Compara mètodes

	Assaig Clínic Bayesiana de Fase III	Prova clínica aleatòria bayesiana
Camp	Epidemiologia	Epidemiologia
Família	Process / pipeline	Process / pipeline
Any d'origen	1990s–2000s (widespread application)	1980s–2000s (formal methodology consolidated ~2004–2006)
Autor original	Donald A. Berry; David J. Spiegelhalter (formalization in clinical context)	Donald A. Berry and David J. Spiegelhalter (applied Bayesian inference formally to RCT design)
Tipus	Confirmatory randomized controlled trial with Bayesian inference	Randomized experimental study with Bayesian inference
Font seminal	Spiegelhalter, D. J., Abrams, K. R., & Myles, J. P. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation. Wiley. ISBN: 978-0471499756	Spiegelhalter, D. J., Abrams, K. R., & Myles, J. P. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation. Wiley. ISBN: 978-0471499756
Àlies	Bayesian confirmatory trial, Bayesian RCT Phase III, Bayesian pivotal trial, BayesCT	Bayesian RCT, Bayesian adaptive trial, Bayesian clinical trial design, BRCT
Relacionats	5	5
Resum	A Bayesian Phase III clinical trial is a large-scale, confirmatory randomized controlled trial that uses Bayesian statistical inference rather than conventional frequentist hypothesis testing to evaluate whether an experimental treatment meets pre-defined efficacy and safety thresholds. By combining prior evidence with accumulating trial data, it quantifies the probability that the treatment effect exceeds a clinically meaningful threshold, enabling more transparent decision-making under uncertainty.	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.