Statistical Designs and Methods for Partially Controlled HIV/AIDS Studies

描述(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评估各种因素对艾滋病毒/艾滋病结果的影响。虽然在假定这些因素被控制的情况下，已经有了许多适当的分析方法，但重要的是需要设计和方法来有效地估计不能直接控制的因素的影响，并最大限度地从这些因素中获益。在这项提案中，我们将制定设计和方法，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利用“主体分层”框架进行的初步工作的基础上。这项工作的成功增加了这项提议的潜在影响。提出的方法有两个广泛的目标，并受到美国的针头交换计划、东非的艾滋病毒治疗管理和艾滋病毒疫苗功效试验的推动。(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。这样的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。我们以前已经开发出方法来估计在给定设计的人群中的治疗效果。我们现在提出了新的方法来寻找设计，使对人群的治疗效果以及定期监测该效果所需的信息最大化。我们的方法是受巴尔的摩针头交换计划和东非PEPFAR艾滋病毒计划的激励，并将应用于指定最大限度地受益于该计划的安置。(目的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(例如，病毒载量)的影响时，这些结果只在随机后感染艾滋病毒的子集上定义。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影响的感染疫苗不同。我们提出了更有效的方法来评估HIV疫苗对感染后纵向结局的影响。我们的方法是有动力的，并将应用于第一个细胞免疫艾滋病毒疫苗试验(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.