Reproducibility of real-world evidence studies using clinical practice data to inform regulatory and coverage decisions

Shirley V. Wang*, Sushama Kattinakere Sreedhara, Sebastian Schneeweiss, Jessica M. Franklin, Joshua J. Gagne, Krista F. Huybrechts, Elisabetta Patorno, Yinzhu Jin, Moa Lee, Mufaddal Mahesri, Ajinkya Pawar, Julie Barberio, Lily G. Bessette, Kristyn Chin, Nileesa Gautam, Adrian Santiago Ortiz, Ellen Sears, Kristina Stefanini, Mimi Zakarian, Sara DejeneJames R. Rogers, Gregory Brill, Joan Landon, Joyce Lii, Theodore Tsacogianis, Seanna Vine, Elizabeth M. Garry, Liza R. Gibbs, Monica Gierada, Danielle L. Isaman, Emma Payne, Sarah Alwardt, Peter Arlett, Dorothee B. Bartels, Andrew Bate, Jesse Berlin, Alison Bourke, Brian Bradbury, Jeffrey Brown, Karen Burnett, Troyen Brennan, K. Arnold Chan, Nam Kyong Choi, Frank de Vries, Hans Georg Eichler, Kristian B. Filion, Lisa Freeman, Jesper Hallas, Laura Happe, Sean Hennessy, REPEAT Initiative

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Studies that generate real-world evidence on the effects of medical products through analysis of digital data collected in clinical practice provide key insights for regulators, payers, and other healthcare decision-makers. Ensuring reproducibility of such findings is fundamental to effective evidence-based decision-making. We reproduce results for 150 studies published in peer-reviewed journals using the same healthcare databases as original investigators and evaluate the completeness of reporting for 250. Original and reproduction effect sizes were positively correlated (Pearson’s correlation = 0.85), a strong relationship with some room for improvement. The median and interquartile range for the relative magnitude of effect (e.g., hazard ratiooriginal/hazard ratioreproduction) is 1.0 [0.9, 1.1], range [0.3, 2.1]. While the majority of results are closely reproduced, a subset are not. The latter can be explained by incomplete reporting and updated data. Greater methodological transparency aligned with new guidance may further improve reproducibility and validity assessment, thus facilitating evidence-based decision-making. Study registration number: EUPAS19636.
Original languageEnglish
Article number5126
Number of pages11
JournalNature Communications
Volume13
Issue number1
DOIs
Publication statusPublished - 31 Aug 2022

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