A Semiparametric Additive-multiplicative Rates Model for the Weighted Composite Endpoint of Recurrent and Terminal Events

Abstract

Recurrent event data are commonly encountered in many scientific fields, including biomedical studies, clinical trials and epidemiological surveys, and many statistical methods have been proposed for their analysis. In this paper, we consider to use a weighted composite endpoint of recurrent and terminal events, which is weighted by the severity of each event, to assess the overall effects of covariates on the two types of events. A flexible additive-multiplicative model incorporating both multiplicative and additive effects on the rate function is proposed to analyze such weighted composite event process, and more importantly, the dependence structure among the recurrent and terminal events is left unspecified. For the estimation, we construct the unbiased estimating equations by virtue of the inverse probability weighting technique, and the resulting estimators are shown to be consistent and asymptotically normal under some mild regularity conditions. We evaluate the finite-sample performance of the proposed method via simulation studies and apply the proposed method to a set of real data arising from a bladder cancer study.