Literature DB >> 34416020

Assessing and Interpreting Real-World Evidence Studies: Introductory Points for New Reviewers.

Shirley V Wang1, Sebastian Schneeweiss1.   

Abstract

Nonrandomized real-world evidence (RWE) studies are conducted using healthcare data collected as part of clinical practice. As RWE studies are increasingly considered for regulatory, coverage, and other clinical decision making, nonspecialists will find themselves in the position of assessing the validity of RWE studies, a field that may be less familiar to them. This introductory guide provides conceptual guidance for reviewing RWE studies and is particularly directed at professionals for whom this is new or whose prior experience has primarily been in reviewing randomized controlled trial evidence. We focus on RWE studies that make causal inference, evaluating whether one treatment option is better, worse, or neutral compared to another. Although we provide citations to direct the reader to resources with more details on complex issues, this guide cannot substitute for years of training and expertise in the field.
© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.

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Year:  2021        PMID: 34416020      PMCID: PMC8771197          DOI: 10.1002/cpt.2398

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  25 in total

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3.  Graphical Depiction of Longitudinal Study Designs in Health Care Databases.

Authors:  Sebastian Schneeweiss; Jeremy A Rassen; Jeffrey S Brown; Kenneth J Rothman; Laura Happe; Peter Arlett; Gerald Dal Pan; Wim Goettsch; William Murk; Shirley V Wang
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4.  Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available.

Authors:  Miguel A Hernán; James M Robins
Journal:  Am J Epidemiol       Date:  2016-03-18       Impact factor: 4.897

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

Authors:  Jessica M Franklin; Sebastian Schneeweiss
Journal:  Clin Pharmacol Ther       Date:  2017-09-25       Impact factor: 6.875

6.  Improving Transparency to Build Trust in Real-World Secondary Data Studies for Hypothesis Testing-Why, What, and How: Recommendations and a Road Map from the Real-World Evidence Transparency Initiative.

Authors:  Lucinda S Orsini; Marc Berger; William Crown; Gregory Daniel; Hans-Georg Eichler; Wim Goettsch; Jennifer Graff; John Guerino; Pall Jonsson; Nirosha Mahendraratnam Lederer; Brigitta Monz; C Daniel Mullins; Sebastian Schneeweiss; David Van Brunt; Shirley V Wang; Richard J Willke
Journal:  Value Health       Date:  2020-09       Impact factor: 5.725

Review 7.  Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses.

Authors:  Miguel A Hernán; Brian C Sauer; Sonia Hernández-Díaz; Robert Platt; Ian Shrier
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8.  Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease.

Authors:  Miguel A Hernán; Alvaro Alonso; Roger Logan; Francine Grodstein; Karin B Michels; Walter C Willett; Joann E Manson; James M Robins
Journal:  Epidemiology       Date:  2008-11       Impact factor: 4.822

9.  Evaluating medication effects outside of clinical trials: new-user designs.

Authors:  Wayne A Ray
Journal:  Am J Epidemiol       Date:  2003-11-01       Impact factor: 4.897

10.  Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies V1.0.

Authors:  Shirley V Wang; Sebastian Schneeweiss; Marc L Berger; Jeffrey Brown; Frank de Vries; Ian Douglas; Joshua J Gagne; Rosa Gini; Olaf Klungel; C Daniel Mullins; Michael D Nguyen; Jeremy A Rassen; Liam Smeeth; Miriam Sturkenboom
Journal:  Pharmacoepidemiol Drug Saf       Date:  2017-09       Impact factor: 2.890

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  2 in total

1.  Use of Extrapolation in New Drug Approvals by the US Food and Drug Administration.

Authors:  Daniel Feldman; Jerry Avorn; Aaron S Kesselheim
Journal:  JAMA Netw Open       Date:  2022-04-01

2.  A Framework for Visualizing Study Designs and Data Observability in Electronic Health Record Data.

Authors:  Shirley V Wang; Sebastian Schneeweiss
Journal:  Clin Epidemiol       Date:  2022-04-29       Impact factor: 5.814

  2 in total

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