Comparer des méthodes

	Essai clinique randomisé adaptatif	Essai clinique randomisé bayésien
Domaine	Épidémiologie	Épidémiologie
Famille	Process / pipeline	Process / pipeline
Année d'origine	Late 1990s–2000s (widespread adoption post-2010)	1980s–2000s (formal methodology consolidated ~2004–2006)
Auteur d'origine	Donald Berry and colleagues; formalized by FDA guidance in 2010 and 2019	Donald A. Berry and David J. Spiegelhalter (applied Bayesian inference formally to RCT design)
Type	Experimental clinical trial design	Randomized experimental study with Bayesian inference
Source fondatrice	Berry, D. A. (2006). Bayesian clinical trials. Nature Reviews Drug Discovery, 5(1), 27–36.	Spiegelhalter, D. J., Abrams, K. R., & Myles, J. P. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation. Wiley. ISBN: 978-0471499756
Alias	adaptive RCT, adaptive trial design, response-adaptive randomization trial, adaptive clinical trial	Bayesian RCT, Bayesian adaptive trial, Bayesian clinical trial design, BRCT
Apparentées	6	5
Résumé	An adaptive randomized clinical trial (adaptive RCT) is a prospective experimental study that uses pre-specified rules to modify one or more trial aspects — such as sample size, allocation ratios, or treatment arms — based on accumulating data collected during the trial itself, while maintaining statistical validity and integrity of the study.	A Bayesian randomized clinical trial (Bayesian RCT) combines the rigour of random treatment allocation with Bayesian statistical inference, allowing researchers to incorporate prior evidence and update beliefs continuously as trial data accumulate. Unlike the classical frequentist RCT, it yields direct probability statements about treatment effects and supports pre-specified adaptive stopping rules based on posterior probabilities.