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A Statistical Roadmap for Journey from Real-World Data to Real-World Evidence

机译:从真实数据到现实世界证据的旅程统计路线图

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摘要

Randomized controlled clinical trials are the gold standard for evaluating the safety and efficacy of pharmaceutical drugs, but in many cases their costs, duration, limited generalizability, and ethical or technical feasibility have caused some to look for real-world studies as alternatives. On the other hand, real-world data may be much less convincing due to the lack of randomization and the presence of confounding bias. In this article, we propose a statistical roadmap to translate real-world data (RWD) to robust real-world evidence (RWE). The Food and Drug Administration (FDA) is working on guidelines, with a target to release a draft by 2021, to harmonize RWD applications and monitor the safety and effectiveness of pharmaceutical drugs using RWE. The proposed roadmap aligns with the newly released framework for FDA's RWE Program in December 2018 and we hope this statistical roadmap is useful for statisticians who are eager to embark on their journeys in the real-world research.
机译:随机对照临床试验是评估药物的安全性和功效的黄金标准,但在许多情况下,他们的成本,持续时间,有限的普遍性和道德或技术可行性导致一些人作为替代品的现实研究。 另一方面,由于缺乏随机化和混淆偏见的存在,现实世界数据可能不那么令人信服。 在本文中,我们提出了一个统计的路线图来将现实世界数据(RWD)转化为强大的真实证据(RWE)。 食品和药物管理局(FDA)正在研究指导方针,以释放2021年的草案,以协调RWD申请并监测使用RWE的药物的安全性和有效性。 建议的路线图与2018年12月与FDA RWE计划的新发布的框架保持一致,我们希望这一统计路线图对统计人员有用,旨在渴望在现实世界研究中开始旅程。

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