Empirical bayes approach for dynamic bayesian borrowing for clinical trials in rare diseases

Application of Bayesian methods is one the tools that can be used to face the multiple challenges that are met when clinical trials must be conducted in rare diseases. We propose in this work to use a dynamic Bayesian borrowing approach, based on a mixture prior, to complement the control arm of a c...

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Bibliographic Details
Published in:Journal of pharmacokinetics and pharmacodynamics 2023-12, Vol.50 (6), p.495-499
Main Author: Sebastien, Bernard
Format: Article
Language:English
Subjects:
Bayes Theorem
Bayesian analysis
Biochemistry
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Clinical trials
Computer Simulation
Humans
Normal distribution
Original Paper
Pharmacodynamics
Pharmacokinetics
Pharmacology/Toxicology
Pharmacy
Rare diseases
Rare Diseases - drug therapy
Research Design
Sample Size
Veterinary Medicine/Veterinary Science
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Summary:Application of Bayesian methods is one the tools that can be used to face the multiple challenges that are met when clinical trials must be conducted in rare diseases. We propose in this work to use a dynamic Bayesian borrowing approach, based on a mixture prior, to complement the control arm of a comparative trial and estimate the mixture parameter by an Empirical Bayes approach. The method is compared, using simulations, with an approach based on a pre-specified (non-adaptive) informative prior. The simulation study shows that the proposed method exhibits similar power as the non-adaptive prior and drastically reduce type I error in case of severe discrepancy between the informative prior and the study control arm data. In case of limited discrepancy between the informative prior and the study control arm data, then our proposed adaptive prior does not reduce the inflation of the type I error.
ISSN:1567-567X
1573-8744
DOI:10.1007/s10928-023-09860-0