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Competing risks regression for stratified data. (English) Zbl 1217.62199

Summary: For competing risks data, the J. P. Fine and R. J. Gray [J. Am. Stat. Assoc. 94, No. 446, 496–509 (1999; Zbl 0999.62077)] proportional hazards model for subdistribution has gained popularity for its convenience in directly assessing the effect of covariates on the cumulative incidence function. However, in many important applications, proportional hazards may not be satisfied, including multicenter clinical trials, where the baseline subdistribution hazards may not be common due to varying patient populations.
We consider a stratified competing risks regression, to allow the baseline hazard to vary across levels of the stratification covariate. According to the relative size of the number of strata and strata sizes, two stratification regimes are considered. Using partial likelihood and weighting techniques, we obtain consistent estimators of the regression parameters. The corresponding asymptotic properties and resulting inferences are provided for the two regimes separately. Data from a breast cancer clinical trial and from a bone marrow transplantation registry illustrate the potential utility of the stratified Fine-Gray model.

MSC:

62P10 Applications of statistics to biology and medical sciences; meta analysis
62G08 Nonparametric regression and quantile regression
62N01 Censored data models
92C50 Medical applications (general)
62H30 Classification and discrimination; cluster analysis (statistical aspects)
65C60 Computational problems in statistics (MSC2010)
62N02 Estimation in survival analysis and censored data

Citations:

Zbl 0999.62077

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References:

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