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Dose‐Finding with Two Agents in Phase I Oncology Trials
Author(s) -
Thall Peter F.,
Millikan Randall E.,
Mueller Peter,
Lee SangJoon
Publication year - 2003
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/1541-0420.00058
Subject(s) - prior probability , bayesian probability , cyclophosphamide , computer science , gemcitabine , bayes' theorem , clinical trial , medicine , oncology , mathematics , artificial intelligence , chemotherapy
Summary . We propose an adaptive two‐stage Bayesian design for finding one or more acceptable dose combinations of two cytotoxic agents used together in a Phase I clinical trial. The method requires that each of the two agents has been studied previously as a single agent, which is almost invariably the case in practice. A parametric model is assumed for the probability of toxicity as a function of the two doses. Informative priors for parameters characterizing the single‐agent toxicity probability curves are either elicited from the physician(s) planning the trial or obtained from historical data, and vague priors are assumed for parameters characterizing two‐agent interactions. A method for eliciting the single‐agent parameter priors is described. The design is applied to a trial of gemcitabine and cyclophosphamide, and a simulation study is presented.