2019
DOI: 10.1002/cpt.1658
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Examining the Use of Real‐World Evidence in the Regulatory Process

Abstract: The 21st Century Cures Act passed by the United States Congress mandates the US Food and Drug Administration to develop guidance to evaluate the use of real‐world evidence (RWE) to support the regulatory process. RWE has generated important medical discoveries, especially in areas where traditional clinical trials would be unethical or infeasible. However, RWE suffers from several issues that hinder its ability to provide proof of treatment efficacy at a level comparable to randomized controlled trials. In thi… Show more

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Cited by 110 publications
(135 citation statements)
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References 122 publications
(191 reference statements)
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“…8 Although data from EHRs have less regulatory acceptance compared with data from RCTs in addition to weaknesses, such as informative missingness and observational biases, it facilitates the quantity, accessibility, and heterogeneity of offline observational data for a variety of diseases and patients. We refer the readers to Beaulieu-Jones et al 9 for a detailed review of the advantages and limitations of using real-world evidence, such as EHRs, to infer treatment effects. Estimating individualized treatment effects from EHR data represents a thriving area of research, in which machine learning methods are primed to take center stage.…”
Section: From Randomized Trials To Patient Observational Datamentioning
confidence: 99%
See 1 more Smart Citation
“…8 Although data from EHRs have less regulatory acceptance compared with data from RCTs in addition to weaknesses, such as informative missingness and observational biases, it facilitates the quantity, accessibility, and heterogeneity of offline observational data for a variety of diseases and patients. We refer the readers to Beaulieu-Jones et al 9 for a detailed review of the advantages and limitations of using real-world evidence, such as EHRs, to infer treatment effects. Estimating individualized treatment effects from EHR data represents a thriving area of research, in which machine learning methods are primed to take center stage.…”
Section: From Randomized Trials To Patient Observational Datamentioning
confidence: 99%
“…At the end of the day, because we never observe any counterfactuals, expert knowledge is always needed to validate the model' s estimates of the treatment effects. 9 Furthermore, we must ensure that the patient population used to train the model is representative of the patient population the model is to be deployed on. If this is not the case, additional methods are needed to ensure that causal inference models are robust to distributional shifts in the patient population.…”
Section: Limitations and Future Research Directionsmentioning
confidence: 99%
“…For regulatory definitions of RWD and a useful discussion of the strengths and challenges it is worth reading Beaulieu-Jones. 1 Of course, the need to consider other types of study complicates the discussion of strength of evidence. If we allow a wider range of study methodology the specification of exactly what types of study and results will be acceptable becomes extremely challenging.…”
Section: Most Of Us Have An Idea Of What We Mean By Strength Of Evi-mentioning
confidence: 99%
“…They conclude that the answer to this question is “yes,” indeed that cross‐border dialogue between international regulatory agencies is a well‐established and near‐daily activity ( Figure ). Through a survey, they identified 30 clusters for scientific collaboration and information exchange in certain disease areas or specific topics such as biosimilars, pediatric medicines, pharmacogenomics, and real‐world evidence/big data . Two recent, independent comparisons between outcomes of reviews by the FDA and EMA showed a high degree of concordance, which could indicate that such international collaboration has a positive impact on the consistency of regulatory decision making.…”
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confidence: 99%