Bayesian assessment of the influence and interaction conditions in multipopulation tailoring clinical trials.

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 Stat

authors

Millen BA,Dmitrienko A,Song G

doi

10.1080/10543406.2013.856025

subject

Has Abstract

pub_date

2014-01-01 00:00:00

pages

94-109

issue

1

eissn

1054-3406

issn

1520-5711

journal_volume

24

pub_type

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