Statistical Methods for Advancing HIV Prevention

促进艾滋病毒预防的统计方法

• 批准号: 10700642
• 负责人: Fei Gao
• 金额: $ 43.1万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10700642
• 关键词: AIDS prevention; Anti-Retroviral Agents; Biological Assay; Characteristics; Classification; Clinical Trials Design; Communicable Diseases; Complex; Data; Development; Evaluation; Future; HIV; Human immunodeficiency virus test; Incidence; Individual; Infection; Intervention; Intervention Trial; Left; Measures; Methodology; Methods; Participant; Performance; Phase; Placebo Control; Placebos; Population; Population Analysis; Positioning Attribute; Prevention; Property; Prophylactic treatment; Relaxation; Research; Resources; Sampling; Sexually Transmitted Diseases; Source; Statistical Methods; Testing; Time trend; active control; arm; cohort; design; direct application; effectiveness measure; effectiveness study; efficacy evaluation; efficacy trial; high risk; implementation barriers; improved; innovation; insight; next generation; novel; population based; prevent; prevention efficacy trial; preventive intervention; randomized trial; randomized, controlled study; screening; simulation; success; tool; trial design; volunteer

Project Summary/Abstract Antiretroviral-based HIV prophylaxis is highly effective at preventing acquisition of HIV, yet there are many implementation challenges. Population-based effectiveness studies seek to evaluate real-world impact of preventive interventions. There is, however, a major limitation in our current ability to measure effectiveness of preventive interventions at the population-level due to its requirement of resource-extensive longitudinal testing in a closed cohort. HIV recency assays (assays that provide information on the timing of HIV acquisition) offer resource- efficient estimates of incidence. However, the utility of such assays is currently limited due to lack of precision. In addition, designing efficacy trials to evaluate new HIV preventive interventions is increasingly challenging when effective prevention agents exist. To fill these gaps, we will advance statistical methodology to measure HIV incidence and develop a new trial design to assess efficacy of an HIV preventive intervention. Specifically, we will extend existing methods for estimating HIV incidence using recency assay data to accommodate covariate effects on assay properties, temporal trends in HIV incidence, and to estimate HIV incidence with increased precision. We will also develop a new class of HIV prevention efficacy trial design termed the ‘augmented active-controlled design’ which will leverage additional information to infer HIV incidence absent intervention, i.e. ‘counterfactual placebo’ HIV incidence. To extend and develop these methods, we will define a statistical framework; define approaches to estimating and drawing inference about parameters given the data; derive and compare analytic properties of the inferential methods; evaluate performance in simulation studies; and apply the methods to real data to generate new scientific insights. These novel methods have direct application to evaluating the impact of HIV preventive interventions in population-based effectiveness studies and randomized controlled efficacy trials, and will be applicable to the study of other infectious diseases. 1

项目摘要/摘要 以抗逆转录病毒为基础的艾滋病毒预防措施在预防艾滋病毒感染方面非常有效，但有许多 实施挑战。基于人群的有效性研究试图评估预防措施的现实影响 干预措施。然而，我们目前衡量预防措施有效性的能力存在重大限制。 人口一级的干预措施，因为它需要资源广泛的封闭式纵向测试 一群人。艾滋病毒新近检测(提供艾滋病毒感染时间信息的检测)提供了资源-- 对发病率的有效估计。然而，由于缺乏精确度，这类检测的实用性目前受到限制。在……里面 此外，在以下情况下，设计有效性试验以评估新的艾滋病毒预防干预措施越来越具有挑战性 有效的预防制剂是存在的。为了填补这些空白，我们将推进衡量艾滋病毒的统计方法 并开发一种新的试验设计来评估艾滋病毒预防干预的有效性。具体来说，我们将 扩展现有的使用新近分析数据估计HIV发病率的方法以适应协变量影响 关于检测特性、艾滋病毒发病率的时间趋势，以及更精确地估计艾滋病毒发病率。 我们还将开发一种新的艾滋病毒预防功效试验设计，称为增强主动控制 设计将利用额外的信息在没有干预的情况下推断艾滋病毒发病率，即 安慰剂的艾滋病毒发病率。为了扩展和发展这些方法，我们将定义一个统计框架；定义 对给定数据的参数进行估计和推断的方法；推导和比较分析 推理方法的性质；在模拟研究中评估性能；以及将这些方法应用于实际 产生新的科学见解的数据。这些新的方法直接应用于评估 以人群为基础的有效性研究和随机对照疗效试验中的艾滋病毒预防干预措施 并将适用于其他传染病的研究。 1