Pregnancy and response to antiretroviral therapy in South Africa

说明(申请人提供)：这项提案的总体目标是支持首席研究员Daniel Westreich博士成为撒哈拉以南非洲艾滋病毒妇女怀孕研究的领先健康科学家，特别关注怀孕对南非高效抗逆转录病毒疗法(HAART)反应的影响。南非孕妇的艾滋病毒感染率大大高于其他成年人。虽然在预防母婴传播艾滋病毒的问题上，在怀孕期间和怀孕后对抗逆转录病毒治疗的反应，人们对怀孕本身对治疗反应的影响知之甚少。了解怀孕对母体对HAART反应的影响，对于向非洲和其他地方的艾滋病毒妇女提供良好的临床护理至关重要。为了解决这些问题，这项工作建议检查怀孕(包括在治疗开始时怀孕，以及在治疗开始后怀孕)对HAART的病毒学反应、对HAART的依从性、护理中的滞留、对HAART的免疫学反应以及对HAART的临床(艾滋病/死亡)反应的影响。由于不可能(而且非常不道德)对怀孕的暴露情况进行随机化，这项研究将依赖南非约翰内斯堡的Themba Lethu诊所收集的高质量临床数据，该诊所是一家城市抗逆转录病毒治疗诊所，与威特沃特斯兰德大学的临床艾滋病毒研究单位有关联。拟议工作的首席调查员Daniel Westreich博士在与临床研究人员和临床医生合作产生高质量研究方面有着良好的记录。对这些数据的分析将需要使用结构模型，这是一种先进的流行病学方法。因此，在该奖项的指导阶段，Westreich博士将与结构模型方面的国际公认权威、导师Stephen R.Cole博士合作，掌握这些技能，并评估怀孕对HAART母亲病毒学反应的影响。这次培训将在北卡罗来纳大学教堂山分校的流行病学系进行，这是一个国际知名的流行病学和公共卫生研究的卓越中心。在这一培训和经验的基础上，在奖项的独立阶段，Westreich博士将领导调查，以评估怀孕对保留护理和遵守HAART的影响，以及对HAART的免疫学和临床反应的影响。这项工作将回答一系列关于怀孕对南非HAART反应的影响的关键实质性问题。通过这样做，这项工作将极大地增加关于这一重要主题的科学和公共卫生证据的基础，很可能是以一种可推广到撒哈拉以南非洲大部分地区的方式。此外，这项工作和培训将帮助韦斯特里奇博士发展成为一名健康科学家，使他拥有在复杂纵向数据中应用结构模型和其他流行病学方法进行定量因果推断的专业知识。

DESCRIPTION (provided by applicant): The overall goal of this proposal is to support the principal investigator, Dr. Daniel Westreich, in becoming a leading health scientist in the study of pregnancy among HIV+ women in sub-Saharan Africa, with a particular focus on the effect of pregnancy on response to highly active antiretroviral therapy (HAART) in South Africa. Prevalence of HIV among pregnant women in South Africa is substantially higher than that among other adults. While responses to antiretroviral therapy during and after pregnancy with respect to issues of prevention of mother to child transmission of HIV, little is known about the effect of pregnancy itself on responses to therapy. Understanding the effect of pregnancy on maternal responses to HAART is essential to providing good clinical care to HIV+ women in Africa and elsewhere. To address these questions, this work proposes to examine the effect of pregnancy (both pregnancy present at time of initiation of therapy, and pregnancy which occurs after the initiation of therapy) on virologic responses to HAART, adherence to HAART, retention in care, immunologic responses to HAART, and clinical (AIDS/death) responses to HAART. Because it is impossible (and highly unethical) to randomize the exposure of pregnancy, this study will rely on high quality clinical data collected in the Themba Lethu Clinic in Johannesburg, South Africa, an urban antiretroviral therapy clinic associated with the Clinical HIV Research Unit at the University of the Witwatersrand. The Principal Investigator of the proposed work, Dr. Daniel Westreich, has a strong track record in producing high quality research in collaboration with investigators and clinicians at the Clinic. The analysis of these data will require the use of structural models, an advanced body of epidemiologic methods. Thus, during the mentored phase of this award, Dr. Westreich will work with Mentor Dr. Stephen R. Cole, an internationally recognized authority on structural models, to acquire these skills and to evaluate the effect of pregnancy on maternal virologic responses to HAART. This training will take place in the Department of Epidemiology at The University of North Carolina at Chapel Hill, an internationally renowned center of excellence in epidemiologic and public health research. Building on this training and experience, during the independent phase of the award Dr. Westreich will lead investigations to evaluate the impact of pregnancy on retention in care and adherence to HAART, and on immunologic and clinical responses to HAART. This work will answer a suite of key substantive questions around the impact of pregnancy on response to HAART in South Africa. In doing so, this work will dramatically increase the base of scientific and public health evidence on this important subject, most likely in a way which is generalizable to much of sub-Saharan Africa. In addition, this work and training will help Dr. Westreich develop as a health scientist, giving him expertise in the application of structural models and other epidemiologic methods for quantitative causal inference in complex longitudinal data.