Estimation of the Prevalence of Post Treatment Controllers of HIV-1 Infection Using Pooled Data from Independent Study Sites

 描述（由申请方提供）：欧洲VISCONTI组最近的一份报告估计，在感染期间接受非常早期治疗的患者中，14-15%能够停止治疗并在不接受任何治疗的情况下维持病毒抑制数年。这个15%的估计比预期的要高得多，需要确认。从那时起，没有其他小组能够证实或反驳这一发现，最有可能的原因是需要大量的个体来找到足够的符合PTC评估条件的患者，因为大多数接受抑制治疗的患者很少停止治疗。因此，为了获得足够大的样本量来明确估计PTC的患病率和与PTC相关的相关因素，有必要将来自进行急性和极早期HIV感染研究的相似但独立来源的联合收割机数据结合起来。该项目的主要目标是以标准化的方式将来自三个来源的联合收割机数据结合起来：历史急性感染/早期疾病研究计划（AIEDRP）数据库、华盛顿大学原发感染队列数据库和加州圣地亚哥大学原发感染队列数据库。这个合并的数据库将被称为PTC数据库，并将用于从三个来源中获得PTC组合百分比的初步估计，改进UW和UCSD小组独立获得的估计。此外，将根据结合这三个数据集时确定的QC程序和格式制定正式方案。本方案将提供有关如何对数据进行QC和格式化以纳入PTC数据库的具体说明。一旦我们确定了将数据集与估计PTC患病率所需信息相结合的可行性，并制定了一项方案，说明如何准备数据集以纳入PTC数据库，则计划进行R 01申请，该申请将招募其他研究中心向PTC数据库提供数据。将向每个研究中心提供该方案，以便他们能够高效且一致地准备各自的数据集，以纳入PTC数据库。然后，该数据库将用于估计PTC的患病率，并评估PTC的相关因素和其他机制。关于PTC的预测因子和其他特征的信息可以允许具有这些预测因子和特征的某些患者考虑治疗中断。此外，与PTC相关的因素的鉴定可以指导寻找HIV功能性治愈的额外研究。

 DESCRIPTION (provided by applicant): A recent report from the European VISCONTI group estimated that 14-15% of patients treated very early during infection were able to discontinue therapy and maintain viral suppression for several years without any therapy. This estimate of 15% is much higher than expected and requires confirmation. Since then, no other group has been able to confirm or refute this finding, most likely because very large numbers of individuals are required to find enough patients eligible for evaluation for PTC, since most patients on suppressive therapy rarely discontinue treatment. Therefore, in order to get a large enough sample size to definitively estimate the prevalence of PTC and associated factors associated with PTC it is necessary to combine data from similar but independent sources conducting research on acute and very early HIV infection. The primary goal of this project is to combine data in a standardized manner from three sources: The historical Acute Infection/Early Disease Research Program (AIEDRP) database, the University of Washington Primary Infection Cohort database and the University of California San Diego Primary Infection Cohort database. This combined database will be referred to as to the PTC Database and will be used to obtain a preliminary estimate of the percentage of PTCs in combination from the three sources, improving on the estimates that have been obtained by both the UW and UCSD groups independently. In addition, a formal protocol, based on procedures for QC and formatting identified while combining these three data sets, will be developed. This protocol will provide specific instructions on how to QC and format data for inclusion in the PTC Database. Once we establish feasibility for combing data sets with the information needed to estimate the prevalence of PTC and develop a protocol with instructions on how to prepare datasets for inclusion in the PTC Database, an R01 application is planned which will recruit additional sites to contribute data to the PTC Database. The protocol will be provided to each site so that they can prepare their individual data sets efficiently and consistently to be included in the PTC Database. This database would then be used to estimate the prevalence of PTCs and evaluate correlates and other mechanisms of PTC. Information on predictors and other features of PTCs may allow certain patients with those predictors and features to consider a treatment interruption. In addition, the identification of factors associated with PTCs could direct additionl research on finding a functional cure for HIV.