Question: R survival analysis : surv_pvalue vs fit.coxph for log-rank-test pvalue
0
ZheFrench250 wrote:

I have different value for test\$pval and and other.pval that should return the same log-rank test p-value, no ?

``````surv_object <- Surv(time = as.numeric(final_group_annotated[,time]), event = final_group_annotated[,opt\$endPoint] )it1 <- survfit(surv_object ~ group, data = final_group_annotated)

test=surv_pvalue(fit1, final_group_annotated)
print(test\$pval)
``````

0.3427874

``````fit.coxph <- coxph(surv_object ~ group, data = final_group_annotated)
print(summary(fit.coxph))

coxph(formula = surv_object ~ group, data = final_group_annotated)

n= 188, number of events= 30

coef exp(coef) se(coef)      z Pr(>|z|)
groupgroup2 -0.3482    0.7060   0.3689 -0.944    0.345

exp(coef) exp(-coef) lower .95 upper .95
groupgroup2     0.706      1.417    0.3426     1.455

Concordance= 0.538  (se = 0.049 )
Likelihood ratio test= 0.87  on 1 df,   p=0.4
Wald test            = 0.89  on 1 df,   p=0.3
Score (logrank) test = 0.9  on 1 df,   p=0.3

other.pval <- coef(summary(fit.coxph))[,5]
print(other.pval)
``````

0.3452066

survival analysis R • 53 views
modified 4 days ago by Kevin Blighe51k • written 4 days ago by ZheFrench250
2
Kevin Blighe51k wrote:

The p-value returned by `Surv()` is the log-rank p-value from the score test; so, you should be comparing this to the log-rank p-value from the Cox PH model. I went over this recently in this thread: A: survfit(Surv()) P-value interpretation for 3 survival curves?

## ------------------------------------

The way that you are doing it, i.e.:

``````coef(summary(fit.coxph))[,5]
``````

This will return multiple p-values when there are multiple strata, one p-value representing a single stratum / coefficient compared to the reference stratum.

To extract the log-rank p-value for the overall model, you need to use:

``````summary(coxfit)\$sctest
``````

Kevin