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Abstract:
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How subgroups of patients react heterogeneously to treatment plays an important role in precision medicine. Identifying the distinct subgroup and interpreting the pre-planned or post-hoc exploratory subgroup for the development of individualized treatment rules has been recommended and yet challenging. The risk of overlooking an important subgroup and making a decision based on a false discovery becomes very crucial. At the meantime, the limited sample size, multiplicity, lack of power, and information borrowing make the solutions not so easy. Bayesian framework provides the ability to incorporate priors with a degree of skepticism, form models with exchangeability or shrinkage, and allow synthesis of information from a variety of sources. During this round table discussion, we will start with presenting one of the recent proposals on applying novel Bayesian methodology to subgroup analysis, followed by an open floor discussion of the pros and cons of applying Bayesian approach to precision medicine.
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