BAGS: A Bayesian Adaptive Group Sequential Trial Design with Subgroup-Specific Survival Comparisons

Ruitao Lin, Peter F. Thall & Ying Yuan
A Bayesian group sequential design is proposed that performs survival comparisons within patient subgroups in randomized trials where treatment–subgroup interactions may be present. A latent subgroup membership variable is assumed to allow the design to adaptively combine homogeneous subgroups, or split heterogeneous subgroups, to improve the procedure’s within-subgroup power. If a baseline covariate related to survival is available, the design may incorporate this information to improve subgroup identification while basing the comparative test on the...
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