When and How Can Real World Data Analyses Substitute for Randomized Controlled Trials?
When and How Can Real World Data Analyses Substitute for Randomized Controlled Trials?
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DOI：
10.1002/cpt.857
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发表时间：
2017-12-01
影响因子：
6.7
通讯作者：
Schneeweiss, Sebastian
中科院分区：
文献类型：
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作者：
Franklin, Jessica M.;Schneeweiss, Sebastian
监管机构认为随机对照试验（RCT）是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导致一些人寻找替代品。基于RCT以外收集的数据的真实的世界证据，例如登记研究和纵向医疗数据库，有时可以替代RCT，但对有效性的担忧限制了其影响。在监管决策中更多地依赖这些真实的世界数据（RWD），需要理解为什么有些研究失败，而另一些研究成功地产生了与RCT相似的结果。在考虑RWD分析是否可以替代RCT进行监管决策时，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应，以及如果决定采用该方法，如何实施有效的RWD分析。WHEN主要由调查人员无法控制的外部性驱动，而HOW则专注于避免RWD分析中的已知错误。
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 decisionmaking 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.