Planning a Bayesian early-phase phase I/II study for human vaccines in HER2 carcinomas

Recent innovative statistical approaches for phase I/II clinical trials allow one to jointly model the toxicity and efficacy of a new treatment, taking into account the information gathered during the trial. Prior probabilities are then updated with interim data and thus predictive probabilities become more accurate as the trial progresses. In this study, prior distribution elicited from a physician's opinion on the available dose levels planned for a vaccination dose-finding trial, with human DNA in patients with HER2-positive tumours in terms of toxicity and therapeutic response is presented and discussed. A simulation study was conducted in order to quantify the impact of the choice of prior on study results, i.e. the recommended dose level at the end of the trial.