Semiparametric Proportional Rate Regression for the Composite Endpoint of Recurrent and Terminal Events

• Activity Number: 117
• Type: Topic Contributed
• Date/Time: Monday, August 5, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Danyu Lin*+ and Lu Mao
• Companies: Univ of North Carolina and The University of North Carolina
• Keywords: Competing risks ; Counting process ; Dependent censoring ; Intensity function ; Inverse probability weighting ; Mean function

Abstract

Analysis of recurrent event data has received tremendous attention in recent years. A major complication arises when recurrent events are terminated by death. To assess the overall covariate effects, we consider the composite endpoint of recurrent and terminal events and propose a proportional rate model which specifies that (possibly time-dependent) covariates have multiplicative affects on the marginal rate function of the composite event process. We derive appropriate estimators for the regression parameters and the baseline mean function by modifying the familiar inverse probability weighting technique. We show that the estimators are consistent and asymptotically normal with variances that can be consistently estimated. Simulation studies demonstrate that the proposed methods perform well in realistic situations. Applications to real clinical trials are provided.