Literature DB >> 21830924

Bayesian approaches in medical device clinical trials: a discussion with examples in the regulatory setting.

Pablo Bonangelino1, Telba Irony, Shengde Liang, Xuefeng Li, Vandana Mukhi, Shiling Ruan, Yunling Xu, Xiting Yang, Chenguang Wang.   

Abstract

Challenging statistical issues often arise in the design and analysis of clinical trials to assess safety and effectiveness of medical devices in the regulatory setting. The use of Bayesian methods in the design and analysis of medical device clinical trials has been increasing significantly in the past decade, not only due to the availability of prior information, but mainly due to the appealing nature of Bayesian clinical trial designs. The Center for Devices and Radiological Health at the Food and Drug Administration (FDA) has gained extensive experience with the use of Bayesian statistical methods and has identified some important issues that need further exploration. In this article, we discuss several topics relating to the use of Bayesian statistical methods in medical device trials, based on our experience and real applications. We illustrate the benefits and challenges of Bayesian approaches when incorporating prior information to evaluate the effectiveness and safety of a medical device. We further present an example of a Bayesian adaptive clinical trial and compare it to a traditional frequentist design. Finally, we discuss the use of Bayesian hierarchical models for multiregional trials and highlight the advantages of the Bayesian approach when specifying clinically relevant study hypotheses.

Mesh:

Year:  2011        PMID: 21830924     DOI: 10.1080/10543406.2011.589650

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  3 in total

1.  Building efficient comparative effectiveness trials through adaptive designs, utility functions, and accrual rate optimization: finding the sweet spot.

Authors:  Byron J Gajewski; Scott M Berry; Melanie Quintana; Mamatha Pasnoor; Mazen Dimachkie; Laura Herbelin; Richard Barohn
Journal:  Stat Med       Date:  2015-01-07       Impact factor: 2.373

2.  Randomized, Multicenter Trial of ARTSS-2 (Argatroban With Recombinant Tissue Plasminogen Activator for Acute Stroke).

Authors:  Andrew D Barreto; Gary A Ford; Loren Shen; Claudia Pedroza; Jon Tyson; Chunyan Cai; Mohammad H Rahbar; James C Grotta
Journal:  Stroke       Date:  2017-05-15       Impact factor: 7.914

3.  A Bayesian comparative effectiveness trial in action: developing a platform for multisite study adaptive randomization.

Authors:  Alexandra R Brown; Byron J Gajewski; Lauren S Aaronson; Dinesh Pal Mudaranthakam; Suzanne L Hunt; Scott M Berry; Melanie Quintana; Mamatha Pasnoor; Mazen M Dimachkie; Omar Jawdat; Laura Herbelin; Richard J Barohn
Journal:  Trials       Date:  2016-08-31       Impact factor: 2.279

  3 in total

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