Literature DB >> 23897858

Bayesian methods for design and analysis of safety trials.

Karen L Price1, H Amy Xia, Mani Lakshminarayanan, David Madigan, David Manner, John Scott, James D Stamey, Laura Thompson.   

Abstract

Safety assessment is essential throughout medical product development. There has been increased awareness of the importance of safety trials recently, in part due to recent US Food and Drug Administration guidance related to thorough assessment of cardiovascular risk in the treatment of type 2 diabetes. Bayesian methods provide great promise for improving the conduct of safety trials. In this paper, the safety subteam of the Drug Information Association Bayesian Scientific Working Group evaluates challenges associated with current methods for designing and analyzing safety trials and provides an overview of several suggested Bayesian opportunities that may increase efficiency of safety trials along with relevant case examples.
Copyright © 2013 John Wiley & Sons, Ltd.

Entities:  

Keywords:  Bayesian safety trials; hierarchical modeling; medical product safety; outcomes trials; postmarketing safety surveillance; rare events

Mesh:

Year:  2013        PMID: 23897858     DOI: 10.1002/pst.1586

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


  6 in total

1.  Causal assessment of pharmaceutical treatments: why standards of evidence should not be the same for benefits and harms?

Authors:  Barbara Osimani; Fiorenzo Mignini
Journal:  Drug Saf       Date:  2015-01       Impact factor: 5.606

2.  Efficient methods for signal detection from correlated adverse events in clinical trials.

Authors:  Guoqing Diao; Guanghan F Liu; Donglin Zeng; William Wang; Xianming Tan; Joseph F Heyse; Joseph G Ibrahim
Journal:  Biometrics       Date:  2019-03-29       Impact factor: 2.571

3.  New Insights in Computational Methods for Pharmacovigilance: E-Synthesis, a Bayesian Framework for Causal Assessment.

Authors:  Francesco De Pretis; Barbara Osimani
Journal:  Int J Environ Res Public Health       Date:  2019-06-24       Impact factor: 3.390

4.  E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance.

Authors:  Francesco De Pretis; Jürgen Landes; Barbara Osimani
Journal:  Front Pharmacol       Date:  2019-12-17       Impact factor: 5.810

5.  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

6.  BAHAMA: A Bayesian Hierarchical Model for the Detection of MedDRA®-Coded Adverse Events in Randomized Controlled Trials.

Authors:  Alma Revers; Michel H Hof; Aeilko H Zwinderman
Journal:  Drug Saf       Date:  2022-07-15       Impact factor: 5.228

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.