Statistical Methods for Adherence Issues in HIV Prevention Research

 描述（由申请人提供）：生物医学预防干预的最新进展，例如，治疗即预防（TasP）和暴露前预防（PrEP）已经改变了艾滋病毒预防的概念和实施方式，而有效的艾滋病毒疫苗尚未开发。对于一个生物艾滋病毒预防方案，最有可能在口腔医学，是有效的，用户的遵守规定的方案是至关重要的。不完美的依从性降低了方案的有效性，并且也使得难以在临床试验环境中评估方案的功效。在临床实践中，研究人员使用各种工具来测量依从性。由于这些工具都有其局限性，我们认识到，严重缺乏系统的统计方法， 灵活和可靠的不同的数据收集程序。为了满足需求，在本申请中，我们的目标是1）开发可以捕获不同纵向依从性模式的一致的统计测量; 2）开发使用来自不同测量仪器的数据来推断真实依从性模式的统计方法; 3）开发检测和分析依从性模式与免受HIV感染的保护水平之间的关联的统计方法; 4）开发一个统计/数学建模框架，以预测依从性改善对人群总体艾滋病毒发病率降低的人群影响。该项目完成后，将开发一套创新、有用和易于实施的统计工具和软件，用于评估、分析和提高艾滋病毒预防研究的依从性。

 DESCRIPTION (provided by applicant): Recent advances in biomedical prevention intervention, e.g., Treatment as Prevention (TasP) and Pre‐ Exposure Prophylaxis (PrEP), have changed how HIV prevention is conceptualized and implemented, while effective HIV vaccine is yet to be developed. For a biological HIV prevention regimen, mostly likely in oral medicine, to be effective, users' adherence to the prescribed regimen is critical. Imperfect adherence reduces the regimen's effectiveness, and also makes it difficult to assess the regimen's efficacy in clinical trial settings. There are various instruments used in clinical practce for researchers trying to measure the adherence. Since each of these instruments has its limitations, we have realized that there is a serious lack of systematic statistical methods, being flexible and reliable to the different data collection procedures. To address the need, in this application we aim to 1) develop consistent statistical measures that can capture different longitudinal adherence patterns; 2) develop statistical methods to infer the true adherence pattern using data from different measuring instruments; 3) develop statistical methods to detect and analyze the association between the adherence patterns and the level of protection from HIV acquisition; 4) develop a statistical/mathematical modeling framework to predict the population impact of adherence improvement on a population's overall HIV incidence reduction. Upon the completion of this project, an innovative, useful and easy‐to‐implement set of statistical tools and software will be developed for assessing, analyzing and improving adherence in HIV prevention research.