.732 0.090 1.589000e+00 -1.327 0.184 RaceBlack -15.086 0.000000e+00 5232.960 0.000 Inf -0.003 0.998 RaceWhite -0.605 5.460000e-01 1.166 0.055 5.369000e+00 -0.519 0.604 Stage2 15.016 3.321694e+06 0.846 633216.615 1.742477e+07 17.757 0.000 Stage3 16.575 1.578773e+07 0.789 3361878.775 7.414076e+07 21.003 0.000 Stage4 18.470 1.051010e+08 0.910 17668759.230 6.251838e+08 20.302 0.000 Purity 1.649 5.200000e+00 3.857 0.003 9.972666e+03 0.427 0.669 signif FASN · Age * Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.367 (max possible = 6.71e-01 ) Likelihood ratio test p = 7.03e-04 Wald test p = 2.78e-248 Score (logrank) test p = 5.61e-09 FASN in KIRC (n=533): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.513 1.671 0.119 1.324 2.109 4.323 0.000 *** Age 0.040 1.040 0.009 1.023 1.058 4.609 0.000 *** Gendermale 0.058 1.059 0.186 0.735 1.526 0.309 0.757 RaceBlack 0.704 2.023 1.069 0.249 16.447 0.659 0.510 RaceWhite 0.588 1.801 1.024 0.242 13.410 0.574 0.566 Stage2 0.151 1.163 0.350 0.586 2.310 0.432 0.666 Stage3 0.814 2.258 0.231 1.436 3.550 3.528 0.000 *** Stage4 1.800 6.048 0.217 3.955 9.249 8.304 0.000 *** Purity 0.079 1.082 0.368 0.526 2.225 0.214 0.831 Rsquare = 0.203 (max possible = 9.65e-01 ) Likelihood ratio test p = 5.42e-18 Wald test p = 4.38e-17 Score (logrank) test p = 1.25e-20 FASN in KIRP (n=290): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.981 2.667 0.285 1.524 4.668 3.437 0.001 ** Age 0.033 1.033 0.017 0.999 1.069 1.905 0.057 · Gendermale -0.052 0.949 0.404 0.430 2.095 -0.129 0.898 RaceBlack -1.403 0.246 1.251 0.021 2.855 -1.121 0.262 RaceWhite -2.011 0.134 1.217 0.012 1.454 -1.652 0.098 · Stage2 -1.012 0.364 1.065 0.045 2.934 -0.950 0.342 Stage3 1.153 3.166 0.444 1.327 7.556 2.597 0.009 ** Stage4 2.521 12.438 0.527 4.426 34.954 4.782 0.000 *** Purity -0.446 0.640 0.758 0.145 2.828 -0.589 0.556 Rsquare = 0.209 (max possible = 7.58e-01 ) Likelihood ratio test p = 5.74e-08 Wald test p = 1.01e-07 Score (logrank) test p = 4.07e-12 FASN in LAML (n=173): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.255 1.291 0.135 0.991 1.682 1.891 0.059 · Age 0.039 1.040 0.008 1.024 1.057 4.853 0.000 *** Gendermale -0.212 0.809 0.215 0.530 1.233 -0.987 0.323 RaceBlack -0.589 0.555 1.113 0.063 4.916 -0.530 0.596 RaceWhite -0.921 0.398 1.025 0.053 2.968 -0.899 0.369 Rsquare = 0.176 (max possible = 9.96e-01 ) Likelihood ratio test p = 2.43e-05 Wald test p = 7.33e-05 Score (logrank) test p = 4.89e-05 FASN in LGG (n=516): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.505 0.603 0.143 0.456 0.798 -3.538 0.000 *** Age 0.063 1.065 0.008 1.049 1.081 8.123 0.000 *** Gendermale 0.053 1.055 0.194 0.721 1.543 0.275 0.783 RaceBlack 15.235 4135028.474 2048.965 0.000 Inf 0.007 0.994 RaceWhite 15.344 4609441.218 2048.965 0.000 Inf 0.007 0.994 Purity -0.808 0.446 0.414 0.198 1.003 -1.952 0.051 · Rsquare = 0.159 (max possible = 9.07e-01 ) Likelihood ratio test p = 3.29e-15 Wald test p = 5.67e-15 Score (logrank) test p = 1.49e-16 FASN in LIHC (n=371): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.088 1.092 0.073 0.946 1.260 1.204 0.228 Age 0.011 1.011 0.008 0.995 1.027 1.374 0.170 Gendermale -0.154 0.857 0.227 0.550 1.337 -0.679 0.497 RaceBlack 0.906 2.475 0.491 0.946 6.478 1.846 0.065 · RaceWhite -0.010 0.990 0.237 0.622 1.576 -0.040 0.968 Stage2 0.331 1.392 0.261 0.834 2.322 1.267 0.205 Stage3 0.924 2.520 0.235 1.589 3.994 3.931 0.000 *** Stage4 1.616 5.032 0.619 1.495 16.936 2.609 0.009 ** Purity 0.533 1.704 0.461 0.690 4.206 1.156 0.248 Rsquare = 0.089 (max possible = 9.66e-01 ) Likelihood ratio test p = 6.84e-04 Wald test p = 4.37e-04 Score (logrank) test p = 1.64e-04 FASN in LUAD (n=515): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.030 1.031 0.072 0.895 1.186 0.420 0.674 Age 0.007 1.007 0.009 0.989 1.025 0.764 0.445 Gendermale 0.002 1.002 0.173 0.713 1.406 0.009 0.993 RaceBlack 16.097 9786669.156 1894.988 0.000 Inf 0.008 0.993 RaceWhite 16.279 11740199.367 1894.988 0.000 Inf 0.009 0.993 Stage2 0.862 2.368 0.201 1.597 3.512 4.288 0.000 *** Stage3 1.003 2.727 0.219 1.774 4.191 4.575 0.000 *** Stage4 0.999 2.714 0.334 1.410 5.227 2.987 0.003 ** Purity 0.564 1.757 0.350 0.885 3.488 1.612 0.107 Rsquare = 0.097 (max possible = 9.74e-01 ) Likelihood ratio test p = 2.23e-06 Wald test p = 2.85e-05 Score (logrank) test p = 3.26e-06 FASN in LUSC (n=501): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.132 1.141 0.084 0.967 1.346 1.563 0.118 Age 0.017 1.017 0.009 0.999 1.036 1.801 0.072 · Gendermale 0.391 1.479 0.195 1.010 2.165 2.009 0.045 * RaceBlack -0.024 0.977 0.607 0.297 3.209 -0.039 0.969 RaceWhite -0.522 0.593 0.563 0.197 1.790 -0.927 0.354 Stage2 0.176 1.192 0.188 0.825 1.724 0.936 0.349 Stage3 0.574 1.776 0.215 1.165 2.707 2.672 0.008 ** Stage4 0.805 2.236 0.795 0.471 10.625 1.012 0.311 Purity -0.385 0.680 0.367 0.332 1.395 -1.051 0.293 Rsquare = 0.057 (max possible = 9.87e-01 ) Likelihood ratio test p = 1.02e-02 Wald test p = 8.5e-03 Score (logrank) test p = 7.38e-03 FASN in MESO (n=87): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.468 1.596 0.147 1.197 2.128 3.187 0.001 ** Age 0.017 1.017 0.016 0.986 1.048 1.057 0.290 Gendermale -0.332 0.717 0.334 0.373 1.380 -0.996 0.319 RaceBlack 0.059 1.061 1.528 0.053 21.201 0.039 0.969 RaceWhite -0.544 0.581 1.045 0.075 4.505 -0.520 0.603 Stage2 -0.099 0.906 0.462 0.366 2.240 -0.214 0.831 Stage3 -0.037 0.963 0.411 0.430 2.157 -0.091 0.928 Stage4 0.052 1.053 0.480 0.411 2.696 0.108 0.914 Purity -0.939 0.391 0.543 0.135 1.134 -1.729 0.084 · Rsquare = 0.164 (max possible = 9.98e-01 ) Likelihood ratio test p = 8.45e-02 Wald test p = 7.77e-02 Score (logrank) test p = 6.26e-02 FASN in OV (n=303): Model: Surv(OS, EVENT) ~ `FASN` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.114 0.892 0.094 0.742 1.072 -1.220 0.223 Age 0.035 1.036 0.008 1.020 1.053 4.351 0.000 *** RaceBlack -0.041 0.960 0.576 0.310 2.972 -0.070 0.944 RaceWhite -0.191 0.826 0.515 0.301 2.269 -0.370 0.711 Purity -0.650 0.522 0.672 0.140 1.948 -0.968 0.333 Rsquare = 0.087 (max possible = 9.97e-01 ) Likelihood ratio test p = 6.1e-04 Wald test p = 4.85e-04 Score (logrank) test p = 4.28e-04 FASN in PAAD (n=179): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.217 0.805 0.148 0.602 1.075 -1.472 0.141 Age 0.023 1.023 0.011 1.002 1.045 2.132 0.033 * Gendermale -0.257 0.773 0.219 0.503 1.188 -1.173 0.241 RaceBlack -0.024 0.976 0.738 0.230 4.149 -0.032 0.974 RaceWhite 0.326 1.386 0.475 0.546 3.518 0.687 0.492 Stage2 0.545 1.724 0.442 0.725 4.099 1.233 0.217 Stage3 -0.457 0.633 1.103 0.073 5.502 -0.414 0.679 Stage4 0.289 1.335 0.824 0.265 6.711 0.350 0.726 Purity -0.600 0.549 0.411 0.245 1.227 -1.462 0.144 Rsquare = 0.1 (max possible = 9.91e-01 ) Likelihood ratio test p = 4.29e-02 Wald test p = 5.78e-02 Score (logrank) test p = 5.49e-02 FASN in PCPG (n=181): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.578 1.783 0.552 0.604 5.263 1.047 0.295 Age 0.042 1.043 0.028 0.986 1.102 1.471 0.141 Gendermale 1.381 3.980 0.910 0.669 23.672 1.519 0.129 RaceBlack -0.568 0.567 19098.109 0.000 Inf 0.000 1.000 RaceWhite 17.053 25478921.358 15320.180 0.000 Inf 0.001 0.999 Purity 5.754 315.422 3.569 0.289 344218.876 1.612 0.107 Rsquare = 0.061 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.13e-01 Wald test p = 3.43e-01 Score (logrank) test p = 2.64e-01 FASN in PRAD (n=498): Model: Surv(OS, EVENT) ~ `FASN` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.358 1.430 0.331 0.748 2.735 1.081 0.280 Age 0.015 1.015 0.056 0.909 1.133 0.263 0.793 RaceBlack 15.242 4163017.967 6720.841 0.000 Inf 0.002 0.998 RaceWhite 16.386 13073753.134 6720.841 0.000 Inf 0.002 0.998 Purity 1.050 2.858 1.363 0.198 41.343 0.770 0.441 Rsquare = 0.01 (max possible = 1.83e-01 ) Likelihood ratio test p = 5.6e-01 Wald test p = 6.95e-01 Score (logrank) test p = 6.34e-01 FASN in READ (n=166): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.228 1.256 0.557 0.421 3.744 0.409 0.683 Age 0.116 1.123 0.048 1.023 1.234 2.432 0.015 * Gendermale -0.305 0.737 0.689 0.191 2.847 -0.442 0.658 RaceBlack 13.019 450940.260 10162.699 0.000 Inf 0.001 0.999 RaceWhite 11.927 151322.852 10162.699 0.000 Inf 0.001 0.999 Stage2 -1.843 0.158 1.252 0.014 1.842 -1.472 0.141 Stage3 -0.370 0.690 0.936 0.110 4.323 -0.396 0.692 Stage4 -0.157 0.855 0.952 0.132 5.529 -0.165 0.869 Purity 0.276 1.318 1.361 0.092 18.973 0.203 0.839 Rsquare = 0.211 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.5e-02 Wald test p = 2.55e-01 Score (logrank) test p = 4.93e-02 FASN in SARC (n=260): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.529 1.698 0.131 1.314 2.193 4.051 0.000 *** Age 0.019 1.020 0.008 1.004 1.036 2.398 0.016 * Gendermale 0.107 1.113 0.227 0.713 1.737 0.472 0.637 RaceBlack -0.080 0.923 1.086 0.110 7.765 -0.073 0.942 RaceWhite -0.529 0.589 1.023 0.079 4.371 -0.517 0.605 Purity 0.875 2.400 0.587 0.759 7.590 1.490 0.136 Rsquare = 0.106 (max possible = 9.75e-01 ) Likelihood ratio test p = 2.07e-04 Wald test p = 1.87e-04 Score (logrank) test p = 2.16e-04 FASN in SKCM (n=471): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.010 1.010 0.063 0.892 1.142 0.151 0.880 Age 0.018 1.019 0.005 1.008 1.029 3.549 0.000 *** Gendermale -0.050 0.951 0.157 0.699 1.295 -0.316 0.752 RaceWhite -1.289 0.276 0.402 0.125 0.606 -3.207 0.001 ** Stage2 0.275 1.317 0.218 0.858 2.020 1.260 0.208 Stage3 0.610 1.841 0.204 1.234 2.746 2.991 0.003 ** Stage4 1.348 3.850 0.352 1.932 7.675 3.831 0.000 *** Purity 1.010 2.746 0.346 1.395 5.405 2.923 0.003 ** Rsquare = 0.123 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.21e-08 Wald test p = 1.15e-08 Score (logrank) test p = 1.36e-09 FASN in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.006 9.940000e-01 0.145 0.749 1.321 -0.040 0.968 Age 0.012 1.012000e+00 0.016 0.981 1.044 0.748 0.455 Gendermale 0.206 1.228000e+00 0.469 0.490 3.080 0.439 0.661 RaceWhite -1.264 2.830000e-01 0.620 0.084 0.952 -2.039 0.041 * Stage2 17.472 3.872807e+07 6204.539 0.000 Inf 0.003 0.998 Stage3 17.975 6.403052e+07 6204.539 0.000 Inf 0.003 0.998 Stage4 20.092 5.319997e+08 6204.539 0.000 Inf 0.003 0.997 Purity 0.291 1.337000e+00 1.047 0.172 10.403 0.278 0.781 Rsquare = 0.146 (max possible = 8.69e-01 ) Likelihood ratio test p = 6.13e-02 Wald test p = 5.54e-02 Score (logrank) test p = 4.51e-03 FASN in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.015 1.015 0.069 0.887 1.162 0.219 0.827 Age 0.021 1.021 0.006 1.010 1.032 3.653 0.000 *** Gendermale -0.059 0.943 0.172 0.673 1.321 -0.342 0.732 RaceWhite -1.067 0.344 0.602 0.106 1.119 -1.773 0.076 · Stage2 0.152 1.165 0.230 0.741 1.829 0.661 0.508 Stage3 0.562 1.754 0.209 1.165 2.642 2.689 0.007 ** Stage4 1.130 3.096 0.400 1.414 6.779 2.827 0.005 ** Purity 1.129 3.094 0.376 1.481 6.461 3.006 0.003 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.08e-06 Wald test p = 1.6e-06 Score (logrank) test p = 6.05e-07 FASN in STAD (n=415): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.132 0.876 0.099 0.721 1.065 -1.331 0.183 Age 0.027 1.028 0.010 1.007 1.049 2.673 0.008 ** Gendermale 0.132 1.142 0.207 0.760 1.714 0.638 0.523 RaceBlack 0.403 1.496 0.459 0.609 3.676 0.878 0.380 RaceWhite 0.137 1.147 0.247 0.708 1.860 0.558 0.577 Stage2 0.481 1.617 0.389 0.754 3.468 1.235 0.217 Stage3 0.923 2.517 0.363 1.236 5.127 2.544 0.011 * Stage4 1.283 3.607 0.505 1.341 9.706 2.540 0.011 * Purity -0.520 0.594 0.380 0.282 1.252 -1.369 0.171 Rsquare = 0.075 (max possible = 9.79e-01 ) Likelihood ratio test p = 7.32e-03 Wald test p = 9.97e-03 Score (logrank) test p = 7.75e-03 FASN in TGCT (n=150): Model: Surv(OS, EVENT) ~ `FASN` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 45.395 5.186516e+19 18470.081 0 Inf 0.002 0.998 Age 0.983 2.672000e+00 1872.451 0 Inf 0.001 1.000 RaceBlack -22.853 0.000000e+00 5932733.660 0 Inf 0.000 1.000 RaceWhite -76.677 0.000000e+00 5948596.585 0 Inf 0.000 1.000 Stage2 -45.082 0.000000e+00 45970.947 0 Inf -0.001 0.999 Stage3 39.098 9.552743e+16 109573.146 0 Inf 0.000 1.000 Purity -182.006 0.000000e+00 265748.073 0 Inf -0.001 0.999 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 2.73e-03 FASN in THCA (n=509): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.911 2.488 0.494 0.944 6.555 1.844 0.065 · Age 0.162 1.176 0.032 1.105 1.251 5.111 0.000 *** Gendermale -0.404 0.667 0.668 0.180 2.470 -0.606 0.545 RaceBlack 17.201 29540994.793 9162.331 0.000 Inf 0.002 0.999 RaceWhite 17.336 33803797.997 9162.331 0.000 Inf 0.002 0.998 Stage2 0.710 2.034 1.105 0.233 17.740 0.642 0.521 Stage3 0.296 1.344 0.846 0.256 7.057 0.350 0.727 Stage4 1.666 5.291 0.992 0.757 36.963 1.680 0.093 · Purity 2.195 8.979 1.075 1.091 73.873 2.041 0.041 * Rsquare = 0.157 (max possible = 3.47e-01 ) Likelihood ratio test p = 4.66e-11 Wald test p = 2.98e-04 Score (logrank) test p = 4.57e-11 FASN in THYM (n=120): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.217 1.243 0.427 0.538 2.869 0.509 0.611 Age 0.049 1.050 0.031 0.989 1.116 1.594 0.111 Gendermale -0.212 0.809 0.731 0.193 3.392 -0.290 0.772 RaceBlack -16.633 0.000 10096.672 0.000 Inf -0.002 0.999 RaceWhite 0.461 1.586 1.098 0.184 13.658 0.420 0.674 Purity 0.431 1.539 1.099 0.178 13.276 0.392 0.695 Rsquare = 0.046 (max possible = 4.51e-01 ) Likelihood ratio test p = 4.99e-01 Wald test p = 6.46e-01 Score (logrank) test p = 5.59e-01 FASN in UCEC (n=545): Model: Surv(OS, EVENT) ~ `FASN` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.101 1.107 0.163 0.805 1.522 0.624 0.533 Age 0.049 1.051 0.016 1.018 1.084 3.101 0.002 ** RaceBlack -0.373 0.689 0.797 0.144 3.285 -0.468 0.640 RaceWhite -0.474 0.623 0.749 0.143 2.704 -0.632 0.527 Purity 0.380 1.462 0.657 0.403 5.299 0.578 0.563 Rsquare = 0.04 (max possible = 7.81e-01 ) Likelihood ratio test p = 4.32e-02 Wald test p = 5.33e-02 Score (logrank) test p = 5.01e-02 FASN in UCS (n=57): Model: Surv(OS, EVENT) ~ `FASN` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN -0.179 0.836 0.258 0.505 1.386 -0.694 0.488 Age 0.048 1.049 0.025 0.999 1.102 1.921 0.055 · RaceBlack 17.703 48791624.103 6491.906 0.000 Inf 0.003 0.998 RaceWhite 17.887 58661362.844 6491.906 0.000 Inf 0.003 0.998 Purity -0.928 0.395 1.064 0.049 3.180 -0.872 0.383 Rsquare = 0.127 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.16e-01 Wald test p = 3.15e-01 Score (logrank) test p = 2.3e-01 FASN in UVM (n=80): Model: Surv(OS, EVENT) ~ `FASN` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif FASN 0.332 1.394 0.299 0.776 2.503 1.112 0.266 Age 0.042 1.043 0.020 1.004 1.084 2.158 0.031 * Gendermale 0.396 1.485 0.505 0.552 3.994 0.784 0.433 Stage3 0.129 1.138 0.524 0.407 3.177 0.246 0.806 Stage4 3.809 45.125 1.220 4.127 493.382 3.122 0.002 ** Purity 1.557 4.744 1.251 0.409 55.077 1.245 0.213 Rsquare = 0.265 (max possible = 8.72e-01 ) Likelihood ratio test p = 5.99e-04 Wald test p = 2.09e-03 Score (logrank) test p = 1.33e-09 IDH1 in ACC (n=79): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.729 2.073 0.256 1.255 3.424 2.847 0.004 ** Age 0.014 1.014 0.013 0.987 1.041 1.013 0.311 Gendermale 0.808 2.244 0.438 0.951 5.295 1.844 0.065 · RaceBlack -1.114 0.328 13125.604 0.000 Inf 0.000 1.000 RaceWhite 16.931 22542880.200 11285.933 0.000 Inf 0.002 0.999 Purity 0.987 2.683 2.237 0.033 215.092 0.441 0.659 Rsquare = 0.194 (max possible = 9.38e-01 ) Likelihood ratio test p = 3.15e-02 Wald test p = 9.86e-02 Score (logrank) test p = 6.09e-02 IDH1 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.057 0.945 0.063 0.834 1.070 -0.897 0.370 Age 0.034 1.034 0.009 1.017 1.052 3.936 0.000 *** Gendermale -0.168 0.845 0.178 0.596 1.199 -0.942 0.346 RaceBlack 0.695 2.004 0.446 0.836 4.806 1.558 0.119 RaceWhite 0.107 1.113 0.355 0.556 2.231 0.303 0.762 Stage2 14.398 1790570.346 1867.446 0.000 Inf 0.008 0.994 Stage3 14.821 2732969.391 1867.446 0.000 Inf 0.008 0.994 Stage4 15.370 4733203.111 1867.446 0.000 Inf 0.008 0.993 Purity 0.212 1.237 0.347 0.626 2.443 0.611 0.541 Rsquare = 0.132 (max possible = 9.91e-01 ) Likelihood ratio test p = 1.43e-07 Wald test p = 8.99e-07 Score (logrank) test p = 2.49e-07 IDH1 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.003 1.003 0.114 0.801 1.254 0.024 0.981 Age 0.036 1.036 0.008 1.021 1.052 4.732 0.000 *** Gendermale 0.042 1.043 1.007 0.145 7.517 0.042 0.966 RaceBlack 0.001 1.001 0.619 0.297 3.368 0.002 0.999 RaceWhite -0.223 0.800 0.597 0.248 2.575 -0.375 0.708 Stage2 0.409 1.505 0.304 0.829 2.730 1.344 0.179 Stage3 1.189 3.282 0.313 1.776 6.066 3.794 0.000 *** Stage4 2.516 12.373 0.391 5.751 26.618 6.436 0.000 *** Purity 0.514 1.672 0.422 0.731 3.824 1.218 0.223 Rsquare = 0.081 (max possible = 7.85e-01 ) Likelihood ratio test p = 2.48e-12 Wald test p = 6.86e-16 Score (logrank) test p = 8.63e-22 IDH1 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.481 6.180000e-01 0.291 0.349 1.094 -1.652 0.099 · Age 0.019 1.019000e+00 0.019 0.983 1.057 1.027 0.304 RaceBlack -0.650 5.220000e-01 1.114 0.059 4.638 -0.583 0.560 RaceWhite -0.789 4.540000e-01 1.133 0.049 4.188 -0.696 0.486 Stage2 18.579 1.171928e+08 6539.570 0.000 Inf 0.003 0.998 Stage3 19.998 4.842349e+08 6539.570 0.000 Inf 0.003 0.998 Stage4 21.341 1.855419e+09 6539.570 0.000 Inf 0.003 0.997 Purity 0.633 1.884000e+00 0.954 0.290 12.225 0.664 0.507 Rsquare = 0.171 (max possible = 7.18e-01 ) Likelihood ratio test p = 1.64e-04 Wald test p = 4.25e-03 Score (logrank) test p = 1.59e-06 IDH1 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.437 1.549000e+00 0.552 0.525 4.571 0.792 0.428 Age 0.021 1.021000e+00 0.031 0.961 1.085 0.673 0.501 RaceBlack -2.722 6.600000e-02 1.817 0.002 2.317 -1.498 0.134 RaceWhite -1.466 2.310000e-01 1.481 0.013 4.203 -0.990 0.322 Stage2 18.006 6.606678e+07 15595.709 0.000 Inf 0.001 0.999 Stage3 19.857 4.204208e+08 15595.709 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 3.374 2.920200e+01 2.386 0.272 3136.949 1.414 0.157 Rsquare = 0.377 (max possible = 6.68e-01 ) Likelihood ratio test p = 2.32e-04 Wald test p = 2.21e-01 Score (logrank) test p = 9.26e-15 IDH1 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.055 0.947 0.177 0.669 1.340 -0.308 0.758 Age 0.049 1.050 0.012 1.026 1.075 4.104 0.000 *** Gendermale -15.355 0.000 3459.618 0.000 Inf -0.004 0.996 RaceBlack -0.444 0.641 1.175 0.064 6.420 -0.378 0.705 RaceWhite 0.268 1.308 1.034 0.172 9.934 0.260 0.795 Stage2 0.314 1.369 0.376 0.655 2.859 0.835 0.404 Stage3 0.845 2.327 0.397 1.069 5.068 2.127 0.033 * Stage4 2.125 8.376 0.597 2.600 26.988 3.561 0.000 *** Purity 0.301 1.351 0.612 0.407 4.486 0.491 0.624 Rsquare = 0.07 (max possible = 6.81e-01 ) Likelihood ratio test p = 1e-04 Wald test p = 1.98e-05 Score (logrank) test p = 3.95e-07 IDH1 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.118 1.125 0.262 0.673 1.882 0.450 0.653 Age 0.052 1.053 0.021 1.010 1.098 2.410 0.016 * Gendermale 1.054 2.870 1.118 0.321 25.668 0.943 0.346 RaceBlack 16.595 16103648.239 6517.914 0.000 Inf 0.003 0.998 RaceWhite 15.925 8243220.425 6517.914 0.000 Inf 0.002 0.998 Stage2 0.678 1.969 1.072 0.241 16.094 0.632 0.527 Stage3 1.565 4.784 1.063 0.596 38.396 1.473 0.141 Stage4 2.083 8.032 1.172 0.807 79.943 1.777 0.076 · Purity 1.145 3.141 1.340 0.227 43.399 0.854 0.393 Rsquare = 0.106 (max possible = 6.98e-01 ) Likelihood ratio test p = 3.94e-02 Wald test p = 6.86e-02 Score (logrank) test p = 2.36e-02 IDH1 in CESC (n=306): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.002 0.998 0.140 0.759 1.313 -0.013 0.990 Age 0.011 1.011 0.010 0.991 1.032 1.108 0.268 RaceBlack 1.045 2.843 1.079 0.343 23.570 0.968 0.333 RaceWhite 0.820 2.270 1.025 0.304 16.922 0.800 0.424 Purity 0.575 1.777 0.738 0.418 7.553 0.778 0.436 Rsquare = 0.014 (max possible = 8.91e-01 ) Likelihood ratio test p = 6.8e-01 Wald test p = 7.15e-01 Score (logrank) test p = 7.07e-01 IDH1 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.380 1.462 0.450 0.605 3.535 0.843 0.399 Age 0.013 1.014 0.023 0.969 1.061 0.580 0.562 Gendermale 0.253 1.288 0.552 0.437 3.800 0.459 0.646 RaceBlack -0.778 0.459 1.594 0.020 10.443 -0.488 0.625 RaceWhite -1.209 0.298 0.921 0.049 1.813 -1.314 0.189 Stage2 0.699 2.011 0.675 0.535 7.557 1.034 0.301 Stage3 -13.935 0.000 6966.541 0.000 Inf -0.002 0.998 Stage4 0.768 2.156 0.664 0.587 7.922 1.157 0.247 Purity 2.869 17.614 1.951 0.385 806.750 1.470 0.142 Rsquare = 0.227 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.13e-01 Wald test p = 6.17e-01 Score (logrank) test p = 4.37e-01 IDH1 in COAD (n=458): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.183 0.833 0.246 0.514 1.350 -0.741 0.459 Age 0.024 1.024 0.011 1.001 1.047 2.046 0.041 * Gendermale 0.234 1.263 0.272 0.742 2.152 0.861 0.389 RaceBlack -0.447 0.640 0.829 0.126 3.248 -0.539 0.590 RaceWhite -0.497 0.608 0.780 0.132 2.806 -0.638 0.524 Stage2 0.212 1.237 0.562 0.411 3.723 0.378 0.706 Stage3 0.784 2.190 0.550 0.745 6.439 1.425 0.154 Stage4 1.849 6.350 0.554 2.144 18.810 3.337 0.001 ** Purity -0.246 0.782 0.600 0.241 2.533 -0.411 0.681 Rsquare = 0.111 (max possible = 9.04e-01 ) Likelihood ratio test p = 3.76e-04 Wald test p = 1.31e-04 Score (logrank) test p = 1.95e-05 IDH1 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 1.418 4.129 0.716 1.015 16.793 1.981 0.048 * Age -0.024 0.976 0.048 0.888 1.073 -0.502 0.616 Gendermale -0.118 0.888 1.282 0.072 10.969 -0.092 0.927 RaceBlack 1.206 3.340 2.030 0.062 178.575 0.594 0.552 RaceWhite -3.149 0.043 1.571 0.002 0.932 -2.005 0.045 * Purity -1.817 0.163 2.604 0.001 26.771 -0.698 0.485 Rsquare = 0.224 (max possible = 5.58e-01 ) Likelihood ratio test p = 1.09e-01 Wald test p = 2.04e-01 Score (logrank) test p = 1.08e-01 IDH1 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.146 0.864 0.161 0.630 1.184 -0.909 0.363 Age 0.011 1.011 0.014 0.984 1.040 0.800 0.423 Gendermale 0.595 1.813 0.551 0.615 5.341 1.079 0.280 RaceBlack 0.346 1.414 1.069 0.174 11.480 0.324 0.746 RaceWhite -0.119 0.888 0.450 0.368 2.144 -0.265 0.791 Stage2 0.640 1.897 0.657 0.523 6.875 0.974 0.330 Stage3 1.398 4.046 0.671 1.086 15.065 2.084 0.037 * Stage4 2.863 17.518 0.769 3.878 79.125 3.722 0.000 *** Purity 0.307 1.359 0.782 0.293 6.294 0.392 0.695 Rsquare = 0.146 (max possible = 9.32e-01 ) Likelihood ratio test p = 8.59e-03 Wald test p = 3.64e-03 Score (logrank) test p = 3e-04 IDH1 in GBM (n=153): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.049 1.050 0.190 0.724 1.523 0.256 0.798 Age 0.029 1.030 0.008 1.013 1.047 3.504 0.000 *** Gendermale -0.081 0.922 0.220 0.599 1.419 -0.369 0.712 RaceBlack 0.540 1.716 0.728 0.412 7.153 0.741 0.459 RaceWhite -0.243 0.785 0.614 0.235 2.616 -0.395 0.693 Purity -1.098 0.334 0.534 0.117 0.949 -2.058 0.040 * Rsquare = 0.129 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.68e-03 Wald test p = 6.76e-03 Score (logrank) test p = 5.92e-03 IDH1 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.071 1.074 0.090 0.900 1.282 0.788 0.431 Age 0.022 1.022 0.008 1.007 1.037 2.815 0.005 ** Gendermale -0.254 0.776 0.172 0.554 1.086 -1.477 0.140 RaceBlack 0.102 1.107 0.560 0.370 3.317 0.182 0.855 RaceWhite -0.264 0.768 0.511 0.282 2.092 -0.516 0.606 Stage2 0.597 1.817 0.544 0.625 5.279 1.097 0.273 Stage3 0.835 2.304 0.537 0.804 6.601 1.554 0.120 Stage4 1.228 3.415 0.511 1.254 9.298 2.403 0.016 * Purity -0.068 0.934 0.365 0.457 1.910 -0.187 0.852 Rsquare = 0.071 (max possible = 9.89e-01 ) Likelihood ratio test p = 4.13e-04 Wald test p = 1.06e-03 Score (logrank) test p = 7.72e-04 IDH1 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.046 1.047000e+00 0.336 0.543 2.021 0.137 0.891 Age 0.011 1.011000e+00 0.025 0.962 1.063 0.435 0.663 Gendermale -0.165 8.480000e-01 0.544 0.292 2.459 -0.304 0.761 RaceBlack 18.917 1.642500e+08 12032.395 0.000 Inf 0.002 0.999 RaceWhite 18.114 7.355613e+07 12032.395 0.000 Inf 0.002 0.999 Stage2 17.424 3.690578e+07 5289.545 0.000 Inf 0.003 0.997 Stage3 16.556 1.549304e+07 5289.545 0.000 Inf 0.003 0.998 Stage4 17.469 3.859476e+07 5289.545 0.000 Inf 0.003 0.997 Purity -1.569 2.080000e-01 1.065 0.026 1.680 -1.473 0.141 Rsquare = 0.087 (max possible = 9.17e-01 ) Likelihood ratio test p = 7.46e-01 Wald test p = 9.54e-01 Score (logrank) test p = 8.68e-01 IDH1 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.046 1.047 0.096 0.868 1.263 0.477 0.633 Age 0.026 1.027 0.009 1.010 1.044 3.083 0.002 ** Gendermale -0.287 0.751 0.183 0.525 1.074 -1.569 0.117 RaceBlack -0.040 0.960 0.566 0.317 2.911 -0.072 0.943 RaceWhite -0.407 0.665 0.513 0.244 1.818 -0.794 0.427 Stage2 0.359 1.432 0.554 0.484 4.241 0.648 0.517 Stage3 0.721 2.057 0.541 0.712 5.939 1.333 0.183 Stage4 1.131 3.099 0.513 1.134 8.471 2.204 0.027 * Purity 0.183 1.201 0.404 0.544 2.650 0.453 0.650 Rsquare = 0.085 (max possible = 9.89e-01 ) Likelihood ratio test p = 3.11e-04 Wald test p = 8.5e-04 Score (logrank) test p = 6.42e-04 IDH1 in KICH (n=66): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p IDH1 2.281 9.789 0.604 2.998 3.196400e+01 3.778 0.000 Age 0.077 1.080 0.031 1.017 1.147000e+00 2.514 0.012 Gendermale -0.714 0.489 0.734 0.116 2.063000e+00 -0.973 0.330 RaceBlack -11.692 0.000 5598.938 0.000 Inf -0.002 0.998 RaceWhite 1.295 3.652 1.159 0.377 3.539200e+01 1.118 0.264 Stage2 15.639 6191764.203 0.832 1211159.895 3.165391e+07 18.786 0.000 Stage3 17.318 33194737.979 0.796 6967930.014 1.581374e+08 21.743 0.000 Stage4 17.719 49554575.990 0.888 8701233.341 2.822193e+08 19.963 0.000 Purity 6.696 809.375 4.174 0.226 2.892983e+06 1.604 0.109 signif IDH1 *** Age * Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.406 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.44e-04 Wald test p = 2.44e-263 Score (logrank) test p = 3.7e-09 IDH1 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.002 1.002 0.136 0.768 1.307 0.012 0.990 Age 0.035 1.036 0.008 1.019 1.053 4.156 0.000 *** Gendermale -0.082 0.921 0.185 0.641 1.324 -0.444 0.657 RaceBlack 0.204 1.226 1.057 0.154 9.731 0.193 0.847 RaceWhite 0.153 1.165 1.014 0.160 8.501 0.151 0.880 Stage2 0.215 1.240 0.345 0.631 2.437 0.623 0.533 Stage3 0.811 2.251 0.230 1.434 3.533 3.528 0.000 *** Stage4 1.759 5.806 0.217 3.797 8.879 8.117 0.000 *** Purity -0.002 0.998 0.384 0.470 2.118 -0.006 0.995 Rsquare = 0.174 (max possible = 9.65e-01 ) Likelihood ratio test p = 1.04e-14 Wald test p = 1.07e-14 Score (logrank) test p = 5.73e-18 IDH1 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.654 1.923 0.287 1.095 3.378 2.275 0.023 * Age 0.008 1.008 0.016 0.978 1.040 0.520 0.603 Gendermale -0.385 0.680 0.393 0.315 1.470 -0.980 0.327 RaceBlack -1.449 0.235 1.229 0.021 2.613 -1.178 0.239 RaceWhite -1.572 0.208 1.214 0.019 2.244 -1.294 0.196 Stage2 -0.584 0.558 1.056 0.070 4.422 -0.553 0.580 Stage3 1.580 4.855 0.430 2.092 11.268 3.678 0.000 *** Stage4 2.737 15.433 0.518 5.596 42.563 5.287 0.000 *** Purity -0.078 0.925 0.752 0.212 4.041 -0.104 0.918 Rsquare = 0.182 (max possible = 7.58e-01 ) Likelihood ratio test p = 1.4e-06 Wald test p = 1.26e-06 Score (logrank) test p = 1.22e-10 IDH1 in LAML (n=173): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.250 1.284 0.149 0.959 1.720 1.679 0.093 · Age 0.038 1.039 0.008 1.022 1.055 4.664 0.000 *** Gendermale -0.154 0.857 0.212 0.566 1.298 -0.727 0.467 RaceBlack -0.043 0.958 1.120 0.107 8.602 -0.039 0.969 RaceWhite -0.439 0.644 1.029 0.086 4.841 -0.427 0.669 Rsquare = 0.172 (max possible = 9.96e-01 ) Likelihood ratio test p = 3.46e-05 Wald test p = 1.34e-04 Score (logrank) test p = 8.24e-05 IDH1 in LGG (n=516): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.675 1.964 0.170 1.409 2.739 3.981 0.000 *** Age 0.064 1.066 0.008 1.049 1.082 8.101 0.000 *** Gendermale 0.200 1.222 0.197 0.831 1.796 1.018 0.309 RaceBlack 15.949 8442871.562 1982.645 0.000 Inf 0.008 0.994 RaceWhite 15.643 6218048.501 1982.645 0.000 Inf 0.008 0.994 Purity -1.424 0.241 0.416 0.106 0.544 -3.422 0.001 ** Rsquare = 0.166 (max possible = 9.07e-01 ) Likelihood ratio test p = 4.98e-16 Wald test p = 3.07e-15 Score (logrank) test p = 1.13e-16 IDH1 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.122 1.129 0.125 0.885 1.442 0.978 0.328 Age 0.012 1.012 0.008 0.996 1.028 1.435 0.151 Gendermale -0.151 0.860 0.226 0.552 1.340 -0.666 0.505 RaceBlack 0.809 2.246 0.496 0.850 5.934 1.633 0.103 RaceWhite -0.030 0.970 0.239 0.608 1.550 -0.126 0.900 Stage2 0.322 1.379 0.261 0.827 2.299 1.233 0.217 Stage3 0.912 2.490 0.238 1.561 3.972 3.830 0.000 *** Stage4 1.585 4.877 0.619 1.450 16.406 2.560 0.010 * Purity 0.490 1.633 0.464 0.658 4.055 1.057 0.291 Rsquare = 0.087 (max possible = 9.66e-01 ) Likelihood ratio test p = 8.29e-04 Wald test p = 4.72e-04 Score (logrank) test p = 1.74e-04 IDH1 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.133 1.142 0.107 0.925 1.410 1.238 0.216 Age 0.006 1.006 0.009 0.989 1.024 0.717 0.474 Gendermale -0.014 0.986 0.171 0.706 1.379 -0.081 0.936 RaceBlack 16.199 10847750.864 1834.638 0.000 Inf 0.009 0.993 RaceWhite 16.352 12630682.205 1834.638 0.000 Inf 0.009 0.993 Stage2 0.872 2.392 0.201 1.613 3.549 4.334 0.000 *** Stage3 1.016 2.763 0.218 1.803 4.235 4.664 0.000 *** Stage4 0.953 2.594 0.337 1.340 5.021 2.827 0.005 ** Purity 0.553 1.738 0.345 0.884 3.419 1.602 0.109 Rsquare = 0.1 (max possible = 9.74e-01 ) Likelihood ratio test p = 1.27e-06 Wald test p = 1.7e-05 Score (logrank) test p = 2.28e-06 IDH1 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.014 0.986 0.095 0.818 1.188 -0.148 0.882 Age 0.016 1.017 0.009 0.998 1.035 1.754 0.079 · Gendermale 0.438 1.550 0.194 1.060 2.267 2.259 0.024 * RaceBlack 0.002 1.002 0.607 0.305 3.296 0.003 0.997 RaceWhite -0.520 0.594 0.563 0.197 1.793 -0.924 0.356 Stage2 0.211 1.235 0.187 0.857 1.781 1.131 0.258 Stage3 0.603 1.828 0.214 1.201 2.783 2.816 0.005 ** Stage4 0.750 2.116 0.797 0.444 10.098 0.940 0.347 Purity -0.348 0.706 0.366 0.345 1.445 -0.953 0.341 Rsquare = 0.05 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.41e-02 Wald test p = 1.86e-02 Score (logrank) test p = 1.61e-02 IDH1 in MESO (n=87): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.056 0.946 0.178 0.667 1.340 -0.315 0.753 Age 0.020 1.020 0.016 0.989 1.052 1.255 0.210 Gendermale -0.152 0.859 0.337 0.443 1.664 -0.451 0.652 RaceBlack 0.215 1.240 1.550 0.059 25.845 0.139 0.890 RaceWhite -0.478 0.620 1.049 0.079 4.848 -0.456 0.649 Stage2 -0.208 0.812 0.476 0.319 2.066 -0.437 0.662 Stage3 -0.094 0.910 0.421 0.399 2.076 -0.224 0.823 Stage4 -0.117 0.890 0.489 0.341 2.320 -0.239 0.811 Purity -0.779 0.459 0.558 0.154 1.369 -1.397 0.162 Rsquare = 0.061 (max possible = 9.98e-01 ) Likelihood ratio test p = 8.02e-01 Wald test p = 7.79e-01 Score (logrank) test p = 7.72e-01 IDH1 in OV (n=303): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.070 1.073 0.132 0.828 1.390 0.531 0.595 Age 0.036 1.037 0.008 1.021 1.054 4.454 0.000 *** RaceBlack -0.024 0.976 0.579 0.314 3.035 -0.042 0.966 RaceWhite -0.146 0.864 0.515 0.315 2.372 -0.284 0.777 Purity -0.580 0.560 0.671 0.150 2.083 -0.865 0.387 Rsquare = 0.082 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.02e-03 Wald test p = 9.35e-04 Score (logrank) test p = 7.77e-04 IDH1 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.060 1.061 0.147 0.795 1.417 0.405 0.685 Age 0.022 1.022 0.011 1.001 1.044 2.009 0.045 * Gendermale -0.209 0.811 0.217 0.530 1.242 -0.961 0.336 RaceBlack -0.012 0.989 0.738 0.233 4.199 -0.016 0.988 RaceWhite 0.375 1.455 0.476 0.572 3.697 0.787 0.431 Stage2 0.616 1.851 0.437 0.786 4.358 1.408 0.159 Stage3 -0.187 0.830 1.098 0.096 7.144 -0.170 0.865 Stage4 0.198 1.219 0.829 0.240 6.190 0.239 0.811 Purity -0.633 0.531 0.419 0.234 1.207 -1.511 0.131 Rsquare = 0.089 (max possible = 9.91e-01 ) Likelihood ratio test p = 7.92e-02 Wald test p = 1.19e-01 Score (logrank) test p = 1.13e-01 IDH1 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.349 0.705 0.737 0.166 2.988 -0.474 0.635 Age 0.035 1.036 0.029 0.978 1.096 1.205 0.228 Gendermale 1.438 4.211 0.897 0.726 24.439 1.603 0.109 RaceBlack 0.014 1.014 19604.292 0.000 Inf 0.000 1.000 RaceWhite 17.347 34186562.286 15269.748 0.000 Inf 0.001 0.999 Purity 5.497 243.978 3.298 0.380 156465.541 1.667 0.096 · Rsquare = 0.056 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.5e-01 Wald test p = 4.04e-01 Score (logrank) test p = 3.01e-01 IDH1 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.867 2.380 0.484 0.922 6.147 1.791 0.073 · Age 0.033 1.033 0.059 0.921 1.160 0.559 0.576 RaceBlack 16.810 19983110.422 10652.457 0.000 Inf 0.002 0.999 RaceWhite 17.403 36155029.246 10652.457 0.000 Inf 0.002 0.999 Purity 1.485 4.415 1.424 0.271 71.972 1.043 0.297 Rsquare = 0.017 (max possible = 1.83e-01 ) Likelihood ratio test p = 2.42e-01 Wald test p = 3.46e-01 Score (logrank) test p = 2.48e-01 IDH1 in READ (n=166): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.025 1.025 0.423 0.447 2.350 0.059 0.953 Age 0.111 1.117 0.047 1.018 1.225 2.345 0.019 * Gendermale -0.353 0.703 0.690 0.182 2.715 -0.512 0.609 RaceBlack 13.461 701670.863 10544.307 0.000 Inf 0.001 0.999 RaceWhite 12.431 250500.074 10544.307 0.000 Inf 0.001 0.999 Stage2 -1.840 0.159 1.261 0.013 1.878 -1.460 0.144 Stage3 -0.469 0.625 0.922 0.103 3.809 -0.509 0.611 Stage4 -0.140 0.870 0.964 0.131 5.756 -0.145 0.885 Purity 0.147 1.158 1.352 0.082 16.384 0.109 0.913 Rsquare = 0.209 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.7e-02 Wald test p = 2.44e-01 Score (logrank) test p = 3.9e-02 IDH1 in SARC (n=260): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.189 0.828 0.143 0.626 1.096 -1.320 0.187 Age 0.024 1.024 0.008 1.007 1.041 2.848 0.004 ** Gendermale -0.031 0.969 0.223 0.626 1.502 -0.140 0.889 RaceBlack -0.216 0.805 1.089 0.095 6.802 -0.199 0.842 RaceWhite -0.526 0.591 1.024 0.079 4.399 -0.513 0.608 Purity 0.607 1.835 0.611 0.554 6.081 0.993 0.321 Rsquare = 0.05 (max possible = 9.75e-01 ) Likelihood ratio test p = 6.57e-02 Wald test p = 8.08e-02 Score (logrank) test p = 7.83e-02 IDH1 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.095 1.100 0.099 0.906 1.334 0.962 0.336 Age 0.018 1.018 0.005 1.008 1.029 3.513 0.000 *** Gendermale -0.046 0.955 0.157 0.701 1.299 -0.295 0.768 RaceWhite -1.330 0.264 0.404 0.120 0.584 -3.290 0.001 ** Stage2 0.278 1.320 0.218 0.861 2.024 1.274 0.203 Stage3 0.613 1.846 0.204 1.238 2.754 3.006 0.003 ** Stage4 1.362 3.905 0.352 1.958 7.786 3.868 0.000 *** Purity 1.072 2.921 0.345 1.485 5.747 3.106 0.002 ** Rsquare = 0.125 (max possible = 9.92e-01 ) Likelihood ratio test p = 1.48e-08 Wald test p = 9.59e-09 Score (logrank) test p = 1.05e-09 IDH1 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.263 1.300000e+00 0.242 0.810 2.088 1.087 0.277 Age 0.013 1.013000e+00 0.016 0.982 1.044 0.815 0.415 Gendermale 0.101 1.107000e+00 0.447 0.461 2.655 0.227 0.821 RaceWhite -1.298 2.730000e-01 0.626 0.080 0.931 -2.075 0.038 * Stage2 17.427 3.700690e+07 6259.930 0.000 Inf 0.003 0.998 Stage3 17.980 6.437966e+07 6259.930 0.000 Inf 0.003 0.998 Stage4 19.751 3.782723e+08 6259.930 0.000 Inf 0.003 0.997 Purity 0.074 1.077000e+00 0.953 0.166 6.975 0.078 0.938 Rsquare = 0.157 (max possible = 8.69e-01 ) Likelihood ratio test p = 4.16e-02 Wald test p = 4.18e-02 Score (logrank) test p = 3.03e-03 IDH1 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.086 1.090 0.109 0.881 1.349 0.791 0.429 Age 0.020 1.021 0.006 1.009 1.032 3.613 0.000 *** Gendermale -0.051 0.950 0.172 0.678 1.332 -0.296 0.767 RaceWhite -1.098 0.334 0.602 0.103 1.085 -1.824 0.068 · Stage2 0.153 1.166 0.230 0.743 1.829 0.666 0.505 Stage3 0.565 1.759 0.209 1.168 2.650 2.704 0.007 ** Stage4 1.154 3.172 0.401 1.446 6.958 2.880 0.004 ** Purity 1.202 3.325 0.378 1.586 6.973 3.181 0.001 ** Rsquare = 0.135 (max possible = 9.95e-01 ) Likelihood ratio test p = 8.42e-07 Wald test p = 1.54e-06 Score (logrank) test p = 5.59e-07 IDH1 in STAD (n=415): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.166 0.847 0.120 0.669 1.073 -1.375 0.169 Age 0.028 1.028 0.010 1.008 1.049 2.707 0.007 ** Gendermale 0.168 1.183 0.210 0.784 1.785 0.801 0.423 RaceBlack 0.349 1.418 0.452 0.585 3.439 0.773 0.440 RaceWhite 0.125 1.133 0.246 0.700 1.833 0.508 0.611 Stage2 0.571 1.769 0.395 0.816 3.838 1.444 0.149 Stage3 0.979 2.663 0.366 1.299 5.458 2.674 0.007 ** Stage4 1.391 4.017 0.507 1.487 10.856 2.742 0.006 ** Purity -0.526 0.591 0.378 0.282 1.239 -1.393 0.164 Rsquare = 0.075 (max possible = 9.79e-01 ) Likelihood ratio test p = 7.02e-03 Wald test p = 1.06e-02 Score (logrank) test p = 8.09e-03 IDH1 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 10.818 49899.896 21796.023 0 Inf 0.000 1.000 Age -1.511 0.221 1702.462 0 Inf -0.001 0.999 RaceBlack 6.417 611.961 17790413.356 0 Inf 0.000 1.000 RaceWhite -41.603 0.000 18499591.065 0 Inf 0.000 1.000 Stage2 -17.941 0.000 43053.592 0 Inf 0.000 1.000 Stage3 15.747 6900249.829 118248.719 0 Inf 0.000 1.000 Purity -7.868 0.000 232591.391 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.26e-03 IDH1 in THCA (n=509): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.975 2.651 0.498 0.999 7.034 1.959 0.050 · Age 0.156 1.168 0.029 1.103 1.237 5.300 0.000 *** Gendermale -0.117 0.890 0.622 0.263 3.009 -0.188 0.851 RaceBlack 17.742 50704845.642 8659.813 0.000 Inf 0.002 0.998 RaceWhite 16.948 22938293.187 8659.813 0.000 Inf 0.002 0.998 Stage2 0.687 1.988 1.131 0.217 18.246 0.608 0.543 Stage3 0.392 1.480 0.871 0.269 8.152 0.450 0.653 Stage4 1.813 6.127 1.009 0.848 44.277 1.797 0.072 · Purity 3.730 41.686 1.528 2.086 832.938 2.441 0.015 * Rsquare = 0.159 (max possible = 3.47e-01 ) Likelihood ratio test p = 3.25e-11 Wald test p = 2.04e-04 Score (logrank) test p = 6.04e-11 IDH1 in THYM (n=120): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.873 2.395 0.571 0.782 7.337 1.529 0.126 Age 0.036 1.037 0.031 0.976 1.101 1.163 0.245 Gendermale -0.110 0.896 0.717 0.220 3.650 -0.153 0.878 RaceBlack -15.900 0.000 10694.208 0.000 Inf -0.001 0.999 RaceWhite 1.018 2.769 1.186 0.271 28.290 0.859 0.390 Purity 0.266 1.305 1.124 0.144 11.806 0.237 0.813 Rsquare = 0.067 (max possible = 4.51e-01 ) Likelihood ratio test p = 2.5e-01 Wald test p = 4.39e-01 Score (logrank) test p = 3.35e-01 IDH1 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.024 1.024 0.134 0.787 1.333 0.177 0.859 Age 0.050 1.051 0.016 1.019 1.084 3.165 0.002 ** RaceBlack -0.415 0.660 0.794 0.139 3.127 -0.523 0.601 RaceWhite -0.531 0.588 0.745 0.136 2.536 -0.712 0.477 Purity 0.446 1.562 0.645 0.441 5.534 0.691 0.490 Rsquare = 0.038 (max possible = 7.81e-01 ) Likelihood ratio test p = 4.97e-02 Wald test p = 5.87e-02 Score (logrank) test p = 5.73e-02 IDH1 in UCS (n=57): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 -0.026 0.975 0.271 0.573 1.657 -0.095 0.924 Age 0.044 1.045 0.025 0.996 1.097 1.783 0.075 · RaceBlack 17.560 42302672.829 6474.148 0.000 Inf 0.003 0.998 RaceWhite 17.813 54443076.499 6474.148 0.000 Inf 0.003 0.998 Purity -0.877 0.416 1.058 0.052 3.310 -0.829 0.407 Rsquare = 0.119 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.53e-01 Wald test p = 3.6e-01 Score (logrank) test p = 2.66e-01 IDH1 in UVM (n=80): Model: Surv(OS, EVENT) ~ `IDH1` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif IDH1 0.182 1.200 0.303 0.663 2.174 0.602 0.547 Age 0.041 1.041 0.019 1.003 1.081 2.135 0.033 * Gendermale 0.252 1.287 0.480 0.502 3.300 0.525 0.600 Stage3 0.288 1.334 0.502 0.499 3.566 0.574 0.566 Stage4 3.813 45.278 1.218 4.160 492.812 3.130 0.002 ** Purity 2.072 7.941 1.266 0.664 95.019 1.636 0.102 Rsquare = 0.256 (max possible = 8.72e-01 ) Likelihood ratio test p = 8.64e-04 Wald test p = 3.73e-03 Score (logrank) test p = 2.6e-09 PDHA1 in ACC (n=79): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -1.000 0.368 0.390 0.171 0.790 -2.563 0.010 * Age 0.011 1.011 0.014 0.985 1.039 0.840 0.401 Gendermale 0.481 1.617 0.415 0.717 3.647 1.159 0.247 RaceBlack -2.125 0.119 12908.403 0.000 Inf 0.000 1.000 RaceWhite 15.434 5045040.264 11014.520 0.000 Inf 0.001 0.999 Purity 2.447 11.551 2.198 0.155 858.849 1.113 0.266 Rsquare = 0.164 (max possible = 9.38e-01 ) Likelihood ratio test p = 7.57e-02 Wald test p = 1.85e-01 Score (logrank) test p = 1.02e-01 PDHA1 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.077 0.926 0.156 0.683 1.256 -0.496 0.620 Age 0.034 1.034 0.009 1.017 1.052 3.904 0.000 *** Gendermale -0.173 0.841 0.178 0.593 1.194 -0.968 0.333 RaceBlack 0.734 2.083 0.448 0.865 5.012 1.637 0.102 RaceWhite 0.129 1.138 0.356 0.567 2.285 0.364 0.716 Stage2 14.460 1905544.760 1864.094 0.000 Inf 0.008 0.994 Stage3 14.887 2920154.094 1864.094 0.000 Inf 0.008 0.994 Stage4 15.442 5083700.318 1864.094 0.000 Inf 0.008 0.993 Purity 0.161 1.175 0.340 0.603 2.288 0.474 0.635 Rsquare = 0.131 (max possible = 9.91e-01 ) Likelihood ratio test p = 1.82e-07 Wald test p = 1.21e-06 Score (logrank) test p = 3.27e-07 PDHA1 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.319 1.376 0.171 0.984 1.923 1.867 0.062 · Age 0.036 1.037 0.008 1.022 1.052 4.812 0.000 *** Gendermale 0.073 1.075 1.007 0.149 7.745 0.072 0.943 RaceBlack -0.151 0.860 0.626 0.252 2.936 -0.240 0.810 RaceWhite -0.286 0.751 0.597 0.233 2.422 -0.479 0.632 Stage2 0.358 1.430 0.306 0.786 2.603 1.171 0.242 Stage3 1.177 3.244 0.313 1.757 5.992 3.760 0.000 *** Stage4 2.497 12.149 0.389 5.671 26.029 6.424 0.000 *** Purity 0.423 1.526 0.427 0.661 3.520 0.991 0.322 Rsquare = 0.084 (max possible = 7.85e-01 ) Likelihood ratio test p = 5.47e-13 Wald test p = 8.98e-17 Score (logrank) test p = 1.26e-22 PDHA1 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.156 8.560000e-01 0.378 0.408 1.794 -0.413 0.680 Age 0.011 1.011000e+00 0.018 0.977 1.046 0.617 0.537 RaceBlack -0.782 4.580000e-01 1.155 0.048 4.402 -0.677 0.499 RaceWhite -1.145 3.180000e-01 1.142 0.034 2.983 -1.003 0.316 Stage2 18.707 1.331931e+08 6473.783 0.000 Inf 0.003 0.998 Stage3 20.111 5.420742e+08 6473.783 0.000 Inf 0.003 0.998 Stage4 21.353 1.877621e+09 6473.783 0.000 Inf 0.003 0.997 Purity 0.844 2.326000e+00 0.991 0.333 16.241 0.852 0.394 Rsquare = 0.157 (max possible = 7.18e-01 ) Likelihood ratio test p = 4.87e-04 Wald test p = 7.08e-03 Score (logrank) test p = 4.52e-06 PDHA1 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.670 5.120000e-01 0.658 0.141 1.858 -1.018 0.308 Age 0.041 1.042000e+00 0.029 0.984 1.104 1.407 0.160 RaceBlack -2.750 6.400000e-02 1.804 0.002 2.193 -1.525 0.127 RaceWhite -1.476 2.290000e-01 1.462 0.013 4.014 -1.009 0.313 Stage2 18.102 7.269431e+07 14813.779 0.000 Inf 0.001 0.999 Stage3 19.690 3.557786e+08 14813.779 0.000 Inf 0.001 0.999 Stage4 52.586 6.880817e+22 1969267.737 0.000 Inf 0.000 1.000 Purity 3.046 2.103900e+01 2.409 0.187 2365.309 1.264 0.206 Rsquare = 0.383 (max possible = 6.68e-01 ) Likelihood ratio test p = 3.92e-04 Wald test p = 1e+00 Score (logrank) test p = 2.99e-14 PDHA1 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 1.024 2.785 0.424 1.213 6.391 2.416 0.016 * Age 0.048 1.050 0.012 1.025 1.075 3.990 0.000 *** Gendermale -15.411 0.000 3479.044 0.000 Inf -0.004 0.996 RaceBlack -0.506 0.603 1.178 0.060 6.063 -0.430 0.667 RaceWhite 0.053 1.055 1.039 0.138 8.076 0.051 0.959 Stage2 0.248 1.282 0.375 0.615 2.672 0.662 0.508 Stage3 0.833 2.300 0.393 1.064 4.973 2.117 0.034 * Stage4 2.119 8.320 0.591 2.613 26.488 3.586 0.000 *** Purity -0.079 0.924 0.658 0.254 3.353 -0.121 0.904 Rsquare = 0.081 (max possible = 6.81e-01 ) Likelihood ratio test p = 1.06e-05 Wald test p = 3.99e-06 Score (logrank) test p = 4.65e-08 PDHA1 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.384 1.469 0.560 0.490 4.398 0.687 0.492 Age 0.050 1.051 0.021 1.008 1.096 2.327 0.020 * Gendermale 0.993 2.699 1.106 0.309 23.574 0.898 0.369 RaceBlack 16.561 15568300.328 6485.222 0.000 Inf 0.003 0.998 RaceWhite 16.044 9281347.082 6485.222 0.000 Inf 0.002 0.998 Stage2 0.638 1.892 1.076 0.230 15.595 0.592 0.554 Stage3 1.553 4.726 1.063 0.589 37.936 1.462 0.144 Stage4 2.085 8.047 1.176 0.803 80.611 1.774 0.076 · Purity 1.290 3.632 1.411 0.229 57.665 0.914 0.361 Rsquare = 0.108 (max possible = 6.98e-01 ) Likelihood ratio test p = 3.6e-02 Wald test p = 7.18e-02 Score (logrank) test p = 2.18e-02 PDHA1 in CESC (n=306): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.502 0.605 0.263 0.361 1.014 -1.908 0.056 · Age 0.014 1.014 0.010 0.995 1.034 1.411 0.158 RaceBlack 0.965 2.624 1.070 0.322 21.379 0.902 0.367 RaceWhite 0.841 2.318 1.015 0.317 16.939 0.828 0.408 Purity 0.725 2.066 0.751 0.474 9.002 0.966 0.334 Rsquare = 0.029 (max possible = 8.91e-01 ) Likelihood ratio test p = 2.37e-01 Wald test p = 2.54e-01 Score (logrank) test p = 2.48e-01 PDHA1 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.529 1.697 0.436 0.722 3.986 1.214 0.225 Age 0.025 1.025 0.024 0.978 1.075 1.047 0.295 Gendermale 0.539 1.713 0.597 0.532 5.524 0.902 0.367 RaceBlack -0.289 0.749 1.506 0.039 14.329 -0.192 0.848 RaceWhite -1.177 0.308 0.915 0.051 1.853 -1.286 0.198 Stage2 0.817 2.264 0.671 0.608 8.429 1.219 0.223 Stage3 -14.893 0.000 7035.274 0.000 Inf -0.002 0.998 Stage4 0.776 2.173 0.681 0.572 8.249 1.140 0.254 Purity 2.042 7.709 1.614 0.326 182.497 1.265 0.206 Rsquare = 0.242 (max possible = 9.46e-01 ) Likelihood ratio test p = 3.53e-01 Wald test p = 5.65e-01 Score (logrank) test p = 3.81e-01 PDHA1 in COAD (n=458): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.046 1.048 0.237 0.659 1.665 0.196 0.844 Age 0.024 1.024 0.012 1.001 1.048 2.082 0.037 * Gendermale 0.212 1.236 0.269 0.730 2.095 0.789 0.430 RaceBlack -0.425 0.654 0.829 0.129 3.317 -0.513 0.608 RaceWhite -0.447 0.639 0.775 0.140 2.919 -0.577 0.564 Stage2 0.212 1.236 0.562 0.411 3.719 0.377 0.706 Stage3 0.814 2.257 0.551 0.766 6.649 1.477 0.140 Stage4 1.894 6.644 0.555 2.241 19.701 3.415 0.001 ** Purity -0.240 0.787 0.607 0.239 2.586 -0.395 0.693 Rsquare = 0.109 (max possible = 9.04e-01 ) Likelihood ratio test p = 4.58e-04 Wald test p = 1.59e-04 Score (logrank) test p = 2.33e-05 PDHA1 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 2.574 13.118 1.484 0.715 240.674 1.734 0.083 · Age -0.010 0.990 0.046 0.905 1.084 -0.208 0.835 Gendermale 1.294 3.647 1.154 0.380 35.019 1.121 0.262 RaceBlack 0.776 2.172 1.786 0.066 72.003 0.434 0.664 RaceWhite -2.931 0.053 1.619 0.002 1.273 -1.811 0.070 · Purity -5.417 0.004 3.313 0.000 2.932 -1.635 0.102 Rsquare = 0.202 (max possible = 5.58e-01 ) Likelihood ratio test p = 1.61e-01 Wald test p = 4.19e-01 Score (logrank) test p = 1.95e-01 PDHA1 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.451 1.570 0.289 0.890 2.769 1.559 0.119 Age 0.005 1.005 0.014 0.978 1.034 0.372 0.710 Gendermale 0.566 1.761 0.541 0.609 5.088 1.045 0.296 RaceBlack 0.379 1.461 1.068 0.180 11.854 0.355 0.722 RaceWhite -0.120 0.886 0.447 0.369 2.130 -0.269 0.788 Stage2 0.763 2.145 0.657 0.592 7.771 1.162 0.245 Stage3 1.453 4.276 0.674 1.141 16.028 2.156 0.031 * Stage4 2.693 14.783 0.791 3.139 69.610 3.407 0.001 ** Purity 0.035 1.036 0.778 0.225 4.761 0.045 0.964 Rsquare = 0.156 (max possible = 9.32e-01 ) Likelihood ratio test p = 4.68e-03 Wald test p = 2.47e-03 Score (logrank) test p = 1.54e-04 PDHA1 in GBM (n=153): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.187 1.206 0.249 0.740 1.964 0.751 0.452 Age 0.030 1.031 0.008 1.014 1.047 3.661 0.000 *** Gendermale -0.068 0.934 0.216 0.612 1.426 -0.315 0.753 RaceBlack 0.561 1.753 0.728 0.421 7.306 0.771 0.441 RaceWhite -0.220 0.802 0.615 0.240 2.679 -0.358 0.720 Purity -1.244 0.288 0.566 0.095 0.874 -2.197 0.028 * Rsquare = 0.133 (max possible = 9.98e-01 ) Likelihood ratio test p = 3.8e-03 Wald test p = 5e-03 Score (logrank) test p = 4.33e-03 PDHA1 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.103 1.108 0.154 0.819 1.498 0.666 0.505 Age 0.022 1.023 0.008 1.007 1.038 2.915 0.004 ** Gendermale -0.257 0.774 0.172 0.552 1.085 -1.489 0.137 RaceBlack 0.136 1.146 0.558 0.383 3.423 0.243 0.808 RaceWhite -0.239 0.788 0.511 0.289 2.144 -0.468 0.640 Stage2 0.606 1.833 0.544 0.631 5.321 1.114 0.265 Stage3 0.851 2.342 0.536 0.818 6.703 1.586 0.113 Stage4 1.232 3.430 0.511 1.260 9.336 2.412 0.016 * Purity -0.064 0.938 0.364 0.459 1.913 -0.177 0.859 Rsquare = 0.07 (max possible = 9.89e-01 ) Likelihood ratio test p = 4.43e-04 Wald test p = 1.11e-03 Score (logrank) test p = 8.15e-04 PDHA1 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.345 7.080000e-01 0.535 0.248 2.023 -0.644 0.520 Age 0.012 1.012000e+00 0.025 0.964 1.063 0.487 0.626 Gendermale -0.149 8.620000e-01 0.535 0.302 2.458 -0.278 0.781 RaceBlack 18.826 1.500013e+08 12095.122 0.000 Inf 0.002 0.999 RaceWhite 18.159 7.696323e+07 12095.122 0.000 Inf 0.002 0.999 Stage2 17.644 4.600379e+07 5218.198 0.000 Inf 0.003 0.997 Stage3 16.920 2.229470e+07 5218.198 0.000 Inf 0.003 0.997 Stage4 17.621 4.496915e+07 5218.198 0.000 Inf 0.003 0.997 Purity -1.634 1.950000e-01 1.081 0.023 1.624 -1.511 0.131 Rsquare = 0.093 (max possible = 9.17e-01 ) Likelihood ratio test p = 7.04e-01 Wald test p = 9.3e-01 Score (logrank) test p = 8.32e-01 PDHA1 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.174 1.190 0.169 0.855 1.657 1.033 0.302 Age 0.027 1.027 0.008 1.010 1.044 3.168 0.002 ** Gendermale -0.298 0.742 0.183 0.518 1.063 -1.628 0.104 RaceBlack -0.012 0.988 0.564 0.327 2.982 -0.022 0.983 RaceWhite -0.377 0.686 0.512 0.251 1.873 -0.736 0.462 Stage2 0.356 1.428 0.554 0.482 4.227 0.643 0.520 Stage3 0.738 2.091 0.541 0.725 6.034 1.364 0.172 Stage4 1.111 3.036 0.513 1.111 8.300 2.165 0.030 * Purity 0.185 1.203 0.400 0.549 2.635 0.462 0.644 Rsquare = 0.088 (max possible = 9.89e-01 ) Likelihood ratio test p = 2.23e-04 Wald test p = 5.63e-04 Score (logrank) test p = 4.26e-04 PDHA1 in KICH (n=66): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p PDHA1 0.005 1.005000e+00 0.677 0.266 3.791000e+00 0.007 0.994 Age 0.076 1.079000e+00 0.029 1.019 1.142000e+00 2.621 0.009 Gendermale -0.903 4.050000e-01 0.728 0.097 1.687000e+00 -1.241 0.215 RaceBlack -17.134 0.000000e+00 6227.877 0.000 Inf -0.003 0.998 RaceWhite -1.951 1.420000e-01 1.160 0.015 1.380000e+00 -1.682 0.092 Stage2 16.072 9.553788e+06 0.848 1811540.296 5.038522e+07 18.945 0.000 Stage3 17.169 2.859239e+07 0.777 6230552.933 1.312122e+08 22.085 0.000 Stage4 19.615 3.302703e+08 0.901 56531684.897 1.929510e+09 21.781 0.000 Purity 1.047 2.850000e+00 3.593 0.002 3.258480e+03 0.291 0.771 signif PDHA1 Age ** Gendermale RaceBlack RaceWhite · Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.346 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.54e-03 Wald test p = 3.13e-281 Score (logrank) test p = 1.07e-08 PDHA1 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.265 0.767 0.197 0.521 1.129 -1.344 0.179 Age 0.034 1.035 0.008 1.018 1.052 4.098 0.000 *** Gendermale -0.126 0.881 0.187 0.611 1.270 -0.678 0.498 RaceBlack 0.315 1.371 1.060 0.172 10.944 0.298 0.766 RaceWhite 0.212 1.237 1.016 0.169 9.056 0.209 0.834 Stage2 0.214 1.239 0.344 0.631 2.434 0.623 0.533 Stage3 0.777 2.176 0.231 1.383 3.421 3.366 0.001 ** Stage4 1.725 5.614 0.217 3.668 8.592 7.944 0.000 *** Purity 0.040 1.041 0.367 0.507 2.135 0.109 0.913 Rsquare = 0.177 (max possible = 9.65e-01 ) Likelihood ratio test p = 4.37e-15 Wald test p = 4e-15 Score (logrank) test p = 2.21e-18 PDHA1 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.818 0.441 0.342 0.226 0.863 -2.390 0.017 * Age 0.015 1.015 0.016 0.984 1.047 0.952 0.341 Gendermale -0.338 0.713 0.388 0.333 1.525 -0.872 0.383 RaceBlack -2.049 0.129 1.207 0.012 1.373 -1.697 0.090 · RaceWhite -2.391 0.092 1.184 0.009 0.933 -2.019 0.043 * Stage2 -0.329 0.720 1.055 0.091 5.687 -0.312 0.755 Stage3 1.345 3.839 0.436 1.632 9.030 3.083 0.002 ** Stage4 2.538 12.648 0.506 4.694 34.083 5.017 0.000 *** Purity -0.092 0.912 0.747 0.211 3.938 -0.124 0.901 Rsquare = 0.184 (max possible = 7.58e-01 ) Likelihood ratio test p = 1.12e-06 Wald test p = 5.74e-07 Score (logrank) test p = 4.15e-11 PDHA1 in LAML (n=173): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.806 2.240 0.388 1.048 4.789 2.080 0.038 * Age 0.041 1.042 0.008 1.025 1.059 4.872 0.000 *** Gendermale -0.191 0.826 0.213 0.544 1.253 -0.899 0.369 RaceBlack -0.161 0.851 1.109 0.097 7.485 -0.145 0.885 RaceWhite -0.550 0.577 1.020 0.078 4.257 -0.539 0.590 Rsquare = 0.181 (max possible = 9.96e-01 ) Likelihood ratio test p = 1.6e-05 Wald test p = 9.7e-05 Score (logrank) test p = 6.58e-05 PDHA1 in LGG (n=516): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.332 1.393 0.280 0.805 2.412 1.184 0.237 Age 0.062 1.064 0.008 1.048 1.080 8.099 0.000 *** Gendermale 0.116 1.123 0.196 0.765 1.650 0.592 0.554 RaceBlack 15.454 5147031.211 2006.632 0.000 Inf 0.008 0.994 RaceWhite 15.486 5316134.875 2006.632 0.000 Inf 0.008 0.994 Purity -0.956 0.384 0.398 0.176 0.839 -2.400 0.016 * Rsquare = 0.139 (max possible = 9.07e-01 ) Likelihood ratio test p = 5.96e-13 Wald test p = 6.27e-13 Score (logrank) test p = 5.17e-14 PDHA1 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.146 1.157 0.162 0.842 1.589 0.901 0.368 Age 0.011 1.011 0.008 0.995 1.027 1.330 0.183 Gendermale -0.076 0.927 0.238 0.582 1.478 -0.319 0.750 RaceBlack 0.855 2.352 0.491 0.899 6.157 1.742 0.081 · RaceWhite 0.015 1.015 0.238 0.636 1.619 0.063 0.950 Stage2 0.276 1.318 0.265 0.783 2.217 1.040 0.298 Stage3 0.932 2.540 0.236 1.601 4.031 3.956 0.000 *** Stage4 1.689 5.412 0.628 1.579 18.544 2.687 0.007 ** Purity 0.593 1.810 0.460 0.735 4.456 1.290 0.197 Rsquare = 0.087 (max possible = 9.66e-01 ) Likelihood ratio test p = 8.87e-04 Wald test p = 5.54e-04 Score (logrank) test p = 2.02e-04 PDHA1 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.259 1.295 0.172 0.925 1.814 1.504 0.133 Age 0.008 1.008 0.009 0.990 1.026 0.875 0.381 Gendermale 0.038 1.038 0.169 0.745 1.446 0.223 0.824 RaceBlack 16.065 9483342.394 1856.614 0.000 Inf 0.009 0.993 RaceWhite 16.282 11776804.924 1856.614 0.000 Inf 0.009 0.993 Stage2 0.878 2.406 0.202 1.621 3.573 4.355 0.000 *** Stage3 1.034 2.811 0.218 1.832 4.313 4.731 0.000 *** Stage4 1.076 2.934 0.338 1.514 5.686 3.189 0.001 ** Purity 0.476 1.610 0.353 0.806 3.215 1.350 0.177 Rsquare = 0.101 (max possible = 9.74e-01 ) Likelihood ratio test p = 9.15e-07 Wald test p = 1.4e-05 Score (logrank) test p = 1.64e-06 PDHA1 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.285 0.752 0.166 0.543 1.041 -1.717 0.086 · Age 0.017 1.017 0.009 0.999 1.036 1.811 0.070 · Gendermale 0.476 1.610 0.195 1.099 2.357 2.447 0.014 * RaceBlack 0.166 1.181 0.613 0.355 3.925 0.271 0.786 RaceWhite -0.467 0.627 0.565 0.207 1.896 -0.827 0.408 Stage2 0.232 1.262 0.187 0.875 1.819 1.246 0.213 Stage3 0.627 1.871 0.215 1.229 2.851 2.919 0.004 ** Stage4 0.789 2.201 0.795 0.463 10.453 0.993 0.321 Purity -0.203 0.816 0.372 0.394 1.692 -0.546 0.585 Rsquare = 0.058 (max possible = 9.87e-01 ) Likelihood ratio test p = 8.67e-03 Wald test p = 6.76e-03 Score (logrank) test p = 5.66e-03 PDHA1 in MESO (n=87): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.521 1.683 0.295 0.944 3.002 1.765 0.078 · Age 0.020 1.020 0.016 0.989 1.052 1.254 0.210 Gendermale -0.029 0.971 0.344 0.494 1.907 -0.085 0.932 RaceBlack -0.160 0.852 1.534 0.042 17.218 -0.104 0.917 RaceWhite -0.650 0.522 1.050 0.067 4.087 -0.619 0.536 Stage2 -0.235 0.790 0.472 0.313 1.993 -0.499 0.618 Stage3 -0.185 0.831 0.431 0.357 1.936 -0.428 0.669 Stage4 -0.213 0.808 0.482 0.314 2.079 -0.442 0.658 Purity -0.811 0.444 0.574 0.144 1.368 -1.413 0.158 Rsquare = 0.093 (max possible = 9.98e-01 ) Likelihood ratio test p = 5.06e-01 Wald test p = 4.69e-01 Score (logrank) test p = 4.53e-01 PDHA1 in OV (n=303): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.034 1.035 0.138 0.790 1.356 0.249 0.803 Age 0.037 1.037 0.008 1.020 1.055 4.349 0.000 *** RaceBlack -0.041 0.960 0.578 0.309 2.982 -0.071 0.943 RaceWhite -0.146 0.864 0.517 0.314 2.380 -0.283 0.778 Purity -0.557 0.573 0.669 0.154 2.127 -0.833 0.405 Rsquare = 0.082 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.13e-03 Wald test p = 9.77e-04 Score (logrank) test p = 8.15e-04 PDHA1 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.412 0.662 0.266 0.394 1.114 -1.552 0.121 Age 0.020 1.020 0.011 0.998 1.042 1.781 0.075 · Gendermale -0.233 0.792 0.216 0.518 1.211 -1.075 0.282 RaceBlack -0.001 0.999 0.740 0.234 4.255 -0.002 0.998 RaceWhite 0.367 1.444 0.473 0.571 3.649 0.776 0.437 Stage2 0.592 1.807 0.440 0.763 4.280 1.344 0.179 Stage3 -0.503 0.605 1.105 0.069 5.272 -0.455 0.649 Stage4 0.153 1.166 0.826 0.231 5.884 0.185 0.853 Purity -0.690 0.502 0.411 0.224 1.123 -1.677 0.094 · Rsquare = 0.101 (max possible = 9.91e-01 ) Likelihood ratio test p = 4.03e-02 Wald test p = 5.68e-02 Score (logrank) test p = 5.18e-02 PDHA1 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 1.755 5.784 0.844 1.105 30.263 2.079 0.038 * Age 0.038 1.039 0.030 0.980 1.101 1.283 0.199 Gendermale 1.279 3.593 0.916 0.597 21.625 1.397 0.162 RaceBlack -0.698 0.497 22612.685 0.000 Inf 0.000 1.000 RaceWhite 17.411 36443074.651 19308.188 0.000 Inf 0.001 0.999 Purity 5.432 228.566 3.671 0.171 304623.749 1.480 0.139 Rsquare = 0.078 (max possible = 3.07e-01 ) Likelihood ratio test p = 3.92e-02 Wald test p = 1.43e-01 Score (logrank) test p = 8.26e-02 PDHA1 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 2.121 8.341 0.888 1.463 47.555 2.388 0.017 * Age 0.008 1.008 0.058 0.899 1.131 0.144 0.885 RaceBlack 16.345 12543335.402 11216.957 0.000 Inf 0.001 0.999 RaceWhite 17.320 33274135.302 11216.957 0.000 Inf 0.002 0.999 Purity 0.622 1.863 1.419 0.115 30.074 0.438 0.661 Rsquare = 0.019 (max possible = 1.83e-01 ) Likelihood ratio test p = 1.67e-01 Wald test p = 1.58e-01 Score (logrank) test p = 1.59e-01 PDHA1 in READ (n=166): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.102 1.107 0.522 0.398 3.079 0.195 0.845 Age 0.111 1.117 0.044 1.024 1.218 2.494 0.013 * Gendermale -0.356 0.701 0.688 0.182 2.696 -0.518 0.605 RaceBlack 13.436 684306.893 10145.127 0.000 Inf 0.001 0.999 RaceWhite 12.417 247007.283 10145.127 0.000 Inf 0.001 0.999 Stage2 -1.822 0.162 1.261 0.014 1.914 -1.445 0.148 Stage3 -0.467 0.627 0.902 0.107 3.670 -0.518 0.605 Stage4 -0.110 0.896 0.975 0.132 6.060 -0.113 0.910 Purity 0.084 1.088 1.342 0.078 15.099 0.063 0.950 Rsquare = 0.21 (max possible = 7.22e-01 ) Likelihood ratio test p = 3.66e-02 Wald test p = 2.42e-01 Score (logrank) test p = 4.91e-02 PDHA1 in SARC (n=260): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.151 1.163 0.186 0.808 1.675 0.813 0.416 Age 0.023 1.023 0.008 1.006 1.040 2.719 0.007 ** Gendermale -0.008 0.992 0.222 0.642 1.534 -0.034 0.973 RaceBlack -0.077 0.925 1.088 0.110 7.799 -0.071 0.943 RaceWhite -0.426 0.653 1.024 0.088 4.862 -0.416 0.677 Purity 0.855 2.352 0.584 0.749 7.381 1.465 0.143 Rsquare = 0.045 (max possible = 9.75e-01 ) Likelihood ratio test p = 9.59e-02 Wald test p = 1.33e-01 Score (logrank) test p = 1.33e-01 PDHA1 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.001 1.001 0.158 0.734 1.365 0.005 0.996 Age 0.018 1.019 0.005 1.008 1.029 3.541 0.000 *** Gendermale -0.050 0.951 0.157 0.699 1.295 -0.319 0.750 RaceWhite -1.286 0.276 0.402 0.126 0.607 -3.201 0.001 ** Stage2 0.275 1.317 0.219 0.857 2.023 1.256 0.209 Stage3 0.611 1.842 0.204 1.235 2.748 2.993 0.003 ** Stage4 1.350 3.859 0.352 1.937 7.688 3.839 0.000 *** Purity 1.019 2.770 0.346 1.407 5.456 2.947 0.003 ** Rsquare = 0.123 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.23e-08 Wald test p = 1.19e-08 Score (logrank) test p = 1.44e-09 PDHA1 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.355 7.010000e-01 0.390 0.326 1.506 -0.910 0.363 Age 0.011 1.012000e+00 0.016 0.980 1.044 0.717 0.473 Gendermale 0.184 1.203000e+00 0.436 0.512 2.826 0.423 0.672 RaceWhite -1.294 2.740000e-01 0.622 0.081 0.927 -2.081 0.037 * Stage2 17.583 4.326854e+07 6208.606 0.000 Inf 0.003 0.998 Stage3 18.010 6.631352e+07 6208.606 0.000 Inf 0.003 0.998 Stage4 20.237 6.147847e+08 6208.606 0.000 Inf 0.003 0.997 Purity 0.617 1.854000e+00 1.028 0.247 13.905 0.600 0.548 Rsquare = 0.154 (max possible = 8.69e-01 ) Likelihood ratio test p = 4.69e-02 Wald test p = 3.9e-02 Score (logrank) test p = 3.12e-03 PDHA1 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.131 1.140 0.173 0.812 1.599 0.758 0.448 Age 0.020 1.020 0.006 1.009 1.032 3.602 0.000 *** Gendermale -0.058 0.943 0.172 0.673 1.322 -0.338 0.736 RaceWhite -1.078 0.340 0.600 0.105 1.104 -1.796 0.073 · Stage2 0.168 1.183 0.231 0.752 1.862 0.726 0.468 Stage3 0.565 1.760 0.209 1.169 2.651 2.705 0.007 ** Stage4 1.139 3.123 0.399 1.427 6.833 2.851 0.004 ** Purity 1.095 2.990 0.375 1.433 6.239 2.918 0.004 ** Rsquare = 0.135 (max possible = 9.95e-01 ) Likelihood ratio test p = 8.59e-07 Wald test p = 1.3e-06 Score (logrank) test p = 5.19e-07 PDHA1 in STAD (n=415): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 -0.210 0.810 0.193 0.555 1.184 -1.086 0.277 Age 0.026 1.027 0.010 1.006 1.048 2.587 0.010 * Gendermale 0.134 1.144 0.207 0.762 1.717 0.647 0.517 RaceBlack 0.407 1.502 0.465 0.604 3.738 0.874 0.382 RaceWhite 0.111 1.117 0.244 0.692 1.803 0.453 0.651 Stage2 0.483 1.620 0.389 0.756 3.472 1.242 0.214 Stage3 0.890 2.435 0.364 1.194 4.966 2.448 0.014 * Stage4 1.307 3.694 0.501 1.383 9.866 2.608 0.009 ** Purity -0.502 0.605 0.380 0.288 1.273 -1.324 0.186 Rsquare = 0.073 (max possible = 9.79e-01 ) Likelihood ratio test p = 9.01e-03 Wald test p = 1.15e-02 Score (logrank) test p = 9.16e-03 PDHA1 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 2.615 13.665 16607.305 0 Inf 0.000 1.000 Age -1.601 0.202 1819.704 0 Inf -0.001 0.999 RaceBlack 9.302 10956.812 16985767.759 0 Inf 0.000 1.000 RaceWhite -34.669 0.000 17022748.265 0 Inf 0.000 1.000 Stage2 -5.023 0.007 44527.372 0 Inf 0.000 1.000 Stage3 15.514 5468342.874 92110.520 0 Inf 0.000 1.000 Purity 7.542 1885.329 232329.128 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.04e-03 PDHA1 in THCA (n=509): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.394 1.483 0.683 0.389 5.657 0.577 0.564 Age 0.148 1.160 0.028 1.097 1.226 5.247 0.000 *** Gendermale -0.192 0.826 0.671 0.222 3.075 -0.286 0.775 RaceBlack 16.804 19848701.290 5743.252 0.000 Inf 0.003 0.998 RaceWhite 16.689 17705122.972 5743.252 0.000 Inf 0.003 0.998 Stage2 0.033 1.034 1.142 0.110 9.701 0.029 0.977 Stage3 0.404 1.497 0.905 0.254 8.818 0.446 0.655 Stage4 1.885 6.584 1.053 0.836 51.864 1.790 0.074 · Purity 2.196 8.988 1.080 1.081 74.707 2.032 0.042 * Rsquare = 0.15 (max possible = 3.47e-01 ) Likelihood ratio test p = 2.2e-10 Wald test p = 3.07e-04 Score (logrank) test p = 1.18e-10 PDHA1 in THYM (n=120): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.438 1.549 0.525 0.553 4.339 0.833 0.405 Age 0.047 1.048 0.031 0.985 1.114 1.480 0.139 Gendermale -0.036 0.965 0.756 0.219 4.243 -0.048 0.962 RaceBlack -16.747 0.000 10165.584 0.000 Inf -0.002 0.999 RaceWhite 0.265 1.304 1.132 0.142 11.996 0.234 0.815 Purity 0.210 1.233 1.123 0.137 11.135 0.187 0.852 Rsquare = 0.05 (max possible = 4.51e-01 ) Likelihood ratio test p = 4.45e-01 Wald test p = 5.69e-01 Score (logrank) test p = 4.44e-01 PDHA1 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.252 1.287 0.267 0.763 2.171 0.946 0.344 Age 0.048 1.050 0.016 1.017 1.083 3.043 0.002 ** RaceBlack -0.431 0.650 0.795 0.137 3.086 -0.542 0.588 RaceWhite -0.496 0.609 0.746 0.141 2.628 -0.665 0.506 Purity 0.377 1.457 0.657 0.402 5.277 0.574 0.566 Rsquare = 0.041 (max possible = 7.81e-01 ) Likelihood ratio test p = 3.59e-02 Wald test p = 4.38e-02 Score (logrank) test p = 4.18e-02 PDHA1 in UCS (n=57): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.204 1.226 0.288 0.698 2.155 0.710 0.478 Age 0.046 1.047 0.024 0.998 1.098 1.881 0.060 · RaceBlack 17.493 39529836.882 6482.060 0.000 Inf 0.003 0.998 RaceWhite 17.702 48721787.682 6482.060 0.000 Inf 0.003 0.998 Purity -0.894 0.409 1.065 0.051 3.301 -0.839 0.402 Rsquare = 0.128 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.14e-01 Wald test p = 3.23e-01 Score (logrank) test p = 2.35e-01 PDHA1 in UVM (n=80): Model: Surv(OS, EVENT) ~ `PDHA1` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif PDHA1 0.935 2.547 0.453 1.048 6.188 2.064 0.039 * Age 0.046 1.047 0.019 1.009 1.087 2.418 0.016 * Gendermale 0.295 1.343 0.471 0.533 3.383 0.625 0.532 Stage3 0.153 1.166 0.498 0.439 3.094 0.308 0.758 Stage4 3.764 43.142 1.209 4.034 461.406 3.113 0.002 ** Purity 2.014 7.496 1.303 0.583 96.373 1.546 0.122 Rsquare = 0.298 (max possible = 8.72e-01 ) Likelihood ratio test p = 1.28e-04 Wald test p = 1.68e-03 Score (logrank) test p = 8.15e-10 SCD in ACC (n=79): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.042 1.04300e+00 0.133 0.803 1.354 0.315 0.753 Age 0.005 1.00500e+00 0.014 0.978 1.033 0.369 0.712 Gendermale 0.381 1.46400e+00 0.418 0.645 3.325 0.911 0.362 RaceBlack -0.002 9.98000e-01 11967.296 0.000 Inf 0.000 1.000 RaceWhite 16.836 2.05065e+07 10190.331 0.000 Inf 0.002 0.999 Purity 2.931 1.87500e+01 2.375 0.178 1971.133 1.234 0.217 Rsquare = 0.068 (max possible = 9.38e-01 ) Likelihood ratio test p = 6.1e-01 Wald test p = 8.98e-01 Score (logrank) test p = 7.57e-01 SCD in BLCA (n=408): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.138 1.147 0.059 1.022 1.288 2.327 0.020 * Age 0.031 1.032 0.009 1.014 1.049 3.606 0.000 *** Gendermale -0.189 0.827 0.179 0.582 1.176 -1.057 0.291 RaceBlack 0.563 1.756 0.451 0.725 4.255 1.248 0.212 RaceWhite 0.070 1.072 0.355 0.535 2.151 0.197 0.844 Stage2 14.360 1723640.270 1859.549 0.000 Inf 0.008 0.994 Stage3 14.813 2711874.798 1859.549 0.000 Inf 0.008 0.994 Stage4 15.333 4561875.930 1859.549 0.000 Inf 0.008 0.993 Purity 0.035 1.036 0.346 0.526 2.040 0.101 0.919 Rsquare = 0.144 (max possible = 9.91e-01 ) Likelihood ratio test p = 1.96e-08 Wald test p = 2.06e-07 Score (logrank) test p = 5.48e-08 SCD in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.048 1.050 0.059 0.934 1.180 0.815 0.415 Age 0.037 1.037 0.008 1.022 1.053 4.794 0.000 *** Gendermale 0.000 1.000 1.009 0.139 7.219 0.000 1.000 RaceBlack 0.006 1.006 0.619 0.299 3.385 0.009 0.993 RaceWhite -0.239 0.787 0.596 0.245 2.535 -0.401 0.689 Stage2 0.426 1.531 0.305 0.843 2.780 1.398 0.162 Stage3 1.209 3.349 0.314 1.810 6.198 3.849 0.000 *** Stage4 2.516 12.375 0.389 5.778 26.503 6.474 0.000 *** Purity 0.445 1.560 0.431 0.671 3.628 1.033 0.302 Rsquare = 0.082 (max possible = 7.85e-01 ) Likelihood ratio test p = 1.83e-12 Wald test p = 4.74e-16 Score (logrank) test p = 6.17e-22 SCD in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `SCD` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.142 8.670000e-01 0.172 0.619 1.215 -0.828 0.408 Age 0.015 1.015000e+00 0.018 0.979 1.052 0.795 0.427 RaceBlack -1.042 3.530000e-01 1.113 0.040 3.125 -0.936 0.349 RaceWhite -1.361 2.560000e-01 1.121 0.029 2.305 -1.215 0.225 Stage2 18.648 1.255242e+08 6490.422 0.000 Inf 0.003 0.998 Stage3 20.014 4.918070e+08 6490.422 0.000 Inf 0.003 0.998 Stage4 21.161 1.549611e+09 6490.422 0.000 Inf 0.003 0.997 Purity 0.814 2.257000e+00 0.956 0.346 14.703 0.851 0.395 Rsquare = 0.16 (max possible = 7.18e-01 ) Likelihood ratio test p = 3.97e-04 Wald test p = 7.21e-03 Score (logrank) test p = 4.21e-06 SCD in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `SCD` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.349 7.050000e-01 0.267 0.418 1.190 -1.308 0.191 Age 0.044 1.045000e+00 0.031 0.983 1.111 1.425 0.154 RaceBlack -3.597 2.700000e-02 1.902 0.001 1.141 -1.891 0.059 · RaceWhite -2.326 9.800000e-02 1.578 0.004 2.153 -1.474 0.141 Stage2 18.549 1.137266e+08 14918.078 0.000 Inf 0.001 0.999 Stage3 20.100 5.361931e+08 14918.078 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 3.519 3.375100e+01 2.372 0.323 3523.533 1.484 0.138 Rsquare = 0.388 (max possible = 6.68e-01 ) Likelihood ratio test p = 1.47e-04 Wald test p = 1.9e-01 Score (logrank) test p = 6.5e-15 SCD in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.031 1.032 0.098 0.851 1.250 0.316 0.752 Age 0.049 1.050 0.012 1.026 1.076 4.085 0.000 *** Gendermale -15.399 0.000 3460.861 0.000 Inf -0.004 0.996 RaceBlack -0.452 0.636 1.175 0.064 6.370 -0.385 0.700 RaceWhite 0.208 1.231 1.039 0.161 9.426 0.200 0.842 Stage2 0.346 1.414 0.380 0.672 2.976 0.912 0.362 Stage3 0.909 2.483 0.421 1.088 5.665 2.160 0.031 * Stage4 2.138 8.481 0.593 2.652 27.128 3.604 0.000 *** Purity 0.278 1.320 0.622 0.390 4.464 0.447 0.655 Rsquare = 0.07 (max possible = 6.81e-01 ) Likelihood ratio test p = 1e-04 Wald test p = 1.91e-05 Score (logrank) test p = 3.86e-07 SCD in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.282 1.326 0.157 0.975 1.803 1.797 0.072 · Age 0.052 1.053 0.021 1.011 1.097 2.480 0.013 * Gendermale 0.968 2.633 1.114 0.297 23.348 0.869 0.385 RaceBlack 16.642 16891656.934 7065.880 0.000 Inf 0.002 0.998 RaceWhite 16.125 10067522.562 7065.880 0.000 Inf 0.002 0.998 Stage2 0.617 1.853 1.078 0.224 15.339 0.572 0.567 Stage3 1.384 3.991 1.065 0.495 32.210 1.299 0.194 Stage4 2.257 9.554 1.182 0.943 96.839 1.910 0.056 · Purity 0.992 2.696 1.384 0.179 40.638 0.717 0.474 Rsquare = 0.125 (max possible = 6.98e-01 ) Likelihood ratio test p = 1.32e-02 Wald test p = 2.07e-02 Score (logrank) test p = 4.57e-03 SCD in CESC (n=306): Model: Surv(OS, EVENT) ~ `SCD` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.186 1.204 0.105 0.979 1.481 1.763 0.078 · Age 0.009 1.009 0.010 0.990 1.028 0.894 0.371 RaceBlack 0.977 2.656 1.069 0.327 21.580 0.914 0.361 RaceWhite 0.771 2.161 1.015 0.295 15.812 0.759 0.448 Purity 0.492 1.636 0.745 0.380 7.043 0.660 0.509 Rsquare = 0.027 (max possible = 8.91e-01 ) Likelihood ratio test p = 2.87e-01 Wald test p = 2.97e-01 Score (logrank) test p = 2.87e-01 SCD in CHOL (n=36): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.497 1.644 0.268 0.973 2.778 1.858 0.063 · Age 0.033 1.033 0.025 0.985 1.085 1.330 0.184 Gendermale 0.548 1.729 0.569 0.567 5.274 0.963 0.336 RaceBlack 0.343 1.409 1.505 0.074 26.885 0.228 0.820 RaceWhite -0.881 0.414 0.868 0.076 2.268 -1.016 0.310 Stage2 0.659 1.933 0.694 0.496 7.533 0.949 0.342 Stage3 -13.244 0.000 7123.288 0.000 Inf -0.002 0.999 Stage4 1.122 3.072 0.714 0.758 12.447 1.572 0.116 Purity 3.044 20.988 1.771 0.652 675.848 1.718 0.086 · Rsquare = 0.288 (max possible = 9.46e-01 ) Likelihood ratio test p = 2.01e-01 Wald test p = 3.82e-01 Score (logrank) test p = 2.15e-01 SCD in COAD (n=458): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.107 1.113 0.136 0.852 1.454 0.786 0.432 Age 0.023 1.023 0.011 1.001 1.047 2.016 0.044 * Gendermale 0.213 1.237 0.268 0.732 2.091 0.793 0.428 RaceBlack -0.332 0.718 0.830 0.141 3.650 -0.400 0.689 RaceWhite -0.363 0.695 0.778 0.151 3.195 -0.467 0.640 Stage2 0.202 1.224 0.562 0.407 3.682 0.360 0.719 Stage3 0.751 2.118 0.554 0.715 6.274 1.355 0.176 Stage4 1.830 6.232 0.557 2.091 18.575 3.283 0.001 ** Purity -0.254 0.776 0.603 0.238 2.528 -0.421 0.674 Rsquare = 0.111 (max possible = 9.04e-01 ) Likelihood ratio test p = 3.63e-04 Wald test p = 1.31e-04 Score (logrank) test p = 1.94e-05 SCD in DLBC (n=48): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.066 1.068 0.509 0.394 2.896 0.130 0.897 Age -0.004 0.996 0.043 0.916 1.082 -0.101 0.919 Gendermale 0.641 1.898 1.062 0.237 15.206 0.604 0.546 RaceBlack 0.440 1.553 1.665 0.059 40.579 0.264 0.792 RaceWhite -2.153 0.116 1.314 0.009 1.525 -1.639 0.101 Purity -2.075 0.126 2.114 0.002 7.916 -0.981 0.326 Rsquare = 0.131 (max possible = 5.58e-01 ) Likelihood ratio test p = 4.51e-01 Wald test p = 5.95e-01 Score (logrank) test p = 3.38e-01 SCD in ESCA (n=185): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.051 0.950 0.137 0.726 1.243 -0.373 0.709 Age 0.009 1.009 0.014 0.981 1.037 0.615 0.538 Gendermale 0.448 1.566 0.545 0.538 4.558 0.823 0.411 RaceBlack 0.347 1.415 1.069 0.174 11.492 0.325 0.745 RaceWhite -0.121 0.886 0.460 0.360 2.185 -0.262 0.793 Stage2 0.702 2.018 0.654 0.560 7.276 1.073 0.283 Stage3 1.476 4.375 0.674 1.167 16.396 2.189 0.029 * Stage4 2.883 17.867 0.776 3.907 81.714 3.717 0.000 *** Purity 0.271 1.311 0.786 0.281 6.115 0.345 0.730 Rsquare = 0.142 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.1e-02 Wald test p = 4.96e-03 Score (logrank) test p = 4.17e-04 SCD in GBM (n=153): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.003 1.003 0.109 0.810 1.242 0.024 0.981 Age 0.030 1.030 0.008 1.014 1.047 3.584 0.000 *** Gendermale -0.096 0.909 0.215 0.597 1.384 -0.446 0.655 RaceBlack 0.527 1.693 0.728 0.406 7.056 0.723 0.470 RaceWhite -0.242 0.785 0.616 0.235 2.629 -0.392 0.695 Purity -1.085 0.338 0.537 0.118 0.969 -2.019 0.044 * Rsquare = 0.129 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.8e-03 Wald test p = 6.82e-03 Score (logrank) test p = 5.79e-03 SCD in HNSC (n=522): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.123 1.130 0.067 0.991 1.290 1.819 0.069 · Age 0.020 1.020 0.008 1.005 1.036 2.635 0.008 ** Gendermale -0.254 0.776 0.172 0.554 1.087 -1.477 0.140 RaceBlack 0.228 1.257 0.561 0.418 3.775 0.407 0.684 RaceWhite -0.123 0.885 0.515 0.322 2.427 -0.238 0.812 Stage2 0.601 1.824 0.544 0.628 5.296 1.106 0.269 Stage3 0.853 2.348 0.536 0.821 6.716 1.591 0.111 Stage4 1.241 3.460 0.510 1.274 9.397 2.435 0.015 * Purity -0.135 0.874 0.372 0.422 1.811 -0.363 0.716 Rsquare = 0.077 (max possible = 9.89e-01 ) Likelihood ratio test p = 1.39e-04 Wald test p = 3.55e-04 Score (logrank) test p = 2.47e-04 SCD in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.136 1.146000e+00 0.198 0.777 1.690 0.686 0.493 Age 0.008 1.008000e+00 0.025 0.960 1.059 0.317 0.751 Gendermale -0.183 8.320000e-01 0.536 0.291 2.381 -0.342 0.732 RaceBlack 18.927 1.659231e+08 12083.327 0.000 Inf 0.002 0.999 RaceWhite 18.191 7.951628e+07 12083.327 0.000 Inf 0.002 0.999 Stage2 17.477 3.893671e+07 5360.416 0.000 Inf 0.003 0.997 Stage3 16.717 1.820916e+07 5360.416 0.000 Inf 0.003 0.998 Stage4 17.509 4.019538e+07 5360.416 0.000 Inf 0.003 0.997 Purity -1.704 1.820000e-01 1.100 0.021 1.572 -1.549 0.121 Rsquare = 0.094 (max possible = 9.17e-01 ) Likelihood ratio test p = 7e-01 Wald test p = 9.35e-01 Score (logrank) test p = 8.36e-01 SCD in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.117 1.124 0.072 0.976 1.294 1.619 0.105 Age 0.025 1.025 0.008 1.009 1.042 2.983 0.003 ** Gendermale -0.284 0.753 0.183 0.526 1.078 -1.552 0.121 RaceBlack 0.073 1.076 0.567 0.354 3.271 0.130 0.897 RaceWhite -0.274 0.760 0.517 0.276 2.096 -0.529 0.597 Stage2 0.340 1.406 0.554 0.474 4.164 0.614 0.539 Stage3 0.710 2.035 0.541 0.705 5.873 1.313 0.189 Stage4 1.120 3.065 0.512 1.124 8.362 2.188 0.029 * Purity 0.124 1.132 0.408 0.508 2.520 0.304 0.761 Rsquare = 0.092 (max possible = 9.89e-01 ) Likelihood ratio test p = 1.18e-04 Wald test p = 2.96e-04 Score (logrank) test p = 2.22e-04 SCD in KICH (n=66): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p SCD 0.467 1.595000e+00 0.230 1.016 2.504000e+00 2.030 0.042 Age 0.099 1.104000e+00 0.032 1.037 1.175000e+00 3.097 0.002 Gendermale -0.831 4.360000e-01 0.735 0.103 1.838000e+00 -1.131 0.258 RaceBlack -16.931 0.000000e+00 6200.744 0.000 Inf -0.003 0.998 RaceWhite -1.750 1.740000e-01 1.160 0.018 1.689000e+00 -1.508 0.132 Stage2 15.631 6.141792e+06 0.847 1168123.485 3.229249e+07 18.458 0.000 Stage3 16.873 2.126435e+07 0.779 4618312.881 9.790860e+07 21.657 0.000 Stage4 18.743 1.380743e+08 0.889 24185199.188 7.882722e+08 21.088 0.000 Purity -0.207 8.130000e-01 3.582 0.001 9.106710e+02 -0.058 0.954 signif SCD * Age ** Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.373 (max possible = 6.71e-01 ) Likelihood ratio test p = 5.58e-04 Wald test p = 4.05e-268 Score (logrank) test p = 5.55e-09 SCD in KIRC (n=533): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.002 1.002 0.073 0.868 1.157 0.029 0.977 Age 0.035 1.036 0.008 1.019 1.053 4.161 0.000 *** Gendermale -0.082 0.921 0.184 0.642 1.321 -0.447 0.655 RaceBlack 0.206 1.229 1.061 0.154 9.824 0.194 0.846 RaceWhite 0.153 1.165 1.014 0.160 8.503 0.151 0.880 Stage2 0.215 1.240 0.344 0.631 2.435 0.624 0.533 Stage3 0.811 2.250 0.230 1.434 3.530 3.529 0.000 *** Stage4 1.760 5.811 0.216 3.802 8.880 8.132 0.000 *** Purity -0.003 0.997 0.368 0.484 2.052 -0.008 0.993 Rsquare = 0.174 (max possible = 9.65e-01 ) Likelihood ratio test p = 1.04e-14 Wald test p = 1.07e-14 Score (logrank) test p = 5.78e-18 SCD in KIRP (n=290): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.104 0.901 0.151 0.671 1.211 -0.689 0.491 Age 0.009 1.009 0.016 0.978 1.040 0.550 0.582 Gendermale -0.535 0.586 0.385 0.275 1.246 -1.390 0.165 RaceBlack -2.182 0.113 1.214 0.010 1.218 -1.797 0.072 · RaceWhite -2.198 0.111 1.184 0.011 1.131 -1.856 0.063 · Stage2 -0.324 0.723 1.062 0.090 5.800 -0.305 0.761 Stage3 1.725 5.615 0.444 2.351 13.410 3.884 0.000 *** Stage4 2.693 14.769 0.506 5.476 39.832 5.319 0.000 *** Purity -0.325 0.722 0.755 0.164 3.171 -0.431 0.666 Rsquare = 0.165 (max possible = 7.58e-01 ) Likelihood ratio test p = 9.55e-06 Wald test p = 4.34e-06 Score (logrank) test p = 6.43e-10 SCD in LAML (n=173): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.144 1.155 0.083 0.981 1.359 1.730 0.084 · Age 0.037 1.037 0.008 1.021 1.054 4.510 0.000 *** Gendermale -0.218 0.804 0.218 0.525 1.232 -1.003 0.316 RaceBlack -0.299 0.741 1.106 0.085 6.475 -0.271 0.787 RaceWhite -0.775 0.461 1.019 0.063 3.393 -0.761 0.447 Rsquare = 0.172 (max possible = 9.96e-01 ) Likelihood ratio test p = 3.41e-05 Wald test p = 1.22e-04 Score (logrank) test p = 8.45e-05 SCD in LGG (n=516): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.485 0.615 0.093 0.512 0.739 -5.196 0.000 *** Age 0.059 1.061 0.008 1.045 1.077 7.716 0.000 *** Gendermale 0.077 1.080 0.195 0.736 1.583 0.392 0.695 RaceBlack 15.910 8117853.879 2168.866 0.000 Inf 0.007 0.994 RaceWhite 15.741 6855213.528 2168.866 0.000 Inf 0.007 0.994 Purity -1.010 0.364 0.400 0.166 0.798 -2.524 0.012 * Rsquare = 0.183 (max possible = 9.07e-01 ) Likelihood ratio test p = 4.98e-18 Wald test p = 1.42e-17 Score (logrank) test p = 2.42e-19 SCD in LIHC (n=371): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.082 1.086 0.058 0.969 1.217 1.410 0.159 Age 0.011 1.011 0.008 0.995 1.027 1.337 0.181 Gendermale -0.185 0.831 0.228 0.532 1.300 -0.810 0.418 RaceBlack 0.974 2.649 0.493 1.008 6.964 1.976 0.048 * RaceWhite 0.018 1.018 0.237 0.640 1.619 0.075 0.940 Stage2 0.360 1.434 0.262 0.857 2.398 1.373 0.170 Stage3 0.932 2.539 0.234 1.604 4.018 3.978 0.000 *** Stage4 1.539 4.659 0.619 1.384 15.679 2.485 0.013 * Purity 0.638 1.893 0.463 0.763 4.695 1.377 0.169 Rsquare = 0.091 (max possible = 9.66e-01 ) Likelihood ratio test p = 5.5e-04 Wald test p = 3.61e-04 Score (logrank) test p = 1.33e-04 SCD in LUAD (n=515): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.133 1.143 0.072 0.993 1.315 1.865 0.062 · Age 0.008 1.008 0.009 0.991 1.026 0.915 0.360 Gendermale -0.023 0.977 0.170 0.701 1.362 -0.137 0.891 RaceBlack 16.259 11512718.973 1880.518 0.000 Inf 0.009 0.993 RaceWhite 16.422 13552276.818 1880.518 0.000 Inf 0.009 0.993 Stage2 0.852 2.343 0.202 1.579 3.479 4.226 0.000 *** Stage3 0.983 2.674 0.218 1.742 4.102 4.501 0.000 *** Stage4 0.994 2.703 0.334 1.405 5.202 2.977 0.003 ** Purity 0.601 1.823 0.343 0.931 3.571 1.751 0.080 · Rsquare = 0.104 (max possible = 9.74e-01 ) Likelihood ratio test p = 5.47e-07 Wald test p = 1.01e-05 Score (logrank) test p = 1.09e-06 SCD in LUSC (n=501): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.001 0.999 0.079 0.856 1.166 -0.013 0.990 Age 0.016 1.016 0.009 0.998 1.035 1.741 0.082 · Gendermale 0.437 1.547 0.196 1.053 2.273 2.225 0.026 * RaceBlack 0.008 1.008 0.607 0.307 3.311 0.013 0.990 RaceWhite -0.518 0.595 0.564 0.197 1.799 -0.919 0.358 Stage2 0.212 1.236 0.188 0.856 1.785 1.129 0.259 Stage3 0.604 1.829 0.214 1.201 2.785 2.815 0.005 ** Stage4 0.759 2.137 0.795 0.450 10.145 0.955 0.339 Purity -0.345 0.708 0.366 0.346 1.450 -0.943 0.346 Rsquare = 0.05 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.42e-02 Wald test p = 1.87e-02 Score (logrank) test p = 1.61e-02 SCD in MESO (n=87): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.327 1.387 0.085 1.174 1.639 3.841 0.000 *** Age 0.017 1.017 0.015 0.987 1.048 1.120 0.263 Gendermale -0.207 0.813 0.336 0.421 1.569 -0.617 0.537 RaceBlack 0.080 1.083 1.526 0.054 21.532 0.052 0.958 RaceWhite -0.911 0.402 1.052 0.051 3.158 -0.866 0.386 Stage2 -0.175 0.839 0.455 0.344 2.047 -0.385 0.700 Stage3 -0.158 0.854 0.405 0.386 1.887 -0.391 0.696 Stage4 -0.018 0.982 0.470 0.391 2.465 -0.039 0.969 Purity -0.516 0.597 0.550 0.203 1.755 -0.938 0.348 Rsquare = 0.214 (max possible = 9.98e-01 ) Likelihood ratio test p = 1.54e-02 Wald test p = 2.13e-02 Score (logrank) test p = 1.47e-02 SCD in OV (n=303): Model: Surv(OS, EVENT) ~ `SCD` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.032 1.032 0.068 0.904 1.178 0.466 0.641 Age 0.036 1.036 0.008 1.020 1.053 4.397 0.000 *** RaceBlack -0.036 0.965 0.578 0.311 2.993 -0.062 0.951 RaceWhite -0.147 0.863 0.516 0.314 2.372 -0.285 0.775 Purity -0.441 0.643 0.708 0.161 2.576 -0.623 0.533 Rsquare = 0.082 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.05e-03 Wald test p = 9.22e-04 Score (logrank) test p = 7.59e-04 SCD in PAAD (n=179): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.169 1.184 0.107 0.960 1.460 1.577 0.115 Age 0.023 1.024 0.011 1.002 1.046 2.169 0.030 * Gendermale -0.196 0.822 0.217 0.537 1.258 -0.904 0.366 RaceBlack 0.017 1.017 0.740 0.239 4.335 0.023 0.981 RaceWhite 0.390 1.478 0.473 0.584 3.736 0.825 0.409 Stage2 0.574 1.775 0.437 0.753 4.182 1.312 0.190 Stage3 -0.219 0.803 1.091 0.095 6.820 -0.201 0.841 Stage4 0.106 1.112 0.827 0.220 5.623 0.129 0.898 Purity -0.714 0.489 0.413 0.218 1.100 -1.729 0.084 · Rsquare = 0.102 (max possible = 9.91e-01 ) Likelihood ratio test p = 3.78e-02 Wald test p = 5.82e-02 Score (logrank) test p = 5.83e-02 SCD in PCPG (n=181): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.284 1.329 0.319 0.710 2.484 0.890 0.374 Age 0.044 1.045 0.029 0.987 1.108 1.512 0.131 Gendermale 1.448 4.255 0.901 0.728 24.861 1.608 0.108 RaceBlack -0.942 0.390 18929.956 0.000 Inf 0.000 1.000 RaceWhite 16.779 19371340.140 15565.669 0.000 Inf 0.001 0.999 Purity 6.765 866.909 3.839 0.468 1606296.177 1.762 0.078 · Rsquare = 0.059 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.23e-01 Wald test p = 3.92e-01 Score (logrank) test p = 3.04e-01 SCD in PRAD (n=498): Model: Surv(OS, EVENT) ~ `SCD` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.196 1.217 0.256 0.737 2.008 0.768 0.443 Age 0.010 1.010 0.057 0.904 1.129 0.181 0.856 RaceBlack 15.172 3884058.180 6642.407 0.000 Inf 0.002 0.998 RaceWhite 16.252 11432585.392 6642.407 0.000 Inf 0.002 0.998 Purity 1.003 2.726 1.384 0.181 41.044 0.725 0.469 Rsquare = 0.008 (max possible = 1.83e-01 ) Likelihood ratio test p = 6.52e-01 Wald test p = 7.74e-01 Score (logrank) test p = 7.11e-01 SCD in READ (n=166): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.582 1.789 0.519 0.647 4.945 1.122 0.262 Age 0.129 1.138 0.051 1.030 1.257 2.543 0.011 * Gendermale -0.359 0.699 0.688 0.182 2.688 -0.522 0.602 RaceBlack 12.856 383259.655 10390.847 0.000 Inf 0.001 0.999 RaceWhite 11.627 112098.534 10390.847 0.000 Inf 0.001 0.999 Stage2 -1.849 0.157 1.264 0.013 1.875 -1.463 0.144 Stage3 -0.508 0.602 0.913 0.101 3.603 -0.556 0.578 Stage4 -0.374 0.688 0.985 0.100 4.742 -0.380 0.704 Purity 0.215 1.239 1.383 0.082 18.623 0.155 0.877 Rsquare = 0.223 (max possible = 7.22e-01 ) Likelihood ratio test p = 2.38e-02 Wald test p = 2.46e-01 Score (logrank) test p = 4.49e-02 SCD in SARC (n=260): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.136 1.146 0.067 1.006 1.306 2.045 0.041 * Age 0.021 1.022 0.008 1.005 1.038 2.551 0.011 * Gendermale 0.000 1.000 0.223 0.646 1.549 0.002 0.998 RaceBlack -0.094 0.910 1.086 0.108 7.649 -0.087 0.931 RaceWhite -0.508 0.601 1.024 0.081 4.477 -0.496 0.620 Purity 1.067 2.905 0.575 0.942 8.962 1.856 0.063 · Rsquare = 0.059 (max possible = 9.75e-01 ) Likelihood ratio test p = 2.8e-02 Wald test p = 3.46e-02 Score (logrank) test p = 3.74e-02 SCD in SKCM (n=471): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.017 1.017 0.067 0.893 1.159 0.261 0.794 Age 0.018 1.019 0.005 1.008 1.029 3.539 0.000 *** Gendermale -0.056 0.946 0.159 0.693 1.291 -0.352 0.725 RaceWhite -1.283 0.277 0.401 0.126 0.609 -3.197 0.001 ** Stage2 0.268 1.307 0.220 0.850 2.012 1.219 0.223 Stage3 0.607 1.835 0.204 1.229 2.740 2.969 0.003 ** Stage4 1.356 3.879 0.352 1.945 7.737 3.848 0.000 *** Purity 1.028 2.795 0.342 1.430 5.464 3.006 0.003 ** Rsquare = 0.124 (max possible = 9.92e-01 ) Likelihood ratio test p = 2.17e-08 Wald test p = 1.19e-08 Score (logrank) test p = 1.4e-09 SCD in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.205 8.150000e-01 0.200 0.551 1.205 -1.024 0.306 Age 0.011 1.011000e+00 0.016 0.979 1.043 0.654 0.513 Gendermale 0.192 1.211000e+00 0.431 0.520 2.820 0.444 0.657 RaceWhite -1.325 2.660000e-01 0.626 0.078 0.906 -2.117 0.034 * Stage2 17.523 4.077059e+07 6201.408 0.000 Inf 0.003 0.998 Stage3 18.005 6.602183e+07 6201.408 0.000 Inf 0.003 0.998 Stage4 20.367 7.003800e+08 6201.408 0.000 Inf 0.003 0.997 Purity 0.267 1.306000e+00 0.937 0.208 8.192 0.285 0.776 Rsquare = 0.156 (max possible = 8.69e-01 ) Likelihood ratio test p = 4.31e-02 Wald test p = 3.72e-02 Score (logrank) test p = 2.99e-03 SCD in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.031 1.032 0.072 0.896 1.188 0.434 0.664 Age 0.020 1.021 0.006 1.009 1.032 3.644 0.000 *** Gendermale -0.071 0.931 0.175 0.661 1.311 -0.408 0.684 RaceWhite -1.057 0.347 0.600 0.107 1.125 -1.763 0.078 · Stage2 0.139 1.149 0.232 0.729 1.811 0.597 0.550 Stage3 0.556 1.744 0.209 1.157 2.628 2.655 0.008 ** Stage4 1.146 3.144 0.401 1.434 6.895 2.859 0.004 ** Purity 1.160 3.191 0.373 1.537 6.623 3.114 0.002 ** Rsquare = 0.134 (max possible = 9.95e-01 ) Likelihood ratio test p = 1.02e-06 Wald test p = 1.65e-06 Score (logrank) test p = 6.21e-07 SCD in STAD (n=415): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.020 0.980 0.069 0.857 1.122 -0.288 0.774 Age 0.027 1.027 0.010 1.007 1.048 2.594 0.009 ** Gendermale 0.133 1.143 0.211 0.755 1.729 0.631 0.528 RaceBlack 0.281 1.324 0.450 0.548 3.197 0.624 0.532 RaceWhite 0.102 1.107 0.246 0.684 1.792 0.416 0.678 Stage2 0.494 1.638 0.390 0.762 3.520 1.265 0.206 Stage3 0.927 2.527 0.364 1.237 5.160 2.544 0.011 * Stage4 1.325 3.762 0.505 1.400 10.113 2.626 0.009 ** Purity -0.542 0.581 0.384 0.274 1.233 -1.414 0.157 Rsquare = 0.07 (max possible = 9.79e-01 ) Likelihood ratio test p = 1.33e-02 Wald test p = 1.81e-02 Score (logrank) test p = 1.46e-02 SCD in TGCT (n=150): Model: Surv(OS, EVENT) ~ `SCD` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -4.180 0.015 49948.610 0 Inf 0.000 1.000 Age -1.786 0.168 1669.154 0 Inf -0.001 0.999 RaceBlack 1.528 4.610 19311123.298 0 Inf 0.000 1.000 RaceWhite -47.075 0.000 22963411.627 0 Inf 0.000 1.000 Stage2 -3.066 0.047 40042.383 0 Inf 0.000 1.000 Stage3 17.104 26796656.866 150693.257 0 Inf 0.000 1.000 Purity 12.438 252128.025 207255.477 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.05e-03 SCD in THCA (n=509): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.476 1.610 0.273 0.944 2.746 1.747 0.081 · Age 0.157 1.169 0.030 1.103 1.240 5.237 0.000 *** Gendermale -0.210 0.810 0.651 0.226 2.905 -0.323 0.747 RaceBlack 17.569 42667614.367 9297.816 0.000 Inf 0.002 0.998 RaceWhite 17.148 28017209.488 9297.816 0.000 Inf 0.002 0.999 Stage2 0.001 1.001 1.085 0.119 8.396 0.001 0.999 Stage3 -0.093 0.911 0.883 0.161 5.146 -0.106 0.916 Stage4 1.365 3.917 0.999 0.553 27.740 1.367 0.172 Purity 2.683 14.626 1.157 1.515 141.240 2.319 0.020 * Rsquare = 0.156 (max possible = 3.47e-01 ) Likelihood ratio test p = 6.07e-11 Wald test p = 2.97e-04 Score (logrank) test p = 4.59e-11 SCD in THYM (n=120): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.024 0.976 0.362 0.480 1.985 -0.066 0.948 Age 0.049 1.050 0.032 0.986 1.118 1.530 0.126 Gendermale -0.182 0.833 0.734 0.198 3.514 -0.248 0.804 RaceBlack -16.581 0.000 10213.115 0.000 Inf -0.002 0.999 RaceWhite 0.511 1.667 1.107 0.190 14.603 0.462 0.644 Purity 0.388 1.474 1.096 0.172 12.634 0.354 0.723 Rsquare = 0.044 (max possible = 4.51e-01 ) Likelihood ratio test p = 5.31e-01 Wald test p = 6.63e-01 Score (logrank) test p = 5.73e-01 SCD in UCEC (n=545): Model: Surv(OS, EVENT) ~ `SCD` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.158 1.171 0.152 0.869 1.578 1.039 0.299 Age 0.053 1.054 0.016 1.021 1.087 3.280 0.001 ** RaceBlack -0.421 0.657 0.793 0.139 3.109 -0.530 0.596 RaceWhite -0.591 0.554 0.749 0.128 2.402 -0.790 0.430 Purity 0.382 1.465 0.654 0.407 5.279 0.584 0.559 Rsquare = 0.042 (max possible = 7.81e-01 ) Likelihood ratio test p = 3.31e-02 Wald test p = 3.96e-02 Score (logrank) test p = 3.8e-02 SCD in UCS (n=57): Model: Surv(OS, EVENT) ~ `SCD` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD -0.103 0.902 0.210 0.598 1.361 -0.491 0.623 Age 0.045 1.046 0.024 0.997 1.097 1.844 0.065 · RaceBlack 17.536 41280955.660 6494.899 0.000 Inf 0.003 0.998 RaceWhite 17.782 52795388.674 6494.899 0.000 Inf 0.003 0.998 Purity -0.941 0.390 1.059 0.049 3.111 -0.889 0.374 Rsquare = 0.123 (max possible = 9.83e-01 ) Likelihood ratio test p = 2.34e-01 Wald test p = 3.36e-01 Score (logrank) test p = 2.46e-01 SCD in UVM (n=80): Model: Surv(OS, EVENT) ~ `SCD` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SCD 0.429 1.536 0.355 0.765 3.083 1.207 0.227 Age 0.042 1.043 0.019 1.005 1.082 2.232 0.026 * Gendermale 0.414 1.513 0.492 0.577 3.970 0.842 0.400 Stage3 0.215 1.240 0.497 0.468 3.283 0.433 0.665 Stage4 3.715 41.078 1.213 3.813 442.537 3.064 0.002 ** Purity 1.830 6.234 1.245 0.543 71.524 1.470 0.142 Rsquare = 0.268 (max possible = 8.72e-01 ) Likelihood ratio test p = 5.24e-04 Wald test p = 2.63e-03 Score (logrank) test p = 1.63e-09 SREBF1 in ACC (n=79): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Purity 64 patients with 24 dying ( 15 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.239 0.788 0.150 0.587 1.057 -1.589 0.112 Age 0.002 1.002 0.014 0.975 1.030 0.148 0.882 Gendermale 0.388 1.474 0.418 0.650 3.345 0.929 0.353 RaceBlack 0.126 1.134 12618.235 0.000 Inf 0.000 1.000 RaceWhite 17.199 29467249.287 10816.309 0.000 Inf 0.002 0.999 Purity 2.526 12.508 2.223 0.160 975.155 1.137 0.256 Rsquare = 0.1 (max possible = 9.38e-01 ) Likelihood ratio test p = 3.47e-01 Wald test p = 5.2e-01 Score (logrank) test p = 3.7e-01 SREBF1 in BLCA (n=408): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 348 patients with 160 dying ( 60 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.116 1.123 0.082 0.957 1.319 1.420 0.156 Age 0.032 1.032 0.009 1.015 1.050 3.685 0.000 *** Gendermale -0.200 0.819 0.180 0.576 1.165 -1.111 0.266 RaceBlack 0.685 1.983 0.447 0.826 4.761 1.532 0.126 RaceWhite 0.131 1.140 0.354 0.569 2.282 0.370 0.712 Stage2 14.315 1647476.434 1897.928 0.000 Inf 0.008 0.994 Stage3 14.757 2564599.826 1897.928 0.000 Inf 0.008 0.994 Stage4 15.255 4220551.237 1897.928 0.000 Inf 0.008 0.994 Purity 0.062 1.063 0.343 0.543 2.084 0.179 0.858 Rsquare = 0.135 (max possible = 9.91e-01 ) Likelihood ratio test p = 8.55e-08 Wald test p = 4.59e-07 Score (logrank) test p = 1.41e-07 SREBF1 in BRCA (n=1100): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 878 patients with 121 dying ( 222 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.096 0.908 0.082 0.773 1.067 -1.173 0.241 Age 0.035 1.036 0.007 1.021 1.051 4.736 0.000 *** Gendermale 0.070 1.073 1.007 0.149 7.726 0.070 0.944 RaceBlack 0.021 1.021 0.619 0.304 3.432 0.033 0.974 RaceWhite -0.175 0.840 0.597 0.261 2.704 -0.293 0.770 Stage2 0.382 1.465 0.304 0.807 2.659 1.255 0.209 Stage3 1.168 3.215 0.313 1.741 5.937 3.732 0.000 *** Stage4 2.499 12.173 0.389 5.680 26.087 6.426 0.000 *** Purity 0.595 1.813 0.424 0.790 4.159 1.404 0.160 Rsquare = 0.082 (max possible = 7.85e-01 ) Likelihood ratio test p = 1.33e-12 Wald test p = 2.48e-16 Score (logrank) test p = 3.03e-22 SREBF1 in BRCA-Basal (n=191): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Race + Stage + Purity 163 patients with 24 dying ( 28 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.131 1.140000e+00 0.256 0.691 1.882 0.512 0.609 Age 0.008 1.008000e+00 0.018 0.973 1.045 0.445 0.656 RaceBlack -0.948 3.880000e-01 1.115 0.044 3.448 -0.850 0.395 RaceWhite -1.264 2.820000e-01 1.122 0.031 2.547 -1.127 0.260 Stage2 18.650 1.257351e+08 6477.152 0.000 Inf 0.003 0.998 Stage3 20.157 5.677078e+08 6477.152 0.000 Inf 0.003 0.998 Stage4 21.531 2.243794e+09 6477.153 0.000 Inf 0.003 0.997 Purity 0.795 2.215000e+00 0.970 0.331 14.830 0.820 0.412 Rsquare = 0.158 (max possible = 7.18e-01 ) Likelihood ratio test p = 4.7e-04 Wald test p = 6.91e-03 Score (logrank) test p = 4.33e-06 SREBF1 in BRCA-Her2 (n=82): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Race + Stage + Purity 59 patients with 11 dying ( 23 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.549 5.780000e-01 0.472 0.229 1.457 -1.163 0.245 Age 0.031 1.032000e+00 0.029 0.974 1.093 1.064 0.287 RaceBlack -3.395 3.400000e-02 1.852 0.001 1.264 -1.833 0.067 · RaceWhite -2.192 1.120000e-01 1.548 0.005 2.322 -1.416 0.157 Stage2 17.998 6.552804e+07 14915.454 0.000 Inf 0.001 0.999 Stage3 20.012 4.909660e+08 14915.454 0.000 Inf 0.001 0.999 Stage4 NA NA 0.000 NA NA NA NA Purity 3.358 2.872800e+01 2.325 0.302 2735.918 1.444 0.149 Rsquare = 0.384 (max possible = 6.68e-01 ) Likelihood ratio test p = 1.72e-04 Wald test p = 2.33e-01 Score (logrank) test p = 9.88e-15 SREBF1 in BRCA-LumA (n=568): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 464 patients with 55 dying ( 104 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.161 0.851 0.136 0.652 1.112 -1.182 0.237 Age 0.045 1.047 0.012 1.022 1.072 3.771 0.000 *** Gendermale -15.188 0.000 3382.257 0.000 Inf -0.004 0.996 RaceBlack -0.300 0.741 1.179 0.074 7.463 -0.255 0.799 RaceWhite 0.401 1.493 1.040 0.194 11.463 0.385 0.700 Stage2 0.248 1.282 0.379 0.610 2.694 0.656 0.512 Stage3 0.732 2.080 0.407 0.937 4.619 1.799 0.072 · Stage4 2.282 9.798 0.602 3.012 31.874 3.792 0.000 *** Purity 0.499 1.647 0.632 0.477 5.684 0.790 0.430 Rsquare = 0.073 (max possible = 6.81e-01 ) Likelihood ratio test p = 5.93e-05 Wald test p = 8.96e-06 Score (logrank) test p = 1.49e-07 SREBF1 in BRCA-LumB (n=219): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 157 patients with 25 dying ( 62 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.104 1.109 0.229 0.708 1.737 0.453 0.651 Age 0.051 1.053 0.021 1.010 1.097 2.407 0.016 * Gendermale 1.009 2.743 1.107 0.313 23.999 0.912 0.362 RaceBlack 16.540 15250780.988 6728.749 0.000 Inf 0.002 0.998 RaceWhite 15.958 8518572.707 6728.749 0.000 Inf 0.002 0.998 Stage2 0.660 1.935 1.074 0.236 15.885 0.615 0.539 Stage3 1.519 4.568 1.072 0.559 37.318 1.417 0.156 Stage4 2.115 8.290 1.175 0.829 82.897 1.800 0.072 · Purity 0.864 2.373 1.377 0.160 35.248 0.628 0.530 Rsquare = 0.106 (max possible = 6.98e-01 ) Likelihood ratio test p = 3.93e-02 Wald test p = 6.59e-02 Score (logrank) test p = 2.04e-02 SREBF1 in CESC (n=306): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Race + Purity 227 patients with 55 dying ( 79 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.197 0.821 0.159 0.602 1.120 -1.244 0.213 Age 0.013 1.013 0.010 0.993 1.034 1.308 0.191 RaceBlack 1.069 2.914 1.067 0.360 23.610 1.002 0.316 RaceWhite 0.760 2.139 1.016 0.292 15.673 0.748 0.454 Purity 0.520 1.681 0.731 0.401 7.048 0.711 0.477 Rsquare = 0.021 (max possible = 8.91e-01 ) Likelihood ratio test p = 4.53e-01 Wald test p = 4.88e-01 Score (logrank) test p = 4.82e-01 SREBF1 in CHOL (n=36): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 36 patients with 18 dying ( 0 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.086 1.090 0.346 0.553 2.146 0.248 0.804 Age 0.019 1.019 0.022 0.975 1.065 0.838 0.402 Gendermale 0.237 1.268 0.563 0.421 3.822 0.422 0.673 RaceBlack -0.451 0.637 1.549 0.031 13.269 -0.291 0.771 RaceWhite -1.135 0.321 0.922 0.053 1.957 -1.232 0.218 Stage2 0.619 1.857 0.693 0.477 7.228 0.893 0.372 Stage3 -15.504 0.000 6942.642 0.000 Inf -0.002 0.998 Stage4 0.767 2.153 0.709 0.537 8.636 1.082 0.279 Purity 1.967 7.152 1.592 0.316 162.106 1.236 0.217 Rsquare = 0.213 (max possible = 9.46e-01 ) Likelihood ratio test p = 4.74e-01 Wald test p = 6.54e-01 Score (logrank) test p = 4.86e-01 SREBF1 in COAD (n=458): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 258 patients with 64 dying ( 200 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.199 1.220 0.183 0.852 1.747 1.086 0.278 Age 0.023 1.023 0.011 1.001 1.046 2.039 0.041 * Gendermale 0.253 1.288 0.271 0.757 2.191 0.933 0.351 RaceBlack -0.383 0.682 0.829 0.134 3.457 -0.463 0.644 RaceWhite -0.427 0.653 0.775 0.143 2.983 -0.551 0.582 Stage2 0.226 1.253 0.562 0.416 3.770 0.401 0.688 Stage3 0.796 2.216 0.550 0.754 6.514 1.446 0.148 Stage4 1.904 6.715 0.553 2.272 19.840 3.445 0.001 ** Purity -0.189 0.828 0.605 0.253 2.708 -0.312 0.755 Rsquare = 0.113 (max possible = 9.04e-01 ) Likelihood ratio test p = 2.91e-04 Wald test p = 9.78e-05 Score (logrank) test p = 1.52e-05 SREBF1 in DLBC (n=48): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Purity 41 patients with 5 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -1.963 0.140 1.375 0.009 2.077 -1.428 0.153 Age 0.006 1.006 0.035 0.938 1.078 0.157 0.875 Gendermale 1.226 3.406 1.157 0.353 32.876 1.060 0.289 RaceBlack -1.312 0.269 1.957 0.006 12.461 -0.671 0.502 RaceWhite -2.389 0.092 1.296 0.007 1.164 -1.843 0.065 · Purity -4.574 0.010 3.129 0.000 4.748 -1.462 0.144 Rsquare = 0.183 (max possible = 5.58e-01 ) Likelihood ratio test p = 2.18e-01 Wald test p = 4.84e-01 Score (logrank) test p = 1.66e-01 SREBF1 in ESCA (n=185): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 140 patients with 47 dying ( 45 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.143 0.866 0.235 0.547 1.372 -0.612 0.541 Age 0.009 1.009 0.014 0.982 1.037 0.656 0.512 Gendermale 0.407 1.502 0.552 0.509 4.430 0.737 0.461 RaceBlack 0.358 1.430 1.069 0.176 11.619 0.335 0.738 RaceWhite -0.220 0.802 0.506 0.297 2.163 -0.436 0.663 Stage2 0.691 1.996 0.654 0.554 7.196 1.056 0.291 Stage3 1.460 4.305 0.671 1.155 16.049 2.174 0.030 * Stage4 2.871 17.661 0.774 3.871 80.582 3.707 0.000 *** Purity 0.429 1.535 0.847 0.292 8.078 0.506 0.613 Rsquare = 0.143 (max possible = 9.32e-01 ) Likelihood ratio test p = 1.01e-02 Wald test p = 4.78e-03 Score (logrank) test p = 3.91e-04 SREBF1 in GBM (n=153): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Purity 135 patients with 108 dying ( 18 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.185 1.203 0.133 0.926 1.562 1.384 0.166 Age 0.027 1.028 0.008 1.011 1.044 3.297 0.001 ** Gendermale -0.087 0.917 0.213 0.604 1.392 -0.406 0.685 RaceBlack 0.524 1.689 0.726 0.407 7.009 0.722 0.470 RaceWhite -0.262 0.769 0.615 0.231 2.568 -0.426 0.670 Purity -0.866 0.421 0.560 0.140 1.260 -1.547 0.122 Rsquare = 0.141 (max possible = 9.98e-01 ) Likelihood ratio test p = 2.17e-03 Wald test p = 2.97e-03 Score (logrank) test p = 2.49e-03 SREBF1 in HNSC (n=522): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 411 patients with 176 dying ( 111 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.117 0.889 0.094 0.739 1.069 -1.247 0.212 Age 0.023 1.023 0.008 1.008 1.039 3.003 0.003 ** Gendermale -0.229 0.795 0.173 0.567 1.116 -1.327 0.185 RaceBlack 0.139 1.150 0.559 0.384 3.438 0.250 0.803 RaceWhite -0.264 0.768 0.511 0.282 2.091 -0.516 0.606 Stage2 0.626 1.871 0.544 0.644 5.431 1.151 0.250 Stage3 0.852 2.345 0.537 0.819 6.714 1.588 0.112 Stage4 1.276 3.583 0.510 1.318 9.744 2.500 0.012 * Purity 0.050 1.051 0.370 0.509 2.172 0.135 0.892 Rsquare = 0.073 (max possible = 9.89e-01 ) Likelihood ratio test p = 2.85e-04 Wald test p = 8.29e-04 Score (logrank) test p = 5.88e-04 SREBF1 in HNSC-HPV+ (n=98): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 65 patients with 23 dying ( 33 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.452 6.370000e-01 0.266 0.378 1.071 -1.700 0.089 · Age 0.005 1.005000e+00 0.026 0.955 1.058 0.203 0.839 Gendermale -0.237 7.890000e-01 0.569 0.258 2.409 -0.416 0.677 RaceBlack 19.500 2.943384e+08 20647.452 0.000 Inf 0.001 0.999 RaceWhite 18.850 1.536217e+08 20647.452 0.000 Inf 0.001 0.999 Stage2 18.420 9.994747e+07 8320.149 0.000 Inf 0.002 0.998 Stage3 17.732 5.021784e+07 8320.149 0.000 Inf 0.002 0.998 Stage4 18.372 9.522002e+07 8320.149 0.000 Inf 0.002 0.998 Purity -1.270 2.810000e-01 1.061 0.035 2.246 -1.197 0.231 Rsquare = 0.129 (max possible = 9.17e-01 ) Likelihood ratio test p = 4.42e-01 Wald test p = 7.06e-01 Score (logrank) test p = 5.66e-01 SREBF1 in HNSC-HPV- (n=422): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 346 patients with 153 dying ( 76 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.087 0.917 0.107 0.744 1.130 -0.812 0.417 Age 0.028 1.029 0.009 1.011 1.046 3.277 0.001 ** Gendermale -0.270 0.763 0.184 0.533 1.094 -1.470 0.142 RaceBlack -0.006 0.994 0.564 0.329 3.005 -0.010 0.992 RaceWhite -0.408 0.665 0.513 0.243 1.815 -0.797 0.426 Stage2 0.374 1.453 0.554 0.491 4.303 0.674 0.500 Stage3 0.727 2.068 0.541 0.717 5.971 1.344 0.179 Stage4 1.167 3.213 0.513 1.176 8.778 2.276 0.023 * Purity 0.284 1.329 0.410 0.595 2.967 0.694 0.488 Rsquare = 0.087 (max possible = 9.89e-01 ) Likelihood ratio test p = 2.62e-04 Wald test p = 8.06e-04 Score (logrank) test p = 5.84e-04 SREBF1 in KICH (n=66): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 63 patients with 9 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p SREBF1 0.248 1.282000e+00 0.538 0.447 3.680000e+00 0.462 0.644 Age 0.078 1.081000e+00 0.030 1.020 1.145000e+00 2.638 0.008 Gendermale -0.769 4.640000e-01 0.728 0.111 1.931000e+00 -1.056 0.291 RaceBlack -17.016 0.000000e+00 6205.577 0.000 Inf -0.003 0.998 RaceWhite -1.723 1.790000e-01 1.160 0.018 1.734000e+00 -1.485 0.137 Stage2 15.945 8.409858e+06 0.847 1598608.053 4.424205e+07 18.823 0.000 Stage3 16.954 2.306083e+07 0.777 5027962.881 1.057688e+08 21.816 0.000 Stage4 19.436 2.761095e+08 0.896 47703623.042 1.598127e+09 21.696 0.000 Purity 1.187 3.278000e+00 3.781 0.002 5.421246e+03 0.314 0.754 signif SREBF1 Age ** Gendermale RaceBlack RaceWhite Stage2 *** Stage3 *** Stage4 *** Purity Rsquare = 0.347 (max possible = 6.71e-01 ) Likelihood ratio test p = 1.46e-03 Wald test p = 9.76e-277 Score (logrank) test p = 1.04e-08 SREBF1 in KIRC (n=533): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 450 patients with 138 dying ( 83 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.245 1.278 0.125 1.000 1.634 1.956 0.050 · Age 0.037 1.037 0.008 1.020 1.054 4.359 0.000 *** Gendermale 0.015 1.015 0.190 0.700 1.473 0.079 0.937 RaceBlack 0.118 1.125 1.057 0.142 8.939 0.111 0.911 RaceWhite 0.123 1.131 1.015 0.155 8.261 0.121 0.903 Stage2 0.169 1.184 0.346 0.602 2.331 0.489 0.625 Stage3 0.755 2.128 0.232 1.351 3.353 3.256 0.001 ** Stage4 1.863 6.442 0.223 4.162 9.971 8.357 0.000 *** Purity -0.045 0.956 0.365 0.467 1.955 -0.124 0.901 Rsquare = 0.181 (max possible = 9.65e-01 ) Likelihood ratio test p = 1.77e-15 Wald test p = 2.77e-15 Score (logrank) test p = 1.13e-18 SREBF1 in KIRP (n=290): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 219 patients with 34 dying ( 71 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.168 1.183 0.355 0.590 2.373 0.472 0.637 Age 0.008 1.008 0.016 0.977 1.040 0.517 0.605 Gendermale -0.522 0.593 0.386 0.278 1.265 -1.351 0.177 RaceBlack -1.974 0.139 1.200 0.013 1.460 -1.645 0.100 RaceWhite -2.030 0.131 1.178 0.013 1.320 -1.724 0.085 · Stage2 -0.446 0.640 1.058 0.081 5.092 -0.421 0.673 Stage3 1.636 5.134 0.427 2.223 11.854 3.831 0.000 *** Stage4 2.750 15.635 0.518 5.665 43.149 5.309 0.000 *** Purity -0.261 0.770 0.754 0.176 3.374 -0.346 0.729 Rsquare = 0.164 (max possible = 7.58e-01 ) Likelihood ratio test p = 1.06e-05 Wald test p = 3.25e-06 Score (logrank) test p = 5.97e-10 SREBF1 in LAML (n=173): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race 149 patients with 93 dying ( 24 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.341 1.406 0.149 1.050 1.883 2.287 0.022 * Age 0.032 1.032 0.008 1.015 1.049 3.766 0.000 *** Gendermale -0.282 0.754 0.223 0.487 1.166 -1.269 0.205 RaceBlack -0.471 0.625 1.107 0.071 5.471 -0.425 0.671 RaceWhite -0.801 0.449 1.019 0.061 3.306 -0.786 0.432 Rsquare = 0.185 (max possible = 9.96e-01 ) Likelihood ratio test p = 1.15e-05 Wald test p = 2.21e-05 Score (logrank) test p = 1.47e-05 SREBF1 in LGG (n=516): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Purity 463 patients with 112 dying ( 53 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.164 0.849 0.101 0.696 1.035 -1.624 0.104 Age 0.062 1.064 0.008 1.048 1.080 8.135 0.000 *** Gendermale 0.115 1.121 0.195 0.765 1.644 0.587 0.557 RaceBlack 15.611 6021763.000 2049.335 0.000 Inf 0.008 0.994 RaceWhite 15.553 5684247.614 2049.335 0.000 Inf 0.008 0.994 Purity -1.090 0.336 0.411 0.150 0.752 -2.653 0.008 ** Rsquare = 0.141 (max possible = 9.07e-01 ) Likelihood ratio test p = 3.45e-13 Wald test p = 2.94e-13 Score (logrank) test p = 2.37e-14 SREBF1 in LIHC (n=371): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 310 patients with 106 dying ( 61 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.049 1.050 0.092 0.878 1.257 0.537 0.591 Age 0.011 1.011 0.008 0.995 1.027 1.382 0.167 Gendermale -0.138 0.871 0.225 0.560 1.355 -0.613 0.540 RaceBlack 0.929 2.533 0.494 0.961 6.672 1.880 0.060 · RaceWhite -0.004 0.996 0.237 0.625 1.585 -0.018 0.986 Stage2 0.333 1.396 0.264 0.833 2.340 1.265 0.206 Stage3 0.956 2.601 0.235 1.641 4.121 4.070 0.000 *** Stage4 1.584 4.875 0.619 1.450 16.391 2.560 0.010 * Purity 0.575 1.777 0.458 0.724 4.360 1.255 0.209 Rsquare = 0.085 (max possible = 9.66e-01 ) Likelihood ratio test p = 1.08e-03 Wald test p = 6.63e-04 Score (logrank) test p = 2.5e-04 SREBF1 in LUAD (n=515): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 421 patients with 150 dying ( 94 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.131 0.877 0.107 0.712 1.081 -1.227 0.220 Age 0.006 1.006 0.009 0.988 1.024 0.648 0.517 Gendermale 0.045 1.046 0.171 0.748 1.462 0.264 0.792 RaceBlack 16.030 9159031.501 1892.997 0.000 Inf 0.008 0.993 RaceWhite 16.206 10917105.988 1892.997 0.000 Inf 0.009 0.993 Stage2 0.890 2.435 0.202 1.639 3.617 4.407 0.000 *** Stage3 1.041 2.833 0.219 1.844 4.352 4.754 0.000 *** Stage4 1.005 2.732 0.334 1.419 5.261 3.007 0.003 ** Purity 0.616 1.852 0.343 0.946 3.624 1.798 0.072 · Rsquare = 0.1 (max possible = 9.74e-01 ) Likelihood ratio test p = 1.27e-06 Wald test p = 1.94e-05 Score (logrank) test p = 2.1e-06 SREBF1 in LUSC (n=501): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 370 patients with 161 dying ( 131 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.017 1.017 0.100 0.835 1.238 0.170 0.865 Age 0.016 1.017 0.009 0.998 1.035 1.754 0.079 · Gendermale 0.433 1.541 0.195 1.052 2.257 2.223 0.026 * RaceBlack 0.008 1.008 0.606 0.307 3.307 0.014 0.989 RaceWhite -0.519 0.595 0.563 0.197 1.794 -0.922 0.356 Stage2 0.209 1.233 0.187 0.854 1.779 1.117 0.264 Stage3 0.602 1.825 0.215 1.199 2.779 2.805 0.005 ** Stage4 0.767 2.154 0.796 0.453 10.246 0.964 0.335 Purity -0.355 0.701 0.369 0.340 1.447 -0.960 0.337 Rsquare = 0.05 (max possible = 9.87e-01 ) Likelihood ratio test p = 2.4e-02 Wald test p = 1.87e-02 Score (logrank) test p = 1.61e-02 SREBF1 in MESO (n=87): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 85 patients with 72 dying ( 2 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.339 1.403 0.182 0.982 2.005 1.862 0.063 · Age 0.020 1.020 0.016 0.989 1.053 1.242 0.214 Gendermale -0.296 0.743 0.338 0.384 1.441 -0.878 0.380 RaceBlack -0.285 0.752 1.549 0.036 15.670 -0.184 0.854 RaceWhite -0.859 0.424 1.065 0.053 3.414 -0.807 0.420 Stage2 -0.211 0.810 0.458 0.330 1.989 -0.460 0.646 Stage3 -0.158 0.854 0.410 0.383 1.906 -0.386 0.700 Stage4 -0.096 0.909 0.473 0.359 2.298 -0.202 0.840 Purity -0.797 0.451 0.544 0.155 1.310 -1.463 0.143 Rsquare = 0.097 (max possible = 9.98e-01 ) Likelihood ratio test p = 4.69e-01 Wald test p = 4.85e-01 Score (logrank) test p = 4.71e-01 SREBF1 in OV (n=303): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Race + Purity 238 patients with 153 dying ( 65 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.013 1.013 0.094 0.842 1.218 0.136 0.891 Age 0.036 1.037 0.008 1.020 1.053 4.398 0.000 *** RaceBlack -0.055 0.947 0.577 0.306 2.931 -0.095 0.924 RaceWhite -0.155 0.856 0.515 0.312 2.351 -0.301 0.763 Purity -0.526 0.591 0.686 0.154 2.267 -0.767 0.443 Rsquare = 0.081 (max possible = 9.97e-01 ) Likelihood ratio test p = 1.15e-03 Wald test p = 1e-03 Score (logrank) test p = 8.33e-04 SREBF1 in PAAD (n=179): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 165 patients with 89 dying ( 14 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.137 0.872 0.168 0.627 1.212 -0.816 0.414 Age 0.021 1.021 0.011 1.000 1.043 1.932 0.053 · Gendermale -0.218 0.804 0.217 0.526 1.230 -1.004 0.315 RaceBlack 0.016 1.016 0.740 0.238 4.332 0.022 0.983 RaceWhite 0.357 1.429 0.474 0.564 3.621 0.752 0.452 Stage2 0.559 1.749 0.444 0.733 4.172 1.260 0.208 Stage3 -0.355 0.701 1.100 0.081 6.061 -0.322 0.747 Stage4 0.201 1.222 0.825 0.243 6.153 0.243 0.808 Purity -0.659 0.517 0.408 0.233 1.150 -1.618 0.106 Rsquare = 0.092 (max possible = 9.91e-01 ) Likelihood ratio test p = 6.83e-02 Wald test p = 9.74e-02 Score (logrank) test p = 9.18e-02 SREBF1 in PCPG (n=181): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Purity 164 patients with 7 dying ( 17 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.003 0.997 0.336 0.516 1.925 -0.009 0.993 Age 0.038 1.039 0.028 0.982 1.098 1.331 0.183 Gendermale 1.407 4.082 0.897 0.704 23.667 1.569 0.117 RaceBlack -0.199 0.819 19987.145 0.000 Inf 0.000 1.000 RaceWhite 17.281 32001624.557 16114.990 0.000 Inf 0.001 0.999 Purity 5.611 273.543 3.603 0.235 319082.947 1.557 0.119 Rsquare = 0.055 (max possible = 3.07e-01 ) Likelihood ratio test p = 1.62e-01 Wald test p = 4.15e-01 Score (logrank) test p = 3.04e-01 SREBF1 in PRAD (n=498): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Race + Purity 403 patients with 9 dying ( 95 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.266 1.304 0.450 0.540 3.150 0.591 0.555 Age 0.011 1.011 0.056 0.905 1.129 0.189 0.850 RaceBlack 15.226 4098872.715 6707.779 0.000 Inf 0.002 0.998 RaceWhite 16.308 12091973.718 6707.779 0.000 Inf 0.002 0.998 Purity 1.024 2.786 1.395 0.181 42.862 0.735 0.463 Rsquare = 0.008 (max possible = 1.83e-01 ) Likelihood ratio test p = 6.9e-01 Wald test p = 8.15e-01 Score (logrank) test p = 7.54e-01 SREBF1 in READ (n=166): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 76 patients with 14 dying ( 90 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.860 2.363 0.679 0.625 8.937 1.267 0.205 Age 0.133 1.142 0.052 1.032 1.265 2.557 0.011 * Gendermale -0.237 0.789 0.683 0.207 3.007 -0.347 0.728 RaceBlack 12.784 356607.615 10566.467 0.000 Inf 0.001 0.999 RaceWhite 11.415 90656.525 10566.467 0.000 Inf 0.001 0.999 Stage2 -1.930 0.145 1.260 0.012 1.717 -1.531 0.126 Stage3 -0.417 0.659 0.914 0.110 3.950 -0.457 0.648 Stage4 -0.594 0.552 1.061 0.069 4.411 -0.560 0.575 Purity -0.429 0.651 1.375 0.044 9.644 -0.312 0.755 Rsquare = 0.225 (max possible = 7.22e-01 ) Likelihood ratio test p = 2.18e-02 Wald test p = 2.49e-01 Score (logrank) test p = 3.9e-02 SREBF1 in SARC (n=260): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Purity 233 patients with 90 dying ( 27 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.270 0.763 0.118 0.606 0.962 -2.293 0.022 * Age 0.022 1.022 0.008 1.006 1.039 2.612 0.009 ** Gendermale 0.025 1.025 0.223 0.662 1.586 0.111 0.912 RaceBlack -0.183 0.832 1.086 0.099 6.993 -0.169 0.866 RaceWhite -0.517 0.596 1.023 0.080 4.426 -0.506 0.613 Purity 0.880 2.411 0.555 0.812 7.154 1.585 0.113 Rsquare = 0.064 (max possible = 9.75e-01 ) Likelihood ratio test p = 1.71e-02 Wald test p = 2.39e-02 Score (logrank) test p = 2.49e-02 SREBF1 in SKCM (n=471): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 390 patients with 186 dying ( 81 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.142 0.867 0.092 0.725 1.038 -1.551 0.121 Age 0.018 1.018 0.005 1.008 1.029 3.497 0.000 *** Gendermale -0.062 0.939 0.158 0.690 1.280 -0.396 0.692 RaceWhite -1.315 0.268 0.402 0.122 0.590 -3.273 0.001 ** Stage2 0.310 1.363 0.220 0.885 2.100 1.405 0.160 Stage3 0.630 1.878 0.205 1.257 2.806 3.075 0.002 ** Stage4 1.383 3.987 0.353 1.996 7.963 3.919 0.000 *** Purity 0.982 2.669 0.340 1.372 5.193 2.891 0.004 ** Rsquare = 0.129 (max possible = 9.92e-01 ) Likelihood ratio test p = 7.64e-09 Wald test p = 4.49e-09 Score (logrank) test p = 5.66e-10 SREBF1 in SKCM-Primary (n=103): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 94 patients with 26 dying ( 9 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.179 1.197000e+00 0.286 0.683 2.097 0.627 0.531 Age 0.010 1.010000e+00 0.016 0.978 1.043 0.590 0.555 Gendermale 0.222 1.249000e+00 0.434 0.533 2.925 0.512 0.609 RaceWhite -1.234 2.910000e-01 0.618 0.087 0.978 -1.996 0.046 * Stage2 17.617 4.476820e+07 6201.972 0.000 Inf 0.003 0.998 Stage3 18.113 7.355122e+07 6201.972 0.000 Inf 0.003 0.998 Stage4 20.361 6.959184e+08 6201.972 0.000 Inf 0.003 0.997 Purity 0.208 1.231000e+00 0.955 0.190 7.998 0.218 0.828 Rsquare = 0.15 (max possible = 8.69e-01 ) Likelihood ratio test p = 5.39e-02 Wald test p = 4.9e-02 Score (logrank) test p = 3.96e-03 SREBF1 in SKCM-Metastasis (n=368): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 296 patients with 160 dying ( 72 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.172 0.842 0.099 0.693 1.023 -1.732 0.083 · Age 0.020 1.020 0.006 1.009 1.032 3.570 0.000 *** Gendermale -0.072 0.931 0.173 0.663 1.306 -0.416 0.678 RaceWhite -1.072 0.342 0.600 0.106 1.109 -1.787 0.074 · Stage2 0.193 1.213 0.233 0.769 1.916 0.830 0.406 Stage3 0.589 1.802 0.210 1.194 2.720 2.803 0.005 ** Stage4 1.187 3.277 0.401 1.492 7.197 2.956 0.003 ** Purity 1.104 3.017 0.369 1.463 6.223 2.990 0.003 ** Rsquare = 0.142 (max possible = 9.95e-01 ) Likelihood ratio test p = 2.98e-07 Wald test p = 5.3e-07 Score (logrank) test p = 2.21e-07 SREBF1 in STAD (n=415): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 289 patients with 111 dying ( 126 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.235 0.791 0.117 0.628 0.995 -2.000 0.046 * Age 0.030 1.030 0.010 1.010 1.051 2.886 0.004 ** Gendermale 0.128 1.137 0.207 0.758 1.706 0.620 0.535 RaceBlack 0.335 1.399 0.451 0.578 3.382 0.745 0.457 RaceWhite 0.207 1.230 0.250 0.753 2.007 0.826 0.409 Stage2 0.571 1.770 0.392 0.820 3.819 1.454 0.146 Stage3 0.999 2.716 0.366 1.326 5.561 2.732 0.006 ** Stage4 1.334 3.798 0.506 1.408 10.245 2.636 0.008 ** Purity -0.510 0.601 0.381 0.285 1.267 -1.339 0.180 Rsquare = 0.083 (max possible = 9.79e-01 ) Likelihood ratio test p = 3.05e-03 Wald test p = 4.02e-03 Score (logrank) test p = 3.23e-03 SREBF1 in TGCT (n=150): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Race + Stage + Purity 75 patients with 2 dying ( 75 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -10.195 0.000 21848.675 0 Inf 0.000 1.000 Age -2.068 0.126 1682.936 0 Inf -0.001 0.999 RaceBlack 5.591 267.912 2900344.972 0 Inf 0.000 1.000 RaceWhite -47.008 0.000 17966238.879 0 Inf 0.000 1.000 Stage2 11.647 114387.445 41505.704 0 Inf 0.000 1.000 Stage3 11.220 74629.288 126924.731 0 Inf 0.000 1.000 Purity 17.008 24359471.048 230195.902 0 Inf 0.000 1.000 Rsquare = 0.14 (max possible = 1.4e-01 ) Likelihood ratio test p = 1.25e-01 Wald test p = 1e+00 Score (logrank) test p = 3.3e-03 SREBF1 in THCA (n=509): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Stage + Purity 395 patients with 16 dying ( 114 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.139 1.149 0.407 0.518 2.549 0.341 0.733 Age 0.148 1.159 0.029 1.096 1.226 5.169 0.000 *** Gendermale -0.091 0.913 0.636 0.262 3.179 -0.142 0.887 RaceBlack 17.068 25842925.034 6733.721 0.000 Inf 0.003 0.998 RaceWhite 16.824 20256334.638 6733.721 0.000 Inf 0.002 0.998 Stage2 -0.167 0.846 1.091 0.100 7.181 -0.153 0.878 Stage3 0.218 1.243 0.856 0.232 6.661 0.254 0.799 Stage4 1.630 5.105 0.991 0.732 35.616 1.645 0.100 Purity 2.221 9.213 1.096 1.075 78.971 2.026 0.043 * Rsquare = 0.149 (max possible = 3.47e-01 ) Likelihood ratio test p = 2.41e-10 Wald test p = 4.15e-04 Score (logrank) test p = 6.04e-11 SREBF1 in THYM (n=120): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Race + Purity 113 patients with 9 dying ( 7 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.009 1.009 0.405 0.457 2.231 0.023 0.982 Age 0.050 1.051 0.032 0.988 1.118 1.576 0.115 Gendermale -0.175 0.839 0.736 0.198 3.551 -0.238 0.812 RaceBlack -16.581 0.000 10019.878 0.000 Inf -0.002 0.999 RaceWhite 0.493 1.638 1.137 0.176 15.199 0.434 0.664 Purity 0.385 1.469 1.097 0.171 12.614 0.351 0.726 Rsquare = 0.044 (max possible = 4.51e-01 ) Likelihood ratio test p = 5.32e-01 Wald test p = 6.66e-01 Score (logrank) test p = 5.74e-01 SREBF1 in UCEC (n=545): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Race + Purity 283 patients with 43 dying ( 262 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.337 0.714 0.193 0.489 1.043 -1.740 0.082 · Age 0.047 1.048 0.016 1.017 1.081 3.035 0.002 ** RaceBlack -0.633 0.531 0.809 0.109 2.596 -0.781 0.435 RaceWhite -0.626 0.535 0.751 0.123 2.330 -0.834 0.404 Purity 0.399 1.490 0.654 0.414 5.369 0.610 0.542 Rsquare = 0.048 (max possible = 7.81e-01 ) Likelihood ratio test p = 1.57e-02 Wald test p = 1.43e-02 Score (logrank) test p = 1.31e-02 SREBF1 in UCS (n=57): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Race + Purity 52 patients with 32 dying ( 5 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 -0.242 0.785 0.218 0.512 1.202 -1.113 0.266 Age 0.047 1.048 0.024 0.999 1.099 1.920 0.055 · RaceBlack 17.285 32115345.168 6554.033 0.000 Inf 0.003 0.998 RaceWhite 17.558 42193886.031 6554.033 0.000 Inf 0.003 0.998 Purity -1.244 0.288 1.111 0.033 2.546 -1.119 0.263 Rsquare = 0.14 (max possible = 9.83e-01 ) Likelihood ratio test p = 1.66e-01 Wald test p = 2.41e-01 Score (logrank) test p = 1.72e-01 SREBF1 in UVM (n=80): Model: Surv(OS, EVENT) ~ `SREBF1` + Age + Gender + Stage + Purity 77 patients with 22 dying ( 3 missing obs. ) coef HR se(coef) 95%CI_l 95%CI_u z p signif SREBF1 0.442 1.555 0.384 0.733 3.301 1.151 0.250 Age 0.046 1.047 0.020 1.006 1.089 2.272 0.023 * Gendermale 0.349 1.417 0.490 0.543 3.701 0.712 0.476 Stage3 0.141 1.151 0.522 0.414 3.201 0.270 0.787 Stage4 3.725 41.477 1.215 3.833 448.866 3.066 0.002 ** Purity 1.757 5.792 1.200 0.552 60.808 1.464 0.143 Rsquare = 0.266 (max possible = 8.72e-01 ) Likelihood ratio test p = 5.7e-04 Wald test p = 2.18e-03 Score (logrank) test p = 1.46e-09