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A bivariate Bayesian dose-finding procedure applied to a seamless phase I/II trial in rheumatoid arthritis

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>11/2012
<mark>Journal</mark>Pharmaceutical Statistics
Number of pages9
Early online date25/09/12
<mark>Original language</mark>English


We describe a dose escalation procedure for a combined phase I/II clinical trial. The procedure is based on a Bayesian model for the joint distribution of the occurrence of a dose limiting event and of some indicator of efficacy (both considered binary variables) making no assumptions other than monotonicity. Thus the chances of each outcome are assumed to be nondecreasing in dose level. We applied the procedure to the design of a placebo-controlled, sequential trial in rheumatoid arthritis, in each stage of which patients were randomized between placebo and all dose levels that currently appeared safe and non-futile. Based on data from a pilot study, we constructed five different scenarios for the dose-response relationships under which we simulated the trial and assessed the performance of the procedure. The new design appears to have satisfactory operating characteristics, and can be adapted to the requirements of a range of trial situations.