R help - Aug 2008 - cmprsk and a time dependent covariate in the model

Dear R 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 (R2.7.1 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=na.omit, 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 = na.omit, 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=na.omit, 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



 




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