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/艾滋病结果的影响。虽然在假设这些因素受到控制的情况下，已经有了大量适合的分析方法，但仍然需要设计和方法来有效地估计这些因素的影响，并最大限度地从不能直接控制的因素中获益。在本提案中，我们将开发设计和方法，以更好地估计和最大化不受控制的因素对人口的好处。拟议的方法将建立在我们使用“主要分层”框架进行的初步工作的基础上。这项工作的成功增加了本提案的潜在影响。提出的方法是为了两个广泛的目标而开发的，其动机是美国的针头交换项目、东非的艾滋病毒治疗管理以及艾滋病毒疫苗功效试验。（目标1）制定设计，以最大限度地提高研究参与者的治疗效益，这些研究控制了提供治疗的地点的位置，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项目的机构，以及发展中国家开展艾滋病毒治疗项目的机构。我们以前已经开发了一些方法来估计给定设计的人群的治疗效果。我们现在提出了新的方法来寻找设计，最大限度地提高对人群的治疗效果，以及定期监测效果所需的信息。我们的方法是由巴尔的摩针头交换计划和总统防治艾滋病紧急救援计划在东非的艾滋病项目的利益最大化的指定项目所推动的，并将被应用于这些项目。（目标2）发展统计方法，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控制的参与者子集中定义。在艾滋病毒疫苗试验中，当评估疫苗对结果（例如病毒载量）的影响时，就会出现这种情况，这些结果仅针对随机化后感染艾滋病毒的亚群进行定义。感染艾滋病毒的疫苗可能不同于那些没有疫苗对感染风险的假定影响的感染者。我们提出了更有效的方法来估计HIV疫苗对纵向感染后结局的影响。我们的方法是有动力的，并将应用于第一个细胞介导的免疫HIV疫苗试验（Step试验），以及关于母婴艾滋病毒传播的Mashi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.