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使用贝叶斯分层复合泊松脆弱模型估计HIV预防试验中的有效性。

Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model.

作者信息

Coley Rebecca Yates, Brown Elizabeth R

机构信息

Department of Biostatistics, University of Washington, Seattle, WA, U.S.A.

Fred Hutchinson Cancer Research Center, Seattle, WA, U.S.A.

出版信息

Stat Med. 2016 Jul 10;35(15):2609-34. doi: 10.1002/sim.6884. Epub 2016 Feb 11.

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.

摘要

近期关于暴露前预防性干预措施的HIV预防试验结果不一致,可能是由于研究参与者之间风险存在异质性。干预效果最常使用Cox模型进行估计,该模型比较不同人群的事件发生时间。当存在异质性时,这种人群水平的测量会低估高危个体的干预效果。我们提出一种基于似然的贝叶斯分层模型,该模型通过使用复合泊松分布的脆弱项来考虑风险异质性,从而估计候选干预措施的个体水平效果。该模型反映了HIV风险机制,并允许一些参与者未接触到HIV,因此在研究期间没有血清转化风险。我们通过模拟评估模型性能,并将该模型应用于一项HIV预防试验的数据。版权所有© 2016约翰威立父子有限公司。

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