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Phase I dose-finding studies aim at identifying the maximal tolerated dose(MTD). It is not uncommon that several dose-finding studies are conducted,although often with some variation in the administration mode or dose panel.For instance, sorafenib (BAY 43-900) was used as monotherapy in at least 29phase I trials according to a recent search in clinicaltrials.gov. Since thetoxicity may not be directly related to the specific indication, synthesizingthe information from several studies might be worthwhile. However, this israrely done in practice and only a fixed-effect meta-analysis framework wasproposed to date. We developed a Bayesian random-effects meta-analysismethodology to pool several phase I trials and suggest the MTD. A curve freehierarchical model on the logistic scale with random effects, accounting forbetween-trial heterogeneity, is used to model the probability of toxicityacross the investigated doses. An Ornstein-Uhlenbeck Gaussian process isadopted for the random effects structure. Prior distributions for the curvefree model are based on a latent Gamma process. An extensive simulation studyshowed good performance of the proposed method also under model deviations.Sharing information between phase I studies can improve the precision of MTDselection, at least when the number of trials is reasonably large.

Random-effects meta-analysis of phase I dose-finding studies using stochastic process priors