Hello,

I am approaching for the first time a competing risk survival analysis. I am using Stata/SE 12.
I have two cohorts of patients with cancer and I am looking at the estimate of their risk of thrombosis; however, there is death as competing risk.

Here is an example of my dataset:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input int patient_id float cohort_num byte(age genderm thrombosis) float follow_up byte(thrombosis_competing_analysis death)
  3 1 58 0 0 .33 2 1
  4 1 73 1 1 .38 1 0
  5 1 60 1 0 .19 2 1
  6 1 38 0 0   1 0 0
  7 1 58 1 0   1 0 0
  8 1 44 0 0   1 0 0
  9 1 64 0 0 .49 2 1
 10 1 47 0 0 .48 2 1
 11 1 70 1 0 .01 2 1
 12 1 37 1 0 .05 2 1
 13 1 26 0 0  .1 0 0
 14 1 54 1 0  .2 0 0
 15 1 37 0 0  .6 0 0
 16 1 65 1 1  .5 1 0
 17 1 76 0 0   1 0 0
 18 1 34 1 0   1 0 0
270 2 74 0 0 .78 2 1
271 2 73 1 0   1 0 0
272 2 70 0 0   1 0 0
273 2 72 0 0   1 0 0
274 2 61 1 0   1 0 0
275 2 80 1 0 .08 2 1
276 2 74 0 0   1 0 0
277 2 73 0 0   1 0 0
278 2 73 0 0   1 0 0
279 2 81 1 1   1 1 0
280 2 35 0 0  .2 0 0
281 2 46 1 0  .3 0 0
282 2 56 0 0  .8 0 0
283 2 75 1 1  .7 1 0
284 2 76 0 0   1 0 0
285 2 24 1 0   1 0 0
end


I have first tried a standard Kaplan-Meier survival analysis, as follows:

Code:
stset follow_up, id(patient_id) failure(thrombosis == 1)
by cohort_num, sort: stptime
sts graph, failure by(cohort_num)
sts test cohort_num, logrank
stcox cohort_num age genderm

Then I tried a competing risk survival analysis, as follows:

Code:
stset follow_up, id(patient_id) failure(thrombosis_competing_analysis == 1)
stcrreg cohort_num, compete(thrombosis_competing_analysis == 2)
stcurve, cif at1(cohort_num = 1) at2(cohort_num = 2)
stcrreg cohort_num  age genderm, compete(thrombosis_competing_analysis == 2)

My questions are:

1) in the competing risk analysis is there a way to provide the failure rate (or the cumulative incidence) for each of my cohorts? Something similar to the stptime command of the standard survival analysis?


2) I have read that to compare two cumulative incidence curve I should use the Gray's test (which is the corresponding of the log-rank test). Is there a way to perform the Gray's test in Stata?
Lacking of the Gray's test, the only possible alternative that came to my mind was to provide the p value of the corresponding SHR from stcrreg (e.g. if cohort_num is not statistically significant, can I say that there is no difference between the two curves?)


Many thanks in advance.

Nicoletta