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Title: Subgroup analysis with time to event outcomes Authors:  Peter Mueller - UT Austin (United States) [presenting]
Satoshi Morita - Kyoto University Graduate School of Medicine (Japan)
Hiroyasu Abe - Kyoto University (Japan)
Abstract: A utility-based Bayesian approach to population finding and subgroup analysis is discussed. The approach casts the population finding process as a formal decision problem together with a flexible probability model using a flexible model, such as random forests or other non-parametric Bayesian models, to fit the data. In contrast, the decision is constrained to be parsimonious and interpretable. We define a utility function that addresses the competing aims of the desired report. We illustrate the approach with a joint time-to-event and toxicity outcome for subgroup analysis, and with a time-to-event outcome in the context of an umbrella trial master protocol.