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Multivariate Continuous Bayesian Clinical Trials in R Pdf

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Bayesian Design for Pediatric Clinical Trials with Binary Endpoints When Borrowing Historical Information of Treatment Effect

Therapeutic Innovation & Regulatory Science volume 55,pages 360–369 (2021)Cite this article

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Abstract

The efficacy evaluation in pediatric population is an important component of drug development and is generally required by the regulatory agencies. It is often challenging to enroll pediatric subjects for a large trial especially when the incidence rate is low in certain disease areas. Bayesian framework can provide analytic avenues to effectively utilize historical information of the treatment effect and help make pediatric trials more efficient by reducing the sample size when there is evidence to suggest similarity of the treatment responses between the populations. Schoenfeld et al. (Clin Trials 6(4):297–304, 2009) proposed a Bayesian hierarchical model for efficacy extrapolation for continuous endpoints, which connects a single historical trial and the current trial by a variance parameter in the prior distribution. In this manuscript, we extend the existing model to borrow strength from multiple historical trials under the same assumptions and develop a quantitative method to borrow historical information more efficiently. Furthermore, we extend Schoenfeld's method based on continuous endpoints to binary endpoints with a hierarchical binomial model to extrapolate efficacy. Sensitivity analyses for the underlying assumptions are discussed with simulations and the methods are illustrated with a real case study, along with some practical considerations about how to choose the prior distribution.

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Author notes

  1. Man Jin PhD

    Present address: AbbVie Inc., 1 N Waukegan Rd, North Chicago, IL, 60064, USA

Authors and Affiliations

  1. Biostatistics and Research Decision Sciences, MRL, Merck & Co., Inc., Rahway, NJ, 07065, USA

    Man Jin PhD, Qing Li & Amarjot Kaur

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Correspondence to Man Jin PhD.

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Jin, M., Li, Q. & Kaur, A. Bayesian Design for Pediatric Clinical Trials with Binary Endpoints When Borrowing Historical Information of Treatment Effect. Ther Innov Regul Sci 55, 360–369 (2021). https://doi.org/10.1007/s43441-020-00220-5

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  • DOI : https://doi.org/10.1007/s43441-020-00220-5

Keywords

  • Sample size calculations
  • Bayesian framework
  • Prior distributions
  • Hierarchical model
  • Pediatric clinical trials

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