Franklin Jessica M, Schneeweiss Sebastian
Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Clin Pharmacol Ther. 2017 Dec;102(6):924-933. doi: 10.1002/cpt.857. Epub 2017 Sep 25.
Regulators consider randomized controlled trials (RCTs) as the gold standard for evaluating the safety and effectiveness of medications, but their costs, duration, and limited generalizability have caused some to look for alternatives. Real world evidence based on data collected outside of RCTs, such as registries and longitudinal healthcare databases, can sometimes substitute for RCTs, but concerns about validity have limited their impact. Greater reliance on such real world data (RWD) in regulatory decision making requires understanding why some studies fail while others succeed in producing results similar to RCTs. Key questions when considering whether RWD analyses can substitute for RCTs for regulatory decision making are WHEN one can study drug effects without randomization and HOW to implement a valid RWD analysis if one has decided to pursue that option. The WHEN is primarily driven by externalities not controlled by investigators, whereas the HOW is focused on avoiding known mistakes in RWD analyses.
监管机构将随机对照试验（RCT）视为评估药物安全性和有效性的金标准，但其成本、持续时间和有限的普遍性促使一些人寻求替代方法。基于RCT之外收集的数据（如登记处和纵向医疗保健数据库）得出的真实世界证据有时可以替代RCT，但对有效性的担忧限制了其影响力。在监管决策中更多地依赖此类真实世界数据（RWD），需要理解为什么有些研究失败而有些研究却成功得出与RCT相似的结果。在考虑RWD分析是否可以替代RCT用于监管决策时，关键问题是何时可以在不进行随机化的情况下研究药物效果，以及如果决定采用该方法，如何进行有效的RWD分析。何时主要由研究者无法控制的外部因素驱动，而如何则侧重于避免RWD分析中已知的错误。
