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  • CIF after competing risk regression with imputed data


    I am using a competing risk regression (Fine and Gray) model to understand patient characteristics associated with major cardiac events (MCE) after organ transplantation. The outcome is MCE and I am using non-MCE death as a competing risk. A single variable included in my final (pack-years smoked) contains missing data and I would like to run the model using multiple imputation for this variable. Thus far, my code is:

    mi stset cohort_end1, id( study_id) fail( comp_risk ==1 ) origin( cohort_date) enter(cohort_date)
    mi estimate, hr: stcrreg i.diabetes i.race i.gender age pack_years i.htn year_transplant, compete(comp_risk==2)
    I would like to plot the CIF by diabetes status:

    stcurve, cif at1(diabetes=0)  at2(diabetes=1)  at3(diabetes =2)
    Easy to do in the non-imputed data, but in the imputed data, I receive an error: "last estimates not found r(301);

    Any advice on how to remedy this is appreciated!

    In addition to plotting the CIF, I would love to generate point estimates of CIF with 95% confidence intervals at specific follow up times (ie: 12 months, 60 months and 120 months after organ transplant).

    Finally, is there a way to perform the Gray test to determine if the cumulative incidence of MCE differs among the different exposures (ie: diabetes status)?

    Thank you for any help you can offer.


  • #2
    I will follow this post.


    • #3
      I have the same Problem. found a solution yet?


      • #4
        No, unfortunately no solutions yet. My statistician who excels in survival analysis is stumped as well.


        • #5
          Hello there, I'm trying to run a similar analysis and am receiving the exact same error when I attempt to get STATA to construct the CIF curves from imputed data. Has any found any solutions or any suggestions?