Trial designs using real‐world data: The changing landscape of the regulatory approval process

观察研究 杠杆(统计) 风险分析(工程) 医学 随机对照试验 临床研究设计 真实世界数据 数据收集 临床试验 过程(计算) 管理科学 计算机科学 数据科学 机器学习 工程类 操作系统 外科 病理 统计 数学
作者
Elodie Baumfeld Andre,Robert F. Reynolds,Patrick Caubel,Laurent Azoulay,Nancy A Dreyer
出处
期刊:Pharmacoepidemiology and Drug Safety [Wiley]
卷期号:29 (10): 1201-1212 被引量:177
标识
DOI:10.1002/pds.4932
摘要

There is a need to develop hybrid trial methodology combining the best parts of traditional randomized controlled trials (RCTs) and observational study designs to produce real-world evidence (RWE) that provides adequate scientific evidence for regulatory decision-making.This review explores how hybrid study designs that include features of RCTs and studies with real-world data (RWD) can combine the advantages of both to generate RWE that is fit for regulatory purposes.Some hybrid designs include randomization and use pragmatic outcomes; other designs use single-arm trial data supplemented with external comparators derived from RWD or leverage novel data collection approaches to capture long-term outcomes in a real-world setting. Some of these approaches have already been successfully used in regulatory decisions, raising the possibility that studies using RWD could increasingly be used to augment or replace traditional RCTs for the demonstration of drug effectiveness in certain contexts. These changes come against a background of long reliance on RCTs for regulatory decision-making, which are labor-intensive, costly, and produce data that can have limited applicability in real-world clinical practice.While RWE from observational studies is well accepted for satisfying postapproval safety monitoring requirements, it has not commonly been used to demonstrate drug effectiveness for regulatory purposes. However, this position is changing as regulatory opinions, guidance frameworks, and RWD methodologies are evolving, with growing recognition of the value of using RWE that is acceptable for regulatory decision-making.
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