Literature DB >> 20800443

Bayesian statistical method was underused despite its advantages in the assessment of implantable medical devices.

Leslie Pibouleau1, Sylvie Chevret.   

Abstract

OBJECTIVE: We sought to review the use of Bayesian methods in the evaluation of the effectiveness of implantable medical devices (IMDs) to identify which areas of research need to be further investigated to improve IMD assessment. STUDY DESIGN AND
SETTING: Relevant studies were identified by searching PubMed and the Food and Drug Administration Web site. Data were extracted independently by the two authors. The quality of Bayesian analysis reporting was summarized using the ROBUST (Reporting Of Bayes Used in clinical STudies) checklist.
RESULTS: Seventeen studies met the inclusion criteria; five published meta-analyses and 12 clinical studies were reported as FDA summaries of safety and effectiveness. Reporting of data was of high quality in meta-analyses, whereas it was of poor quality in clinical studies. Bayesian methods were used in meta-analyses to model study heterogeneity. In clinical studies, the objectives of the Bayesian analyses were mostly to address the question of equivalence and to use surrogate outcome predictors. Prior information, when reported, was less informative. Clinical data external to the trial itself and expert opinions were never used to elicit prior information.
CONCLUSION: Our review highlighted the underuse of Bayesian methods in IMD assessment. The major challenge is to provide to clinical researchers a framework that helps them use external evidence to elicit prior distributions. Copyright Â
© 2011 Elsevier Inc. All rights reserved.

Mesh:

Year:  2010        PMID: 20800443     DOI: 10.1016/j.jclinepi.2010.03.018

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  4 in total

1.  Improving clinical trials using Bayesian adaptive designs: a breast cancer example.

Authors:  Wei Hong; Sue-Anne McLachlan; Melissa Moore; Robert K Mahar
Journal:  BMC Med Res Methodol       Date:  2022-05-04       Impact factor: 4.612

Review 2.  Bayesian Analysis Reporting Guidelines.

Authors:  John K Kruschke
Journal:  Nat Hum Behav       Date:  2021-08-16

Review 3.  Methodological choices for the clinical development of medical devices.

Authors:  Alain Bernard; Michel Vaneau; Isabelle Fournel; Hubert Galmiche; Patrice Nony; Jean Michel Dubernard
Journal:  Med Devices (Auckl)       Date:  2014-09-23

4.  Advantages of Bayesian monitoring methods in deciding whether and when to stop a clinical trial: an example of a neonatal cooling trial.

Authors:  Claudia Pedroza; Jon E Tyson; Abhik Das; Abbot Laptook; Edward F Bell; Seetha Shankaran
Journal:  Trials       Date:  2016-07-22       Impact factor: 2.279

  4 in total

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