Novel Statistical Methods for Cluster-Randomized HIV Prevention Trials

整群随机艾滋病毒预防试验的新统计方法

• 批准号: 9755198
• 负责人: Kaitlyn Ann Cook
• 金额: $ 2.88万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9755198
• 关键词: AIDS prevention; Address; Adoption; Advocate; Africa South of the Sahara; Bisexual; Botswana; Chronic; Clinic Visits; Clinical Trials Design; Cluster Analysis; Cluster randomized trial; Communities; Complex; Computer software; Data; Dependence; Effectiveness; Ethical Issues; Evaluation; Event; Feasibility Studies; Fellowship; Gays; Goals; HIV; HIV Infections; HIV Seropositivity; HIV prevention trial; Health system; Healthcare Systems; Hospitals; Incidence; Individual; Infrastructure; Interdisciplinary Study; Intervention; Latino; Measures; Methodology; Methods; Modification; Monitor; Monitoring Clinical Trials; Outcome; Patients; Performance; Physicians; Populations at Risk; Prevention; Prevention Measures; Prevention strategy; Probability; Procedures; Process; Public Health; Randomized; Reproducibility; Research; Research Design; Research Personnel; Sample Size; Scheme; Statistical Methods; Structure; Time; Underserved Population; United States; acute infection; antiretroviral therapy; arm; base; career; compliance behavior; computer program; data management; data modeling; data structure; design; experience; follow-up; high risk; improved; infection risk; innovation; interest; intervention effect; male; method development; novel; pre-exposure prophylaxis; simulation; skills; socioeconomics; standard of care; success; tool

Project Summary/Abstract HIV remains prevalent among underserved populations in the United States and large parts of sub-Saharan Africa, prompting a strong public health focus on combination HIV prevention practices and pre-exposure pro- phylaxis (PrEP). Cluster-randomized trials (CRTs) are integral to the study of these HIV prevention methods. By collectively randomizing groups of individuals to the same treatment assignment, cluster-randomized designs minimize contamination between trial arms and make feasible the study of community-level prevention efforts. Stepped-wedge cluster-randomized trials (SW-CRTs) are a recent modification of this design involving unidi- rectional crossover from standard-of-care to intervention. However, cluster randomization induces correlation between observations in the same cluster, and these observations are often repeatedly assessed for the out- come of interest. Existing statistical methods for clinical trial design and monitoring fail to address such complex data structures, limiting investigators' ability to conduct statistically rigorous CRTs for HIV prevention. This proposal addresses this methodological gap by (1) developing interim monitoring methods for CRTs with interval-censored endpoints and (2) developing power and sample size methods for SW-CRTs with multiple levels of clustering and longitudinal follow-up. Interval-censoring occurs in HIV prevention trials when the time- to-event outcome of interest is assessed only at intermittent clinic visits. While interim monitoring methods exist for clustered data and for time-to-event data separately, no methods currently handle both clustered and interval- censored observations. One statistical tool commonly used for interim monitoring is the conditional power, the conditional probability of detecting a significant preventative effect at the end of the trial given both the observed interim data and a set of assumptions about the remainder of the study. Aim 1 proposes a simulation-based approach to calculating the conditional power of CRTs with interval-censored endpoints. Aim 2 develops sample size and power formulae for SW-CRTs with hierarchical clustering and longitudinal follow-up. Such dependence structures arise naturally in HIV prevention studies, as, for example, patients are clustered within physicians who are grouped within hospitals, and these patients are then monitored over time for HIV seroconversion. No sample size or power methods for stepped-wedge cluster-randomized trials directly address this data structure. Current stepped-wedge trials may be inappropriately powered as a result, making it difficult for investigators to detect pertinent prevention effects. Thus, the methods developed under this proposal will improve the feasibility of conducting the innovative, cluster-randomized HIV prevention studies needed to evaluate the effectiveness of and patient adherence to PrEP in at-risk populations, and to determine the best ways to implement combination HIV prevention strategies.

项目摘要/摘要 在美国和撒哈拉以南地区的大部分地区，艾滋病毒仍然普遍存在 非洲，促使公共卫生强烈关注艾滋病毒预防习惯和暴露前的联合关系 趋障（准备）。聚类随机试验（CRT）是对这些HIV预防方法的研究不可或缺的一部分。 通过将个体的群体集体随机分配到相同的治疗分配，群集随机设计 最大程度地减少试验臂之间的污染，并使对社区水平的预防工作的研究可行。 阶梯式悬挂聚类的群集试验（SW-CRT）是对这种设计的最新修改，涉及Unidi- 从护理到干预的截肢跨界。但是，聚类随机化诱导相关性 在同一群集中的观察结果之间，这些观察结果经常被反复评估 有兴趣。现有用于临床试验设计和监测的统计方法无法解决这种复杂的问题 数据结构，限制了研究人员在统计上进行统计严格的CRT以预防HIV的能力。 该建议通过（1）开发CRT的临时监控方法来解决此方法上的差距 具有间隔审查的端点和（2）为具有多个的SW-CRT开发功率和样本尺寸方法 聚类和纵向随访的水平。时间进行间隔审查发生在艾滋病毒预防试验中 仅在间歇性诊所就诊时就评估了感兴趣的事件结果。虽然存在临时监视方法 对于群集数据和分别为事件的数据数据，目前尚无方法处理群集和间隔 - 审查的观察结果。一种通常用于临时监视的统计工具是条件功率， 鉴于观察到 临时数据和有关其余研究的一组假设。 AIM 1提案基于模拟 用间隔对端点计算CRT的条件功率的方法。 AIM 2开发了具有分层聚类和纵向的SW-CRT的样本量和功率公式 后续。这种依赖性结构在HIV预防研究中自然出现，例如，患者是 聚集在分组在医院中的医生中，然后随着时间的流逝而监测这些患者 用于HIV血清转化。直接直接用于阶梯式聚类群集试验的样本量或功率方法 解决此数据结构。当前的阶梯边缘试验可能不适当地供电，因此 对于研究人员而言，很难检测相关的预防作用。 这是，根据本提案开发的方法将提高进行创新的可行性， 群集随机的HIV预防研究需要评估患者对 准备高危人群，并确定实施艾滋病毒预防策略的最佳方法。