Randomized discontinuation design
Seminar Room 1, Newton Institute
AbstractRandom discontinuation designs (RDD) proceed in two stages. During the first stage all patients are treated with the experimental therapy. A subgroup of patients who show evidence of response during the first stage are then randomized to control and treatment in a second stage. The intention of the design is to identify in the first stage a subpopulation of patients who could potentially benefit from the treatment, and carry out the comparison in the second stage only in that identified subgroup. Most applications are to oncology phase II trials for cytostatic agents. The design is characterized by several tuning parameters: the duration of the preliminary first stage, the number of patients in the trial, and the selection criterium for the second stage. We discuss an optimal choice of the tuning parameters based on a Bayesian decision theoretic framework. We define a probability model for putative cytostatic agents and specify a suitable utility function. A computational procedure to select the optimal decision is illustrated and the efficacy of the proposed approach is evaluated through a simulation study.
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