Clinical trials in critical care: can a Bayesian approach enhance clinical and scientific decision making?
Yarnell, Christopher J Abrams, Darryl Baldwin, Matthew R Brodie, Daniel Fan, Eddy Ferguson, Niall D Hua, May Madahar, Purnema McAuley, Danny F Munshi, Laveena
Yarnell, Christopher J
Abrams, Darryl
Baldwin, Matthew R
Brodie, Daniel
Fan, Eddy
Ferguson, Niall D
Hua, May
Madahar, Purnema
McAuley, Danny F
Munshi, Laveena
Abstract
Recent Bayesian reanalyses of prominent trials in critical illness have generated controversy by contradicting the initial conclusions based on conventional frequentist analyses. Many clinicians might be sceptical that Bayesian analysis, a philosophical and statistical approach that combines prior beliefs with data to generate probabilities, provides more useful information about clinical trials than the frequentist approach. In this Personal View, we introduce clinicians to the rationale, process, and interpretation of Bayesian analysis through a systematic review and reanalysis of interventional trials in critical illness. In the majority of cases, Bayesian and frequentist analyses agreed. In the remainder, Bayesian analysis identified interventions where benefit was probable despite the absence of statistical significance, where interpretation depended substantially on choice of prior distribution, and where benefit was improbable despite statistical significance. Bayesian analysis in critical care medicine can help to distinguish harm from uncertainty and establish the probability of clinically important benefit for clinicians, policy makers, and patients.
MIDER Authors
Affiliations
University of Toronto; Mount Sinai Hospital Toronto; Columbia University; New York-Presbyterian Hospital; University Health Network and Sinai Health System; Toronto General Hospital Research Institute; Mailman School of Public Health; Queen's University Belfast; Belfast Health and Social Care Trust; University Hospitals Birmingham NHS Foundation Trust; University of Warwick; Sunnybrook Health Sciences Centre
Date
2020-11-20
Type
Article
Collections
Citation
Yarnell CJ, Abrams D, Baldwin MR, Brodie D, Fan E, Ferguson ND, Hua M, Madahar P, McAuley DF, Munshi L, Perkins GD, Rubenfeld G, Slutsky AS, Wunsch H, Fowler RA, Tomlinson G, Beitler JR, Goligher EC. Clinical trials in critical care: can a Bayesian approach enhance clinical and scientific decision making? Lancet Respir Med. 2021 Feb;9(2):207-216. doi: 10.1016/S2213-2600(20)30471-9. Epub 2020 Nov 20.