I am looking at the results of a three-arm clinical trial, where a secondary outcome is the occurrence of a specific adverse event. The trial was run for 96-weeks. I would like to analyse this secondary outcome using time-to-event with competing risks (ie, early d/c & death). The event was coded as 0=censored; 1=event; 2=competing risk.
I use the following competing risks code:
Code:
stset weeks, id(id) failure(event==1) stcrreg i.randgroup, compete(event==2) failure _d: event == 1 analysis time _t: weeks id: id Competing-risks regression No. of obs = 287 No. of subjects = 287 Failure event : event == 1 No. failed = 43 Competing event: event == 2 No. competing = 62 No. censored = 182 Wald chi2(2) = 2.79 Log pseudolikelihood = -234.85681 Prob > chi2 = 0.2483 (Std. Err. adjusted for 287 clusters in id) ------------------------------------------------------------------------------ | Robust _t | SHR Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- randgroup | TDF/FTC/DTG | 1.102586 .3762002 0.29 0.775 .5649167 2.151993 TDF/FTC+EFV | .5667937 .2387167 -1.35 0.178 .2482699 1.293975 ------------------------------------------------------------------------------
As all individuals were followed-up for the same time, would it also be reasonable to present the results simply as "proportion experiencing the event by Week 96 [including censoring for competing risks]"
Code:
tab event randgroup, col +-------------------+ | Key | |-------------------| | frequency | | column percentage | +-------------------+ | randomisation group event | G1 G2 G3 | Total -----------+---------------------------------+---------- censored | 59 67 56 | 182 | 60.20 67.68 59.57 | 62.54 -----------+---------------------------------+---------- event | 16 18 9 | 43 | 16.33 18.18 9.57 | 14.78 -----------+---------------------------------+---------- competing | 23 14 29 | 66 | 23.47 14.14 30.85 | 22.68 -----------+---------------------------------+---------- Total | 98 99 94 | 291 | 100.00 100.00 100.00 | 100.00
So 16%, 18%, and 10%, for each group. Is there a post estimation command for stcrreg that I could use to generate % experiencing event by Wk96, adjusted for baseline characteristics?
Thanks,
Megan
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