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 艾滋病毒仍然在美国和撒哈拉以南大部分地区未得到充分服务的人群中流行 非洲，促使公共卫生高度重视将艾滋病毒预防做法与暴露前预防措施相结合 预防(PrEP)。组群随机试验(CRT)是研究这些艾滋病毒预防方法不可或缺的一部分。 通过集体将个体分组随机分配到相同的治疗分配，整群随机设计 尽量减少试验武器之间的污染，并使社区一级预防工作的研究成为可能。 阶梯-楔形整群随机试验(SW-CRT)是该设计的一种最新改进，涉及UNIDI-fi。 从护理标准到干预的历史性跨越。然而，集群随机化会导致关联 在同一群组中的观测之间，并且这些观测经常被重复地评估外部- 让人感兴趣。现有的临床试验设计和监测的统计方法不能解决这种复杂性 数据结构，限制了调查人员进行用于艾滋病毒预防的统计严格CRT的能力。 该建议通过(1)开发CRT的临时监测方法来解决这一方法学上的差距 具有区间删失端点和(2)发展功率和样本量方法 分组和纵向随访的水平。间隔审查发生在艾滋病毒预防试验中，当时间- 仅在间歇性的诊所就诊时评估感兴趣的事件结果。虽然存在临时监测方法 对于集群数据和事件间隔时间数据，目前还没有方法同时处理集群数据和间隔数据。 被审查的观察结果。中期监测常用的一种统计工具是有条件的权力，即 在试验结束时检测到显著fi不能预防效果的条件概率 中期数据和一系列关于研究剩余部分的假设。目标1提出了一种基于模拟的 区间截尾CRT条件功率的计算方法。 目标2建立了具有等级聚类和纵向分类的短波CRT的样本量和功率公式 后续行动。这种依赖结构自然出现在艾滋病毒预防研究中，例如，患者就是这样 聚集在医院内分组的医生中，然后随着时间的推移对这些患者进行监控 用于艾滋病毒血清转换。阶梯楔形整群随机试验没有样本量或功效方法 处理此数据结构。当前的阶梯式楔形试验可能会因此被不适当地提供动力，使得 DIFfiCURT供调查人员检测有针对性的预防效果。 因此，根据这项建议制定的方法将提高进行创新、 需要进行整群随机HIV预防研究来评估药物的有效性和患者对药物的依从性 在高危人群中做好准备，并确定实施组合艾滋病毒预防战略的最佳方式。