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

描述(由申请人提供)：不同种族、年龄和性别的患者的治疗率差异很大。然而，如果治疗效果在患者中是不同的，仅从治疗率比较就不清楚特定患者组的治疗率应该增加还是减少。理论家认为，工具变量(IV)估计者对后期产生的“局部平均治疗效应”的估计为评估是否应该修改治疗率提供了证据。然而，存在另一种IV估计器，它们具有不同的方法来估计患者组中的LATS。没有方法学研究对比不同的IV估计器在不同患者组中估计LATE的能力。自2005年以来，使用IV估计器在医疗保健领域发表了超过375篇文章。在评估不同患者组治疗的相对有效性时，需要进行方法学研究，以确保从IV估计中做出适当的推断。这项研究将首先进行模拟建模，以评估替代IV估计器的性质，以评估患者组内的治疗效果，当治疗效果在这些组之间和组内都是不同的时候。接下来，我们将使用替代的IV估计器来估计治疗有效性，这种治疗被认为在患者组内和跨患者组具有不同的治疗效果，并通过我们的模拟结果的棱镜来解释这些估计。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。在实践中，非裔美国人的ACE/ARB使用率在急性心肌梗死后显著低于白人。这些按种族划分的比率差异是否被临床证据证明是合理的，还是临床医生在非裔美国人中未充分利用ACE/ARB？为了调查这个问题，我们将使用联邦医疗保险和医疗补助服务中心(CMS)慢性条件数据仓库(CCW)中的联邦医疗保险索赔，适用于拥有联邦医疗保险“D部分”处方药覆盖范围的初诊急性心肌梗死患者。此外，我们将对我们的部分急性心肌梗死样本进行图表抽象，以评估联邦医疗保险索赔中未测量的因素对我们的IV估计的混淆程度，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：评估实践中治疗的相对有效性通常需要分析观察性医疗保健数据库。可用于从观测数据估计相对有效性的方法的性质往往不清楚。这项研究的目的是为医疗政策制定者提供明确的治疗效果推论，这些推论可以由工具变量(IV)估计器做出。

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.