PROPORTIONAL HAZARDS MODELS WITH CONTINUOUS MARKS

• 成果类型: Article
• 署名作者: Sun, Yanqing; Gilbert, Peter B.; McKeague, Ian W.
• 署名单位: University of North Carolina; University of North Carolina Charlotte; University of Washington; University of Washington Seattle; Fred Hutchinson Cancer Center; Columbia University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/07-AOS554
• 发表日期: 2009
• 页码: 394-426
• 关键词: competing risks; clinical-trials; vaccine; time; coefficients

摘要

For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al. Biometrics 34 (1978) 541-554]. This article studies an extension of this approach to allow a continuum of competing risks, in which the cause of failure is replaced by a continuous mark only observed at the failure time. We develop inference for the proportional hazards model in which the regression parameters depend nonparametrically on the mark and the baseline hazard depends nonparametrically on both time and mark. This work is motivated by the need to assess HIV vaccine efficacy, while taking into account the genetic divergence of infecting HIV viruses in trial participants from the HIV strain that is contained in the vaccine, and adjusting for covariate effects. Mark-specific vaccine efficacy is expressed in terms of one of the regression functions in the mark-specific proportional hazards model. The new approach is evaluated in simulations and applied to the first HIV vaccine efficacy trial.