Randomized Cardiovascular Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology (RCT DUPLICATE)

使用前瞻性纵向保险索赔重复的随机心血管试验：应用流行病学技术（RCT DUPLICATE）

• 批准号: 10606588
• 负责人: Sebastian G. Schneeweiss
• 金额: $ 71.34万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10606588
• 关键词: Cardiovascular system; Characteristics; Clinical; Data; Databases; Decision Making; Drug Approval; Educational workshop; Epidemiologic Methods; Evaluation; Exclusion Criteria; Factor Analysis; Future; Health; Healthcare; Individual; Internet; Knowledge; Lead; Measures; Meta-Analysis; Methodology; Methods; Modeling; Observational Study; Outcome; Patients; Performance; Pharmaceutical Preparations; Population; Provider; Public Health; Publishing; Randomized; Randomized, Controlled Trials; Reporting; Research; Research Design; Research Personnel; Review Literature; Sampling; Savings; Variant; Work; World Health; analytical method; cost; design; health data; improved; innovation; insight; insurance claims; patient population; prospective; randomized trial; searchable database; success; treatment comparison; treatment effect; unethical

Project Abstract Randomized controlled trials (RCTs) remain the gold standard for establishing the causal relationship between medications and health outcomes. However, for some clinical questions RCTs may be infeasible, unethical, costly, or generalizable to only a very narrow population. In these cases, observational studies from routinely collected “real-world” health data (RWD) are crucial for supplementing the evidence from RCTs. RWD is particularly useful in the context of cardiovascular outcomes, which are typically well-captured in healthcare databases, but concern about the validity of RWD studies mitigate their impact. The purpose of this project is to empirically evaluate the validity of RWD studies by conducting a systematic replication of a large sample of randomized trials of cardiovascular outcomes, including both completed trials with results already available and ongoing trials where results are not yet released, in order to ensure that validity is not influenced by the availability of trial results. RWD studies are designed to match the corresponding RCT as closely as possible, including exposures, outcomes, and inclusion/exclusion criteria, and RWD studies utilize a variety of design and analysis approaches in order to provide guidance on which questions can be answered in RWD and with which methods. As part of this project, a new meta-analysis model will be developed to model the variation in treatment effect estimates between RCTs and RWD, combining data across RWD methodologic approaches and across clinical questions. All treatment effect estimates for all studies, including both RCT and RWD results, will be reported online, and the results of ongoing RCTs will be added as they become available. This project is the first to evaluate the validity of RWD studies of cardiovascular outcomes based on empirical performance in a large sample of clinical questions across a wide variety of epidemiologic and analytical methods. Findings will guide investigators planning RWD studies of cardiovascular outcomes and increase confidence in the ability of RWD studies to answer questions of importance to patients, providers, and other stakeholders.

项目摘要 随机对照试验（RCT）仍然是确定两者之间因果关系的黄金标准 然而，对于某些临床问题，随机对照试验可能不可行、不道德、 在这些情况下，常规的观察性研究成本高昂，或者只能推广到非常有限的人群。 收集的“真实世界”健康数据（RWD）对于补充 RWD 的证据至关重要。 在心血管结果方面特别有用，这些结果通常在医疗保健中得到很好的体现 数据库，但对 RWD 研究有效性的担忧减轻了其影响 该项目的目的是 通过对大样本进行系统复制来实证评估 RWD 研究的有效性 心血管结局的随机试验，包括已完成的试验和已经获得结果的试验 正在进行的试验，结果尚未公布，以确保有效性不受 RWD 研究的目的是尽可能匹配相应的 RCT， 包括暴露、结果和纳入/排除标准，RWD 研究采用多种设计 和分析方法，以便为可以在 RWD 中回答哪些问题提供指导 作为该项目的一部分，将开发一个新的荟萃分析模型来模拟变化。 RCT 和 RWD 之间的治疗效果估计，结合 RWD 方法学方法的数据 以及所有研究的所有治疗效果估计，包括 RCT 和 RWD 结果将在线报告，并且正在进行的随机对照试验的结果将在可用时添加。 该项目是第一个基于经验评估心血管结果 RWD 研究有效性的项目 在广泛的流行病学和分析领域的大样本临床问题中的表现 研究结果将指导研究人员规划心血管结局的 RWD 研究并增加结果。 对 RWD 研究回答对患者、提供者和其他人员重要的问题的能力充满信心 利益相关者。

项目成果

Real-World Evidence for Assessing Pharmaceutical Treatments in the Context of COVID-19.

在 COVID-19 背景下评估药物治疗的真实世界证据。

• 发表时间: 2021
• 影响因子: 6.7
• 作者: Franklin, Jessica M;Lin, Kueiyu Joshua;Gatto, Nicolle M;Rassen, Jeremy A;Glynn, Robert J;Schneeweiss, Sebastian
• 通讯作者: Schneeweiss, Sebastian

Emulation Differences vs. Biases When Calibrating Real-World Evidence Findings Against Randomized Controlled Trials.

根据随机对照试验校准现实世界的证据结果时的仿真差异与偏差。

• 发表时间: 2020
• 影响因子: 6.7
• 作者: Franklin, Jessica M;Glynn, Robert J;Suissa, Samy;Schneeweiss, Sebastian
• 通讯作者: Schneeweiss, Sebastian

Real-world evidence to support regulatory decision making: New or expanded medical product indications.

支持监管决策的真实证据：新的或扩展的医疗产品适应症。

• 发表时间: 2021
• 影响因子: 2.6
• 作者: Franklin, Jessica M;Liaw, Kai;Iyasu, Solomon;Critchlow, Cathy W;Dreyer, Nancy A
• 通讯作者: Dreyer, Nancy A

When Can Nonrandomized Studies Support Valid Inference Regarding Effectiveness or Safety of New Medical Treatments?

非随机研究何时可以支持关于新药物治疗有效性或安全性的有效推论？

• 发表时间: 2022
• 影响因子: 6.7
• 作者: Franklin, Jessica M;Platt, Richard;Dreyer, Nancy A;London, Alex John;Simon, Gregory E;Watanabe, Jonathan H;Horberg, Michael;Hernandez, Adrian;Califf, Robert M
• 通讯作者: Califf, Robert M

Real-World Evidence Prediction of a Phase IV Oncology Trial: Comparative Degarelix vs Leuprolide Safety.

IV 期肿瘤学试验的真实世界证据预测：比较地加瑞克与亮丙瑞林的安全性。

• 发表时间: 2022-08-10
• 影响因子: 4.4
• 作者: Merola, David;Schneeweiss, Sebastian;Sreedhara, Sushama K;Zabotka, Luke E;Quinto, Kenneth;Concato, John;Wang, Shirley V
• 通讯作者: Wang, Shirley V