Subgroup analysis with time to event outcomes
We discuss a utility-based Bayesian approach to population finding and
subgroup analysis. 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
nonparametric 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.
Xu, Mueller, Tsimberidou, Berry
A Nonparametric Bayesian Basket Trial Design
Morita, and Mueller, P. (2017).
Bayesian Population Finding with Biomarkers in a RCT,
Biometrics, 73, 1355--1365.