Multilevel Propensity Method to Reduce Bias in Comparative Effectiveness Research

描述（由申请人提供）：集群随机临床试验（rct）和观察性研究在基线时都容易受到治疗组不平衡的影响。这个问题出现在不使用患者水平随机化的设计中。不平衡反过来又影响了治疗组的比较。目的：本申请的目的是开发和评估一种统计方法，以减少纵向比较有效性研究中非等效对照组引入的偏倚。方法：将多层次倾向得分匹配这一创新方法在模拟研究中进行评估，并应用于情绪障碍的比较有效性研究。这种方法与我们开发和评估非随机研究的新治疗效果分析的工作直接一致。本项目有四个目标：目标1：纵向聚类随机对照试验中多水平匹配的评估：通过模拟研究，评估在聚类数量较少（<20）的纵向聚类随机对照试验中多水平倾向得分匹配的偏倚减少和信号检测。目的2：应用于档案类随机对照试验数据：使用多水平倾向评分匹配重新分析来自两项已完成的老年抑郁症类随机对照试验的数据，PROSPECT和TRIAD研究。PROSPECT研究了减少自杀和抑郁的干预措施。TRIAD评估了护士改善抑郁症护理的干预措施。目标3：纵向观察研究中多水平匹配的评估：进行模拟研究，评估在观察数量不足以进行五分位分层的纵向观察研究中，多水平倾向评分匹配的偏倚减少和信号检测。目标4：应用于档案纵向观察数据：在NIMH合作抑郁症研究（CDS）中，使用多水平倾向评分匹配来检查抗抑郁药和情绪稳定药物的有效性和安全性，这是一项为期31年的情绪障碍观察性研究。摘要：本项目旨在对一种有前景的统计方法进行全面评估。预计该方法将减少偏差并增强两种设计中的信号检测，从而有助于比较有效性研究，从而更准确地确定患者的最佳治疗方法。

DESCRIPTION (provided by applicant): Cluster randomized clinical trials (RCTs) and observational studies are each vulnerable to treatment group imbalance at baseline. This problem is seen in designs such as these that do not use patient-level randomization. Imbalance, in turn, compromises treatment group comparisons. Objective: The objective of this application is to develop and evaluate a statistical method that will reduce bias introduced by non-equivalent comparison groups in longitudinal comparative effectiveness research. Method: The innovative method, multilevel propensity score matching, will be evaluated in simulation studies and applied to comparative effectiveness research in mood disorders. This approach is in direct continuity with our work that developed and evaluated novel treatment effectiveness analyses for non- randomized studies. There are four aims of the project: Aim 1: Evaluation of Multilevel Matching in Longitudinal Cluster RCTs: Conduct a simulation study to evaluate bias reduction and signal detection with multilevel propensity score matching in longitudinal cluster RCTs where the number of clusters is small (<20). Aim 2: Application to Archival Cluster RCT Data: Use multilevel propensity score matching to reanalyze data from two completed cluster RCTs for geriatric depression, the PROSPECT and TRIAD studies. PROSPECT examined interventions to reduce suicidality and depression. TRIAD evaluated interventions for nurses to improve depression care. Aim 3: Evaluation of Multilevel Matching in Longitudinal Observational Studies: Conduct a simulation study to evaluate bias reduction and signal detection with multilevel propensity score matching in longitudinal, observational studies where the number of observations is not sufficient for quintile stratification. Aim 4: Application to Archival Longitudinal Observational Data: Use multilevel propensity score matching to examine efficacy and safety of antidepressants and mood stabilizer medications in the NIMH Collaborative Depression Study (CDS), a 31 year observational study of mood disorders. Summary: This project is designed to conduct a comprehensive evaluation of a promising statistical methodology. It is anticipated that this method will reduce bias and enhance signal detection in two designs that can contribute to comparative effectiveness research that will more accurately identify the optimal treatment for patients. PUBLIC HEALTH RELEVANCE: Reducing the burden of mental illness at the public health level requires identification of safe and effective treatments. To address this challenge, comparative effectiveness research must provide empirical evidence that guides the selection of treatment. The objective of this application is to develop an innovative statistical method that will reduce bias and, therefore, more accurately identify the optimal treatment for patients and better inform clinicians on best practices.