Coxph(Formula = Surv(Time*, Status ) Stage + Grade + 5% Genomic Changes)

Supplementary Table 1

A1: Multivariate Cox proportional hazards model to identify statistically independent factors in overall survival in 148 tumors.

coxph(formula = Surv(time*, status**) ~ stage + grade + 5% genomic changes)

coef exp(coef) se(coef) z p

stage 1.084 2.96 0.284 3.81 0.00014

grade 0.918 2.50 0.282 3.26 0.00110

5% genomic changes 0.579 1.78 0.284 2.04 0.04200

Rsquare= 0.165 (max possible= 0.964)

Likelihood ratio test= 26.7 on 3 df, p=6.79e-06

Wald test = 26.2 on 3 df, p=8.56e-06

Score (logrank) test = 28.2 on 3 df, p=3.36e-06

A2: Multivariate Cox proportional hazards model to identify statistically independent factors in overall survival in 148 tumors.

coxph(formula = Surv(time*, status**) ~ (stage + grade + 11% genomic changes))

coef exp(coef) se(coef) z p

stage 1.172 3.23 0.292 4.01 0.00006

grade 1.028 2.79 0.283 3.63 0.00028

11% genomic changes 0.907 2.48 0.310 2.93 0.00340

Rsquare= 0.185 (max possible= 0.964)

Likelihood ratio test= 30.3 on 3 df, p=1.21e-06

Wald test = 28.9 on 3 df, p=2.34e-06

Score (logrank) test = 31.8 on 3 df, p=5.92e-07

B: Multivariate Cox proportional hazards model to assess all the clusters along with clinical variable such as stage, size, stage and ER status

coxph(formula = Surv(time*, status**) ~ (stage + grade + cluster3 + cluster3:grade))

coef exp(coef) se(coef) z p

stage 0.93 2.534 0.284 3.28 0.00100

grade 1.29 3.631 0.339 3.80 0.00014

cluster3 2.43 11.388 1.042 2.33 0.02000

cluster3:grade -1.39 0.249 0.618 -2.25 0.02400

Rsquare= 0.168 (max possible= 0.964)

Likelihood ratio test= 27.3 on 4 df, p=1.76e-05

Wald test = 26.7 on 4 df, p=2.31e-05

Score (logrank) test = 29.5 on 4 df, p=6.23e-06

C: Multivariate Cox proportional hazards model to assess all the clusters along with clinical variable such as stage, size, stage and ER status

Call:

coxph(formula = Surv(time*, status**) ~ (ER + stage + grade + size + PTPN1 + STK6 + ZNF217 + CYP24))

n=146 (2 observations deleted due to missing)

coef exp(coef) se(coef) z p

ER 0.102 1.107 0.342 0.298 0.7700

stage 0.899 2.456 0.293 3.0710.0021

grade 0.773 2.167 0.347 2.227 0.0260

size 0.427 1.533 0.324 1.317 0.1900

PTPN1 0.584 1.794 0.588 0.993 0.3200

STK6 -0.123 0.884 0.640 -0.192 0.8500

ZNF217 0.541 1.717 0.596 0.907 0.3600

CYP24 -0.197 0.821 0.526 -0.375 0.7100

Rsquare= 0.172 (max possible= 0.965 )

Likelihood ratio test= 27.6 on 8 df, p=0.000561

Wald test = 28.1 on 8 df, p=0.000455

Score (logrank) test = 31.1 on 8 df, p=0.000134

* survival time

** status – dead/alive

coef – coefficient

exp – expected

se – standard error

z – test score

p – pvalue

df – degree of freedom