Novel approaches for confounding control in observational studies of generic drugs

仿制药观察研究中混杂控制的新方法

• 批准号: 9104377
• 负责人: Rishi J Desai
• 金额: $ 19.92万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9104377
• 关键词: Novel; approaches; confounding; control; observational

Abstract Generic drugs account for approximately 86% of all prescriptions dispensed in the US. Generics are approved for marketing on the basis of demonstrating bioequivalence with their brand-name counterparts and there is no formal requirement for post-marketing surveillance. However, the need for post-marketing surveillance of generics to ensure patient safety is highlighted in recent years in light of reports of suboptimal performance of certain generics. The most efficient approach to monitor the effectiveness and safety of generics in the post- marketing period is to use data collected as a part of patients' routine healthcare to conduct large observational studies comparing outcomes between users of generic and brand-name versions of a drug. However, such studies are prone to confounding bias. Therefore, we propose to conduct research aimed at improving the methodology of post-marketing studies of generics to address confounding and generate valid inferences from these studies. Specifically, our aims will be; Aim 1: Evaluate novel data sources to augment comparative studies of generics. In this Aim, we will assess the feasibility of linking novel data sources, including electronic health records from the Partners HealthCare System and data from the US census, to health insurance claims from the US Medicare program in order to identify additional confounders such as lifestyle variables and socioeconomic indicators which are usually not measured in insurance claims. Aim 2: Identify a set of generally applicable confounders that could be used in comparative studies of generics. In this Aim, we will identify a general set of confounders for observational studies of generic drugs by considering a broad array of variables across the three data sources linked in Aim 1. Aim 3: Compare the performance of various methods for confounding control in comparative studies of generics. In this Aim, we will compare a number of candidate methods for confounding control in observational studies of generics including propensity score (PS)-matching, high dimesional-PS matching, disease risk score-matching; and traditional multivariable regression adjustment.

摘要 仿制药约占美国处方总数的86%。仿制药已获批准 在展示与其品牌对应产品的生物等效性的基础上进行营销，并且没有 对上市后监督的正式要求。然而，上市后监督的必要性 近年来，鉴于有报道称仿制药的性能不佳，因此强调了确保患者安全的仿制药 某些泛型。监测仿制药有效性和安全性的最有效方法是-- 营销期是使用收集的数据作为患者日常保健的一部分，进行大规模观察 比较仿制药和品牌药使用者之间的结果的研究。然而，这样的 研究容易产生令人困惑的偏见。因此，我们建议进行研究，以改善 仿制药上市后研究的方法，以解决混淆并从以下方面产生有效的推论 这些研究。具体来说，我们的目标将是； 目的1：评估新的数据源，以加强仿制药的比较研究。 为此，我们将评估将新的数据来源，包括电子健康记录与 合作伙伴医疗系统和来自美国人口普查的数据，以及来自美国的医疗保险索赔 医疗保险计划，以确定其他混杂因素，如生活方式变量和社会经济 通常不在保险索赔中衡量的指标。 目标2：确定可用于比较研究的一组普遍适用的混杂因素 仿制药。 在这个目标中，我们将通过以下方式确定仿制药观察性研究的一般混杂因素集 考虑到目标1中链接的三个数据源的广泛变量数组。 目标3：在比较研究中比较不同混杂控制方法的性能 仿制药。 为此，我们将比较在观察性研究中混杂控制的一些候选方法。 一般包括倾向性评分(PS)匹配、高维PS匹配、疾病风险评分匹配； 和传统的多变量回归平差。