Bayesian Sequential Design for Identifying and Ranking Effective Patient Subgroups in Precision Medicine in the Case of Counting Outcome Data with Inflated Zeros

Bayesian Sequential Design for Identifying and Ranking Effective Patient Subgroups in Precision Medicine in the Case of Counting Outcome Data with Inflated Zeros

Precision medicine is revolutionizing health care, particularly by addressing patient variability due to different biological profiles. As traditional treatments may not always be appropriate for certain patient subsets, the rise of biomarker-stratified clinical trials has driven the need for innova...

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Bibliographic Details
Main Authors: Valentin Vinnat, Djillali Annane, Sylvie Chevret
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Journal of Personalized Medicine
Subjects:
personalized medicine
biomarkers
Bayesian inference
identification of subset
Online Access:https://www.mdpi.com/2075-4426/13/11/1560

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