Abstract:
|
Traditionally, clinical trials have primarily been concerned with comparing treatments on an entire population to provide the most reliable data about the effects of treatments. But due to the need to streamline drug development, in areas of high unmet medical need, subgroup analysis has started to play a different role. For example, the FDA released a draft Guidance on antibacterial therapies for unmet medical need and notes the possibility to use innovative design strategies including Bayesian modeling approaches for assessing subgroup-specific treatment effects in trials involving multi-site infections instead of starting with multiple clinical trials in different sites. Given this paradigm, I will talk about accounting for exchangeability and/or non-exchangeability in subgroup analysis. I will also explore models for estimating effects at each of these subgroups using varying assumptions of exchangeability and/or non-exchangeability and evaluate bias in the estimates.
|
ASA Meetings Department
732 North Washington Street, Alexandria, VA 22314
(703) 684-1221 • meetings@amstat.org
Copyright © American Statistical Association.