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Risk-group-specific dose finding based on an average toxicity score. (English) Zbl 1192.62218
Summary: We propose a Bayesian dose-finding design that accounts for two important factors, the severity of toxicity and heterogeneity in patients’ susceptibility to toxicity. We consider toxicity outcomes with various levels of severity and define appropriate scores for these severity levels. We then use a multinomial-likelihood function and a Dirichlet prior to model the probabilities of these toxicity scores at each dose, and characterize the overall toxicity using an average toxicity score (ATS) parameter. To address the issue of heterogeneity in patients’ susceptibility to toxicity, we categorize patients into different risk groups based on their susceptibility. A Bayesian isotonic transformation is applied to induce an order-restricted posterior inference on the ATS. We demonstrate the performance of the proposed dose-finding design using simulations based on a clinical trial in multiple myeloma.

MSC:
62P10 Applications of statistics to biology and medical sciences; meta analysis
62F15 Bayesian inference
92C50 Medical applications (general)
65C60 Computational problems in statistics (MSC2010)
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