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

使用独立研究中心的汇总数据估计 HIV-1 感染治疗后控制者的患病率

• 批准号: 9137395
• 负责人: SARAH E HOLTE
• 金额: $ 28.53万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-20 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9137395
• 关键词: Acute; Aftercare; CD4 Positive T Lymphocytes; California; Clinic; Comb animal structure; Data; Data Element; Data Set; Databases; Disease; European; Evaluation; Funding; Goals; HIV; HIV Infections; HIV-1; Individual; Infection; Instruction; Interruption; Investigation; Life; Meta-Analysis; Participant; Patients; Persons; Population; Prevalence; Primary Infection; Procedures; Protocols documentation; Publications; Quality Control; Recruitment Activity; Reporting; Research; Research Infrastructure; Research Personnel; Rest; Sample Size; Sampling; Site; Source; Staging; United States National Institutes of Health; Universities; Viral; Viral Load result; Washington; base; cohort; data format; design; improved; memory CD4 T lymphocyte; patient subsets; programs; public health relevance

 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.

 描述（由适用提供）：欧洲Visconti组的最新报告估计，在感染期间非常早期接受治疗的患者中有14-15％能够停止治疗并维持病毒抑制几年，而无需进行任何治疗。从那时起，没有其他小组能够确认或驳斥这一发现，这很可能是因为需要大量的人找到有资格评估PTC的足够的患者，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，以确定估计PTC的患病率以及与PTC相关的相关因素的患病率，必须结合来自类似但独立的急性研究和早期HIV感染研究的数据。该项目的主要目的是从三个来源以标准化的方式组合数据：历史急性感染/早期疾病研究计划（AIEDRP）数据库，华盛顿大学初级感染队列数据库和加利福尼亚大学圣地亚哥大学原发性感染队列数据库。该组合的数据库将被称为PTC数据库，并将用于从三个来源组合获得PTC百分比的初步估计，从而改善了UW和UCSD组已独立地获得的估计值。此外，将开发基于QC的程序和格式化的正式协议，并在结合这三个数据集时确定。该协议将提供有关如何和格式数据包含在PTC数据库中的特定说明。一旦我们确定了将数据集与估计PTC流行所需的信息相结合的可行性，并使用有关如何准备数据集以包含在PTC数据库中的说明的协议，则计划招募R01应用程序，该应用程序将募集其他站点以向PTC数据库贡献数据。该协议将被提供给每个站点，以便他们可以有效且一致地准备其单个数据集，以包含在PTC数据库中。然后，该数据库将用于估计PTC的患病率，并评估PTC的相关性和其他机制。有关PTC的预测因素和其他特征的信息可能会使某些具有这些预测因子的患者和特征考虑中断治疗。此外，鉴定与PTC相关的因素可以指导有关寻找HIV功能治疗的其他研究。