I have a dataset with patients who had liver transplant. Some of them were in group 1 (if on drug A at baseline), others were in group 2 (if on drug B at baseline), depending on the immunosuppressive med they were taking. I am interested in seeing how the time of first switch from med A to med B impacts graft survival. The issue is that I am relatively new to survival analysis and have definitely no experience with time-dependent covariates.
Given this, I would like to know if anybody can give me a step-by-step on how I could model time of first switch as a time-dependent covariate in a Cox model with time to graft loss as the outcome? I have read a few theoretical, and some more practical tutorials for how to do this in R, so I know I need the data in long format or so-called counting process format with tstart and tstop and all that, but I am still having trouble getting situated and figuring out an action plan for how to analyze this, and in SAS too.
Below is a test dataset similar to the one I have, where GROUP=1, if on drug A; 2 if on drug B, and 3 if they switched from A to B;
CENSOR=1, if event (graft failure) happened, 0 otherwise;
FUTIME = total follow-up time (months) (=CENSDT – transplant date), where CENSDT (not shown here, is either date of event, or date of last follow-up/death);
EVTIME= time of event (months); EVTIME=FUTIME when CENSOR=1, else EVTIME= . ;
SWITCHDATE (not shown here) =date of first switch from drug A to drug B;
SWITCHTIME=time of first switch from group 1 to group 2 (=SWITCHDATE – transplant date); this will be 0 for those patients who start off on drug B at baseline, and it is FUTIME for those who start off on drug A and never switch.
data have;
input ID$ CENSOR$ FUTIME EVTIME SWITCHTIME GROUP$;
datalines;
001 0 1229 . 333 3
002 0 1659 . 343 3
003 0 733 . 509 3
004 0 6998 . 1630 3
005 1 1005 1005 558 3
006 1 4726 4726 147 3
007 0 3790 . 2856 3
008 1 672 672 504 3
009 0 5224 . 2648 3
010 0 4143 . 149 3
011 0 4973 . 500 3
012 1 3626 3626 3624 3
013 0 4296 . 3998 3
014 0 977 . 0 2
015 0 2898 . 331 3
016 0 1382 . 1187 3
017 1 1164 1164 1164 1
018 0 1232 . 336 3
019 1 1599 1599 143 3
020 0 1795 . 111 3
021 0 3171 . 3171 1
022 1 483 483 333 3
023 1 824 824 351 3
024 0 662 . 662 3
025 1 597 597 0 2
026 0 1269 . 0 2
027 0 4120 . 4120 1
028 1 621 621 0 2
029 0 3452 . 3452 1
030 0 1842 . 0 2
;
run;
proc print data=have; run;
