A note on including time-dependent covariate in regression model for competing risks data.
Recently, regression analysis of the cumulative incidence function has gained interest in competing risks data analysis, through the model proposed by Fine and Gray (JASA 1999; 94: 496-509). In this note, we point out that inclusion of time-dependent covariates in this model can lead to serious bias. We illustrate the problems arising in such a context, using bone marrow transplant data as a working example and numerical simulations. Practical advices are given, preventing the misuse of this model.
Latouche
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Département de Biostatistique et Informatique Médicale, Hôpital Saint-Louis, AP-HP, Inserm U717, F-75010 Paris, France. aurelien.latouche@paris7.jussieu.fr
Porcher
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Chevret
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D000465:Algorithms; D000704:Analysis of Variance; D015982:Bias; D016026:Bone Marrow Transplantation / Q000401:mortality / Q000706:statistics & numerical data; D002648:Child; D006086:Graft vs Host Disease / Q000401:mortality; D006801:Humans; D007938:Leukemia / Q000628:therapy; D008137:Longitudinal Studies; D015233:Models, Statistical; D009010:Monte Carlo Method; D011336:Probability; D016016:Proportional Hazards Models; D012008:Recurrence; D012044:Regression Analysis; D018570:Risk Assessment / Q000706:statistics & numerical data*; D016019:Survival Analysis; D015996:Survival Rate