Statistical Designs and Methods for Partially Controlled HIV/AIDS Studies

描述（由申请人提供）：艾滋病毒/艾滋病生物医学研究的一个重要目标是估计因素对艾滋病毒/艾滋病结局的影响。虽然已经有丰富的分析方法，如果这些因素被认为是适当的控制，有重要的设计和方法，有效地估计的影响，并最大限度地从不能直接控制的因素的好处是需要的。在本提案中，我们将开发设计和方法，以更好地估计和最大限度地提高不受控制的因素对人口的好处。拟议的方法将建立在我们已经进行了初步工作，使用的框架“主要分层”。这项工作的成功增加了这项建议的潜在影响。所提出的方法是为两个广泛的目标而开发的，并受到美国针具交换计划、东非艾滋病毒治疗管理和艾滋病毒疫苗有效性试验的激励。(Aim 1）开发设计，以最大限度地提高研究参与者的治疗效益，控制提供治疗的地点，但不直接控制谁接受治疗或谁提供结果。这种情况出现在美国提供针头交换计划的网站，以及发展中国家运营艾滋病毒治疗计划的网站。我们以前开发的方法来估计治疗效果的人口给定的设计。我们现在提出了新的方法来寻找设计，最大限度地提高人口的治疗效果，以及定期监测该效果所需的信息。我们的方法的动机是，并将被应用到指定的位置，最大限度地提高巴尔的摩针交换计划的好处，并在东非的艾滋病毒防治计划。(Aim 2）开发统计方法，以更好地评估治疗对结果的影响，这些结果仅在随机化后选择的未受控制的参与者子集中定义。这种情况出现在艾滋病毒疫苗试验中，当评估疫苗对结果的影响时（例如，病毒载量），仅在随机化后感染HIV的亚组上定义。感染艾滋病毒的疫苗可能与那些没有疫苗对感染风险的假定作用的疫苗不同。我们提出了更有效的方法来估计艾滋病毒疫苗对纵向感染后结果的影响。我们的方法是有动机的，并将被应用于第一个细胞介导的免疫HIV疫苗试验（步骤试验），并对母婴传播艾滋病毒的马什试验。

DESCRIPTION (provided by applicant): An important objective of biomedical studies of HIV/AIDS is to estimate the effect of factors on HIV/AIDS outcomes. Although there has been a rich list of methods of analysis that are appropriate if such factors are assumed controlled, there is important need for designs and methods to validly estimate the effect of, and to maximize the benefit from factors that cannot be directly controlled. In this proposal, we will develop designs and methods to better estimate and to maximize the benefit that uncontrolled factors have on a population. The proposed methods will build on preliminary work we have conducted using the framework of "principal stratification". The success of that work increases the potential impact of this proposal. The proposed methods are developed for two broad aims, and are motivated by needle exchange programs in the US, HIV treatment administration in East Africa, and HIV vaccine efficacy trials. (Aim 1)Develop designs to maximize the treatment benefit for participants in studies that control the location of sites that offer treatments, but do not directly control who gets treatment or who provides outcomes. Such a situation arises with sites offering needle exchange programs in the US, and with sites operating HIV treatment programs in the developing world. We have previously developed methods to estimate the treatment effect on a population given a design. We now propose new methods to find designs that maximize both, the treatment effect on a population, as well as the information needed to periodically monitor that effect. Our methods are motivated by and will be applied to designate placements that maximize the benefit of the Baltimore Needle Exchange Program, and of the PEPFAR HIV programs in East Africa. (Aim 2)Develop statistical methods to better evaluate the effect of a treatment on outcomes which are defined only in an uncontrolled subset of participants selected after randomization. Such a situation arises in HIV vaccine trials when assessing the effect of a vaccine on outcomes (e.g., viral load) that are defined only on the subsets who are infected with HIV post-randomization. Vaccines that are infected with HIV can be different from those who are infected without the putative effect of vaccine on infection risk. We propose more valid methods to estimate the effects of HIV vaccines on longitudinal post-infection outcomes. Our methods are motivated and will be applied to the first cell-mediated immunity HIV vaccine trial (Step trial), and to the Mashi trial on mother-to-child HIV transmission.