Centers for Epidemiology and Environmental Health, Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island.
Center for Health Equity Research, Department of Behavioral and Social Sciences, School of Public Health, Brown University, Providence, Rhode Island.
Am J Epidemiol. 2018 Feb 1;187(2):316-325. doi: 10.1093/aje/kwx247.
Reducing racial/ethnic disparities in human immunodeficiency virus (HIV) disease is a high priority. Reductions in HIV racial/ethnic disparities can potentially be achieved by intervening on important intermediate factors. The potential population impact of intervening on intermediates can be evaluated using observational data when certain conditions are met. However, using standard stratification-based approaches commonly employed in the observational HIV literature to estimate the potential population impact in this setting may yield results that do not accurately estimate quantities of interest. Here we describe a useful conceptual and methodological framework for using observational data to appropriately evaluate the impact on HIV racial/ethnic disparities of interventions. This framework reframes relevant scientific questions in terms of a controlled direct effect and estimates a corresponding proportion eliminated. We review methods and conditions sufficient for accurate estimation within the proposed framework. We use the framework to analyze data on 2,329 participants in the CFAR [Centers for AIDS Research] Network of Integrated Clinical Systems (2008-2014) to evaluate the potential impact of universal prescription of and ≥95% adherence to antiretroviral therapy on racial disparities in HIV virological suppression. We encourage the use of the described framework to appropriately evaluate the potential impact of targeted interventions in addressing HIV racial/ethnic disparities using observational data.
降低人类免疫缺陷病毒 (HIV) 疾病中的种族/民族差异是当务之急。通过干预重要的中间因素,可以减少 HIV 种族/民族差异。当满足某些条件时,可以使用观察性数据评估干预中间因素的潜在人群影响。然而,在这种情况下,使用标准的基于分层的方法通常用于观察性 HIV 文献来估计潜在人群的影响可能会产生不准确地估计感兴趣的数量的结果。在这里,我们描述了一个有用的概念和方法框架,用于使用观察性数据来适当评估干预措施对 HIV 种族/民族差异的影响。该框架根据受控直接效应重新表述相关科学问题,并估计相应的消除比例。我们回顾了在建议的框架内进行准确估计所需的方法和条件。我们使用该框架分析了 2008 年至 2014 年 CFAR [艾滋病研究中心]网络综合临床系统中的 2329 名参与者的数据,以评估普遍处方和≥95%的抗逆转录病毒治疗依从性对 HIV 病毒学抑制中种族差异的潜在影响。我们鼓励使用描述的框架,使用观察性数据适当评估针对 HIV 种族/民族差异的靶向干预措施的潜在影响。