在高度有效的非疫苗预防模式背景下设计艾滋病疫苗疗效试验。

IF 0.8 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Statistics in Biosciences Pub Date : 2020-12-01 Epub Date: 2020-10-22 DOI:10.1007/s12561-020-09292-1
Holly Janes, Yifan Zhu, Elizabeth R Brown
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引用次数: 0

摘要

不断变化的艾滋病预防形势对未来候选艾滋病疫苗试验的统计设计提出了挑战。研究设计必须解决由于在提供给试验参与者的标准预防包中增加了新的预防方式而导致的艾滋病发病率预期下降的问题,还必须考虑到参与者在使用这些方式时的个人选择。我们探讨了应对这些挑战的四种可能的试验设计,重点是如何适应最新增加的一揽子预防方案--基于抗逆转录病毒的暴露前口服预防疗法(PrEP)。这些设计的不同之处在于如何处理在筛查时接受口服 PrEP 的个体。全样本设计(All-Comers Design)对所有符合条件的个体进行招募和随机化;拒绝样本设计(Decliners Design)仅对在筛查时拒绝接受 PrEP 的个体进行招募和随机化;单阶段和多阶段磨合设计(Single and Multi-Stage Run-In Design)对所有个体进行招募,但仅随机化那些在一个或多个磨合期后拒绝接受 PrEP 或对 PrEP 的依从性不足的个体。我们使用一个模拟模型,结合美洲男男性行为者 (MSM) 中的 HIV 风险、PrEP 摄入量和依从性数据,比较了这些设计所需的样本量、研究持续时间和资源需求。我们主张在未来的某些情况下考虑采用 "磨合设计"(Run-In Designs),并指出其相对于其他设计的优势和权衡。这些设计理念不仅适用于艾滋病疫苗,还适用于正在开发的其他预防方式,目的是进一步降低艾滋病发病率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Designing HIV Vaccine Efficacy Trials in the Context of Highly Effective Non-vaccine Prevention Modalities.

Designing HIV Vaccine Efficacy Trials in the Context of Highly Effective Non-vaccine Prevention Modalities.

Designing HIV Vaccine Efficacy Trials in the Context of Highly Effective Non-vaccine Prevention Modalities.

Designing HIV Vaccine Efficacy Trials in the Context of Highly Effective Non-vaccine Prevention Modalities.

The evolving HIV prevention landscape poses challenges to the statistical design of future trials of candidate HIV vaccines. Study designs must address the anticipated reduction in HIV incidence due to adding new prevention modalities to the standard prevention package provided to trial participants, and must also accommodate individual choices of participants with regard to the use of these modalities. We explore four potential trial designs that address these challenges, with a focus on accommodating the newest addition to the prevention package-antiretroviral-based oral pre-exposure prophylaxis (PrEP). The designs differ with respect to how individuals who take up oral PrEP at screening are handled. An All-Comers Design enrolls and randomizes all eligible individuals, a Decliners Design enrolls and randomizes only those who decline PrEP at screening, and Single and Multi-Stage Run-In Designs enroll all but randomize only those who decline PrEP or show inadequate adherence to PrEP after one or multiple run-in periods. We compare these designs with respect to required sample sizes, study duration, and resource requirements, using a simulation model that incorporates data on HIV risk and PrEP uptake and adherence among men who have sex with men (MSM) in the Americas. We advocate considering Run-In Designs for some future contexts, and identify their advantages and tradeoffs relative to the other designs. The design concepts apply beyond HIV vaccines to other prevention modalities being developed with the aim to achieve further reductions in HIV incidence.

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来源期刊
Statistics in Biosciences
Statistics in Biosciences MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
2.00
自引率
0.00%
发文量
28
期刊介绍: Statistics in Biosciences (SIBS) is published three times a year in print and electronic form. It aims at development and application of statistical methods and their interface with other quantitative methods, such as computational and mathematical methods, in biological and life science, health science, and biopharmaceutical and biotechnological science. SIBS publishes scientific papers and review articles in four sections, with the first two sections as the primary sections. Original Articles publish novel statistical and quantitative methods in biosciences. The Bioscience Case Studies and Practice Articles publish papers that advance statistical practice in biosciences, such as case studies, innovative applications of existing methods that further understanding of subject-matter science, evaluation of existing methods and data sources. Review Articles publish papers that review an area of statistical and quantitative methodology, software, and data sources in biosciences. Commentaries provide perspectives of research topics or policy issues that are of current quantitative interest in biosciences, reactions to an article published in the journal, and scholarly essays. Substantive science is essential in motivating and demonstrating the methodological development and use for an article to be acceptable. Articles published in SIBS share the goal of promoting evidence-based real world practice and policy making through effective and timely interaction and communication of statisticians and quantitative researchers with subject-matter scientists in biosciences.
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