Literature DB >> 24038897

Guidance on the implementation and reporting of a drug safety Bayesian network meta-analysis.

David Ohlssen1, Karen L Price, H Amy Xia, Hwanhee Hong, Jouni Kerman, Haoda Fu, George Quartey, Cory R Heilmann, Haijun Ma, Bradley P Carlin.   

Abstract

The Drug Information Association Bayesian Scientific Working Group (BSWG) was formed in 2011 with a vision to ensure that Bayesian methods are well understood and broadly utilized for design and analysis and throughout the medical product development process, and to improve industrial, regulatory, and economic decision making. The group, composed of individuals from academia, industry, and regulatory, has as its mission to facilitate the appropriate use and contribute to the progress of Bayesian methodology. In this paper, the safety sub-team of the BSWG explores the use of Bayesian methods when applied to drug safety meta-analysis and network meta-analysis. Guidance is presented on the conduct and reporting of such analyses. We also discuss different structural model assumptions and provide discussion on prior specification. The work is illustrated through a case study involving a network meta-analysis related to the cardiovascular safety of non-steroidal anti-inflammatory drugs.
Copyright © 2013 John Wiley & Sons, Ltd.

Keywords:  drug safety meta-analysis; mixed treatment comparisons; multiple outcomes; network meta-analysis; prior sensitivity; rare events; reporting Bayesian analysis

Mesh:

Substances:

Year:  2013        PMID: 24038897     DOI: 10.1002/pst.1592

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  8 in total

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Authors:  Francesco Bellanti; Rob C van Wijk; Meindert Danhof; Oscar Della Pasqua
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Authors:  Jing Zhang; Haoda Fu; Bradley P Carlin
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3.  Classifying information-sharing methods.

Authors:  Georgios F Nikolaidis; Beth Woods; Stephen Palmer; Marta O Soares
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4.  The quality of reporting methods and results in network meta-analyses: an overview of reviews and suggestions for improvement.

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Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

5.  Absolute or relative effects? Arm-based synthesis of trial data.

Authors:  S Dias; A E Ades
Journal:  Res Synth Methods       Date:  2015-10-13       Impact factor: 5.273

6.  Network meta-analysis: a technique to gather evidence from direct and indirect comparisons.

Authors:  Fernanda S Tonin; Inajara Rotta; Antonio M Mendes; Roberto Pontarolo
Journal:  Pharm Pract (Granada)       Date:  2017-03-15

7.  Why are not There More Bayesian Clinical Trials? Perceived Barriers and Educational Preferences Among Medical Researchers Involved in Drug Development.

Authors:  Jennifer Clark; Natalia Muhlemann; Fanni Natanegara; Andrew Hartley; Deborah Wenkert; Fei Wang; Frank E Harrell; Ross Bray
Journal:  Ther Innov Regul Sci       Date:  2022-01-03       Impact factor: 1.778

8.  Change Point Analysis for Detecting Vaccine Safety Signals.

Authors:  Seung-Hun You; Eun Jin Jang; Myo-Song Kim; Min-Taek Lee; Ye-Jin Kang; Jae-Eun Lee; Joo-Hyeon Eom; Sun-Young Jung
Journal:  Vaccines (Basel)       Date:  2021-03-02
  8 in total

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