Abstract:
:Multipopulation tailoring trials provide a trial design option that supports the realization of tailored therapeutics or personalized medicine. Several recent publications have focused on statistical and clinical considerations that arise in these trials that are designed to study the overall treatment effect in a population of interest as well as one or more prospectively defined subpopulations. Millen et al. (2012) introduced the influence and interaction conditions as part of a general framework to facilitate decision making in multipopulation trials. This article provides Bayesian methods for assessing the influence and interaction conditions. The methods introduced are illustrated using case studies based on clinical trials with biomarker-driven designs.
journal_name
J Biopharm Statjournal_title
Journal of biopharmaceutical statisticsauthors
Millen BA,Dmitrienko A,Song Gdoi
10.1080/10543406.2013.856025subject
Has Abstractpub_date
2014-01-01 00:00:00pages
94-109issue
1eissn
1054-3406issn
1520-5711journal_volume
24pub_type
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