Salīdzināt metodes

	Bayesiešu I Fāzes Klīniskais Pētījums	Beijiešu randomizēts klīniskais pētījums (Beijiešu RCT)
Nozare	Epidemioloģija	Epidemioloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1990	1980s–2000s (formal methodology consolidated ~2004–2006)
Autors	O'Quigley, Pepe & Fisher (Continual Reassessment Method)	Donald A. Berry and David J. Spiegelhalter (applied Bayesian inference formally to RCT design)
Tips	Adaptive Bayesian dose-finding design	Randomized experimental study with Bayesian inference
Pirmavots	O'Quigley, J., Pepe, M., & Fisher, L. (1990). Continual reassessment method: a practical design for phase 1 clinical trials in cancer. Biometrics, 46(1), 33–48.	Spiegelhalter, D. J., Abrams, K. R., & Myles, J. P. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation. Wiley. ISBN: 978-0471499756
Citi nosaukumi	Bayesian dose-finding trial, CRM trial, continual reassessment method trial, Bayesian dose-escalation study	Bayesian RCT, Bayesian adaptive trial, Bayesian clinical trial design, BRCT
Saistītās	5	5
Kopsavilkums	A Bayesian Phase I clinical trial uses prior probability models and sequential Bayes updating to find the maximum tolerated dose (MTD) of a new agent. Unlike the traditional 3+3 rule-based escalation, the Bayesian approach revises a dose-toxicity curve continuously as each patient's outcome is observed, allowing faster convergence to the true MTD while minimising exposure of patients to unsafe or subtherapeutic doses.	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.