Semiparametric regression for the weighted composite endpoint of recurrent and terminal events.

TitleSemiparametric regression for the weighted composite endpoint of recurrent and terminal events.
Publication TypeJournal Article
Year of Publication2016
AuthorsMao, Lu, and D Y. Lin
JournalBiostatistics
Volume17
Issue2
Pagination390-403
Date Published2016 Apr
ISSN1468-4357
KeywordsComputer Simulation, Critical Illness, Data Interpretation, Statistical, Heart Failure, Humans, Recurrence, Survival Analysis
Abstract

Recurrent event data are commonly encountered in clinical and epidemiological studies. A major complication arises when recurrent events are terminated by death. To assess the overall effects of covariates on the two types of events, we define a weighted composite endpoint as the cumulative number of recurrent and terminal events properly weighted by the relative severity of each event. We propose a semiparametric proportional rates model which specifies that the (possibly time-varying) covariates have multiplicative effects on the rate function of the weighted composite endpoint while leaving the form of the rate function and the dependence among recurrent and terminal events completely unspecified. We construct appropriate estimators for the regression parameters and the cumulative frequency function. We show that the estimators are consistent and asymptotically normal with variances that can be consistently estimated. We also develop graphical and numerical procedures for checking the adequacy of the model. We then demonstrate the usefulness of the proposed methods in simulation studies. Finally, we provide an application to a major cardiovascular clinical trial.

DOI10.1093/biostatistics/kxv050
Alternate JournalBiostatistics
Original PublicationSemiparametric regression for the weighted composite endpoint of recurrent and terminal events.
PubMed ID26668069
PubMed Central IDPMC4804115
Grant ListR01 CA082659 / CA / NCI NIH HHS / United States
R01GM047845 / GM / NIGMS NIH HHS / United States
R01AI029168 / AI / NIAID NIH HHS / United States
R01 GM047845 / GM / NIGMS NIH HHS / United States
P01CA142538 / CA / NCI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
Project: