CMPRSK library and time dependent covariate

[phguardiol@aol.com]

Dear S users,

I d like to assess the effect of "treatment" covariate on a disease relapse risk with the package cmprsk.
However, the effect of this covariate on survival is time-dependent (assessed with cox.zph): no significant effect during the first year of follow-up, then after 1 year a favorable effect is observed on survival (step function might be the correct way to say that ?).
For overall survival analysis I have used a time dependent Cox model which has confirmed this positive effect after 1 year.
Now I m moving to disease relapse incidence and a similar time dependency seems to be present.

what I d like to have is that: for patients without "treatment" the code for "treatment" covariate is always 0, and for patients who received "treatment" covariate I d like to have it = 0 during time interval 0 to 1 year, and equal to 1 after 1 year. Correct me if I m wrong in trying to do so.


First, I have run the following script (Splus2000Pro under XPpro) according to previous advices:

library(cmprsk)
attach(LAMrelapse)
fit1<- crr(rel.t, rel.s, treatment, treatment, function(uft) cbind(ifelse(uft<=1,1,0),ifelse(uft>1,1,0)), failcode=1, cencode=0, na.action="" gtol-06, maxiter)
fit1

where:
rel.t = time to event (in years)
rel.s = status , =1 if disease relapse, =2 if death from non disease related cause (toxicity of previous chemotherapy), =0 if alive & not in relapse
treatment = binary covariate (value: 0 or 1) representing the treatment to test (different from chemotherapy above, with no known toxicity)
I have not yet added other covariates in the model.


this script gave me the following result:
> fit1 <- crr(relcmp.t, relcmp.s, treatment, treatment, function(uft) cbind(ifelse(uft <= 1, 1, 0), ifelse(uft > 1, 1, 0)), failcode = 1, cencode = 0,
    na.action = "" gtol = 1e-006, maxiter = 10)
> fit1
convergence:  TRUE
coefficients:
[1] -0.6808  0.7508
standard errors:
[1] 0.2881 0.3644
two-sided p-values:
[1] 0.018 0.039

...That I dont understand at all since it looks like if "treatment" covariate had also a significant effect of the first period of time !?
This is absolutely not the case.
So I m surely wrong with a part of this script... cov2 and tf are pretty obscure for me in the help file of the package. I would really appreciate advices regarding these 2 "terms".

I was thinking that I might changed : cbind(ifelse(uft <= 1, 1, 0), ifelse(uft > 1, 1, 0)                   into:        cbind(ifelse(uft <= 1, 0, 1), ifelse(uft > 1, 1, 0)

But since I only have one covariate (treatment) to test, shouldnt I only write the following:
fit1<- crr(rel.t, rel.s, treatment, treatment, function(uft) ifelse(uft<=1,0,1)), failcode=1, cencode=0, na.action="" gtol-06, maxiter)

which gives me :
> fit1
convergence:  TRUE
coefficients:
[1]  0.06995 -0.75080
standard errors:
[1] 0.2236 0.3644
two-sided p-values:
[1] 0.750 0.039

which, if I understand things correctly (I m not sure at all !) confirms that before 1 year, the effect of "treatment" covariate is not significant, but is significant after 1 year of follow up. But there I m again not sure of the result I obtain...

any help would be greatly appreciated with cov2 and tf

thanks for  if you have some time for this,

Philippe Guardiola