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Activity Number: 16
Type: Topic Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #319873
Title: A Decision-Theoretic Phase I-II Design for Ordinal Outcomes in Two Cycles
Author(s): Juhee Lee* and Peter F. Thall and Peter Mueller and Yuan Ji
Companies: University of California at Santa Cruz and MD Anderson Cancer Center and The University of Texas at Austin and The University of Chicago
Keywords: Adaptive Design ; Bayesian Design ; Decision Theory ; Dynamic Treatment Regime ; Phase I-II Clinical Trial ; Latent Probit Model

This work is motivated by a phase I-II clinical trial of a targeted agent for advanced solid tumors. We study a stylized version of this trial with the goal to determine optimal actions in each of two cycles of therapy. A design is presented that generalizes the decision-theoretic two-cycle design of Lee and others (2015) to accommodate ordinal outcomes. Backward induction is used to jointly optimize the actions taken for each patient in each of the two cycles, with the second action accounting for the patient's cycle 1 dose and outcomes. A simulation study shows that simpler designs obtained by dichotomizing the ordinal outcomes either perform very similarly to the proposed design, or have much worse performance in some scenarios. We also compare the proposed design to the simpler approaches of optimizing the doses in each cycle separately, or ignoring the distinction between cycles 1 and 2.

Authors who are presenting talks have a * after their name.

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