Corrected Time-dependent Cox (Gender as binary)
n = 656, events = 394
Call:
coxph(formula = Surv(OS_days, event) ~ Grade_num + tt(Grade_num) + 
    Gender_binary + Age_scaled, data = cg_complete, tt = function(x, 
    t, ...) x * log(t))

  n= 656, number of events= 394 

                      coef exp(coef) se(coef)      z Pr(>|z|)    
Grade_num         -3.62245   0.02672  0.83462 -4.340 1.42e-05 ***
tt(Grade_num)      0.38871   1.47508  0.13552  2.868  0.00413 ** 
Gender_binaryMale  0.03021   1.03067  0.10237  0.295  0.76789    
Age_scaled         0.12256   1.13039  0.05180  2.366  0.01799 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

                  exp(coef) exp(-coef) lower .95 upper .95
Grade_num           0.02672    37.4293  0.005204    0.1372
tt(Grade_num)       1.47508     0.6779  1.130990    1.9239
Gender_binaryMale   1.03067     0.9702  0.843311    1.2597
Age_scaled          1.13039     0.8847  1.021251    1.2512

Concordance= 0.674  (se = 0.015 )
Likelihood ratio test= 168.6  on 4 df,   p=<2e-16
Wald test            = 161.3  on 4 df,   p=<2e-16
Score (logrank) test = 193.3  on 4 df,   p=<2e-16

