2021/03/10 by Meizi Liu, Yuan Ji, Liu, Meizi +3
Decision Sciences · Economics, Econometrics and Finance · Mathematics · #FOS: Computer and information sciences #Health Systems, Economic Evaluations, Quality of Life #Methodology (stat.ME) #Optimal Experimental Design Methods #Statistical Methods in Clinical Trials
paper · pdf · doi:10.48550/arxiv.2103.06368
openalex publication_date 2021/03/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We consider a Bayesian framework based on "probability of decision" for dose-finding trial designs. The proposed PoD-BIN design evaluates the posterior predictive probabilities of up-and-down decisions. In PoD-BIN, multiple grades of toxicity, categorized as the mild toxicity (MT) and dose-limiting toxicity (DLT), are modeled simultaneously, and the primary outcome of interests is time-to-toxicity for both MT and DLT. This allows the possibility of enrolling new patients when previously enrolled patients are still being followed for toxicity, thus potentially shortening trial length. The Bayesian decision rules in PoD-BIN utilize the probability of decisions to balance the need to speed up the trial and the risk of exposing patients to overly toxic doses. We demonstrate via numerical examples the resulting balance of speed and safety of PoD-BIN and compare to existing designs.