title: Efficient estimation of the distribution of time to composite endpoint when some endpoints are only partially observed.
abstract: Two common features of clinical trials, and other longitudinal studies, are (1) a primary interest in composite endpoints, and (2) the problem of subjects withdrawing prematurely from the study. In some settings, withdrawal may only affect observation of some components of the composite endpoint, for example when another component is death, information on which may be available from a national registry. In this paper, we use the theory of augmented inverse probability weighted estimating equations to show how such partial information on the composite endpoint for subjects who withdraw from the study can be incorporated in a principled way into the estimation of the distribution of time to composite endpoint, typically leading to increased efficiency without relying on additional assumptions above those that would be made by standard approaches. We describe our proposed approach theoretically, and demonstrate its properties in a simulation study.
authors.affiliation: Department of Medical Statistics and Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK, Rhian.Daniel@LSHTM.ac.uk.
authors.forename: Rhian M
authors.initials: RM
authors.lastname: Daniel
authors.forename: Anastasios A
authors.initials: AA
authors.lastname: Tsiatis
mesh_terms: D056808:Biostatistics; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D003198:Computer Simulation; D023381:Endpoint Determination / Q000706:statistics & numerical data*; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D015233:Models, Statistical; D016016:Proportional Hazards Models; D012042:Registries / Q000706:statistics & numerical data; D018709:Statistics, Nonparametric; D013997:Time Factors