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A New Bayesian Dose-Finding Design for Drug Combination Trials

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Version 2 2018-01-30, 21:27
Version 1 2017-10-30, 20:38
journal contribution
posted on 2018-01-30, 21:27 authored by Rongji Mu, Jin Xu

We consider the problem of finding maximum tolerated dose with targeted dose-limiting toxicity rate in drug combination trials. We propose a novel Bayesian adaptive design, which features adaptive local modeling and weighted learning along the search path. The method is robust in the sense that neither prespecifications of marginal toxicity probabilities nor subjective priors for model parameters are required. Extensive simulation studies show that the proposed method is comparable to some leading methods in terms of correct selection and superior to them when the priors are misspecified. Moreover, the proposed model can be extended to the case of trials with more than two drugs. Supplementary materials for this article are available online.

Funding

The research is supported by National Natural Science Foundation of China (grant 11271134) and by Ministry of Education of China (the 111 Project: B14019).

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