Interpreting IV Estimates with Treatment Effect Heterogeneity: ACE/ARBs & Race

解释 IV 估计与治疗效果异质性：ACE/ARB

• 批准号: 8034425
• 负责人: JOHN M BROOKS
• 金额: $ 145.8万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2013-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8034425
• 关键词: Acute myocardial infarction; Address; African American; Age; Binding; Cardiovascular system; Chronic; Clinical; Data; Databases; Diagnosis; Disease-Free Survival; Drug Prescriptions; Effectiveness; Ensure; Gender; Goals; Guidelines; Health Policy; Health Services Research; Healthcare; Heterogeneity; Internet; Knowledge; Medicare; Medicare claim; Methodology; Methods; Patients; Policies; Policy Maker; Population Heterogeneity; Property; Publishing; Race; Renin-Angiotensin System; Research; Research Personnel; Sampling; Secondary Prevention; Source; Treatment Effectiveness; United States Centers for Medicare and Medicaid Services; abstracting; beneficiary; comparative; comparative effectiveness; control trial; effectiveness research; falls; improved; models and simulation; mortality; public health relevance; racial difference; simulation; treatment effect

DESCRIPTION (provided by applicant): Treatment rates vary dramatically across patients grouped by race, age, and gender. If treatment effects are heterogeneous across patients, though, it is not clear from treatment rate comparisons alone whether treatment rates should be increased or decreased for specific patient groups. Theorists have suggested that estimates of the "local average treatment effect" LATE produced by instrumental variable (IV) estimators provide evidence to assess whether treatment rates should be modified. However, alternative IV estimators exist that have distinct approaches to estimate LATEs across patient groups. No methodological research has contrasted the ability of alternative IV estimators to estimate LATEs across patient groups. Since 2005 over 375 articles have been published in healthcare using IV estimators. Methodological research is needed to ensure proper inferences are made from IV estimates when evaluating the comparative effectiveness of treatments for distinct patient groups. This research will first perform simulation modeling to assess the properties of alternative IV estimators to estimate treatment effectiveness within patient groups when treatment effects are heterogeneous both across and within these groups. Next, we will estimate treatment effectiveness using alternative IV estimators for a treatment thought to have heterogeneous treatment effects both within and across patient groups and interpret these estimates through the prism of our simulation findings. Guidelines suggest that renin- angiotensin system antagonists (ACE/ARBs) be used for secondary prevention post-acute myocardial infarction (AMI), but controlled trial data suggests that ACE/ARB effectiveness is lower for African Americans than whites. In practice, African American ACE/ARB utilization rates are significantly lower post AMI than whites. Are these rate differences by race justified by the clinical evidence or are clinicians underutilizing ACE/ARBs in African Americans? To investigate this question we will use Medicare claims from the Centers for Medicare & Medicaid Services (CMS) Chronic Condition Data Warehouse (CCW) for patients with primary diagnosis of AMI that have Medicare "Part D" prescription drug coverage. In addition, we will perform chart abstractions for a portion of our AMI sample to assess the extent that factors unmeasured in Medicare claims confound our IV estimates and whether our estimates can be interpreted as bounds of true treatment effects with each race group. PUBLIC HEALTH RELEVANCE: Assessing the comparative effectiveness of treatments in practice often requires analysis of observational healthcare databases. The properties of methods available to estimate comparative effectiveness from observational data are often unclear. The goal of this research is to provide clarity to healthcare policy-makers as to the treatment effect inferences that can be made from instrumental variable (IV) estimators.

描述（由申请人提供）：按种族、年龄和性别分组的患者的治疗率差异很大。然而，如果不同患者的治疗效果存在差异，仅通过治疗率比较并不清楚是否应该增加或减少特定患者组的治疗率。理论家建议，工具变量（IV）估计器产生的“局部平均治疗效果”LATE 的估计为评估是否应修改治疗率提供了证据。然而，存在替代的 IV 估计器，它们具有不同的方法来估计不同患者组的 LATE。没有方法学研究对比替代 IV 估计器估计患者组 LATE 的能力。自 2005 年以来，已有超过 375 篇使用 IV 估算器的医疗保健文章发表。需要进行方法学研究，以确保在评估不同患者组治疗的比较有效性时，根据 IV 估计值做出正确的推论。 这项研究将首先进行模拟建模，以评估替代 IV 估计器的特性，以在患者组之间和组内的治疗效果存在异质性时估计患者组内的治疗效果。接下来，我们将使用替代 IV 估计量来估计治疗效果，该治疗被认为在患者组内和患者组之间具有异质性治疗效果，并通过我们的模拟结果的棱镜解释这些估计值。指南建议将肾素-血管紧张素系统拮抗剂（ACE/ARB）用于急性心肌梗死（AMI）后的二级预防，但对照试验数据表明，ACE/ARB 对非裔美国人的有效性低于白人。实际上，非裔美国人 AMI 后 ACE/ARB 的利用率明显低于白人。这些不同种族的比率差异是否有临床证据证明是合理的，还是临床医生在非洲裔美国人中没有充分利用 ACE/ARB？为了调查这个问题，我们将使用 Medicare 和 Medicaid 服务中心 (CMS) 慢性病数据仓库 (CCW) 的 Medicare 索赔，用于初步诊断为 AMI 且拥有 Medicare“D 部分”处方药承保的患者。此外，我们将对 AMI 样本的一部分进行图表抽象，以评估医疗保险索赔中未测量的因素在多大程度上混淆了我们的 IV 估计，以及我们的估计是否可以解释为每个种族组的真实治疗效果的界限。 公共卫生相关性：评估实践中治疗的比较有效性通常需要分析观察性医疗保健数据库。可用于根据观测数据估计比较有效性的方法的特性通常不清楚。这项研究的目的是让医疗保健政策制定者清楚地了解可以从工具变量 (IV) 估计器中得出的治疗效果推论。