title: A note on including time-dependent covariate in regression model for competing risks data.
abstract: 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.
authors.affiliation: Département de Biostatistique et Informatique Médicale, Hôpital Saint-Louis, AP-HP, Inserm U717, F-75010 Paris, France. aurelien.latouche@paris7.jussieu.fr
authors.forename: A
authors.initials: A
authors.lastname: Latouche
authors.forename: R
authors.initials: R
authors.lastname: Porcher
authors.forename: S
authors.initials: S
authors.lastname: Chevret
mesh_terms: 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