When and How Can Real World Data Analyses Substitute for Randomized Controlled Trials?

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  • Jessica M. Franklin
    Division of Pharmacoepidemiology and Pharmacoeconomics Brigham and Women's Hospital and Harvard Medical School Boston Massachusetts USA
  • Sebastian Schneeweiss
    Division of Pharmacoepidemiology and Pharmacoeconomics Brigham and Women's Hospital and Harvard Medical School Boston Massachusetts USA

説明

<jats:p>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.</jats:p>

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