title: Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model.
abstract: Inconsistent results in recent HIV prevention trials of pre-exposure prophylactic interventions may be due to heterogeneity in risk among study participants. Intervention effectiveness is most commonly estimated with the Cox model, which compares event times between populations. When heterogeneity is present, this population-level measure underestimates intervention effectiveness for individuals who are at risk. We propose a likelihood-based Bayesian hierarchical model that estimates the individual-level effectiveness of candidate interventions by accounting for heterogeneity in risk with a compound Poisson-distributed frailty term. This model reflects the mechanisms of HIV risk and allows that some participants are not exposed to HIV and, therefore, have no risk of seroconversion during the study. We assess model performance via simulation and apply the model to data from an HIV prevention trial. Copyright © 2016 John Wiley & Sons, Ltd.
authors: Department of Biostatistics, University of Washington, Seattle, WA, U.S.A.
authors: Rebecca Yates
authors: RY
authors: Coley
authors: Department of Biostatistics, University of Washington, Seattle, WA, U.S.A.|Fred Hutchinson Cancer Research Center, Seattle, WA, U.S.A.
authors: Elizabeth R
authors: ER
authors: Brown
mesh_terms: D001499:Bayes Theorem; D000073496:Frailty; D015658:HIV Infections / Q000517:prevention & control*; D006801:Humans; D016013:Likelihood Functions; D012107:Research Design
keywords: Bayesian analysis; data augmentation; heterogeneity; latent variable; survival analyisis