Investigating dose finding methods and different priors in Bayesian continual reassessment method


  • Tuba Koc Cankiri Karatekin University Department of Statistics
  • Mehmet Ali Cengiz Ondokuz Mayis University


Clinical trial, maximum tolerated dose, Bayesian inference, prior selection


Clinical trials are studies that explore whether a treatment, drug or device is safe and effective for humans. These studies can show which medial method work best for certain diseases. A well-designed and a properly-analyzed clinical trial is a powerful tool for the development of new drugs. The first step in drug discovery (phase I) is very important to determine maximum tolerated dose (MTD).

In the first part of the study, the classical 3+3 design, Continual Reassessment Method (CRM), and Bayesian Continual Reassessment Method (B-CRM) are compared in terms of selection probability of MTD and the number of treated patients. Among these designs, the B-CRM produced better results than the 3+3 and the CRM. In the second part of the study, we considered different model structures and priors in the B-CRM design. We evaluated power model, hyperbolic tanget model and logit model for gamma, uniform and lognormal prior. We found that if power or hyperbolic tangent model structure and uniform prior was selected, the MTD selection rates was the highest in B-CRM.

Author Biographies

Tuba Koc, Cankiri Karatekin University Department of Statistics

Science of faculty department of statistics

Mehmet Ali Cengiz, Ondokuz Mayis University

Statistics Department