Ohlssen David, Price Karen L, Xia H Amy, Hong Hwanhee, Kerman Jouni, Fu Haoda, Quartey George, Heilmann Cory R, Ma Haijun, Carlin Bradley P
Novartis Pharmaceuticals Corporation, East Hanover, NJ, 07936, USA.
Pharm Stat. 2014 Jan-Feb;13(1):55-70. doi: 10.1002/pst.1592. Epub 2013 Aug 30.
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.
药物信息协会贝叶斯科学工作组（BSWG）成立于2011年，其愿景是确保贝叶斯方法得到充分理解，并广泛应用于设计、分析以及整个医疗产品开发过程，同时改善行业、监管和经济决策。该小组由来自学术界、行业和监管部门的人员组成，其使命是促进贝叶斯方法的恰当使用并推动其发展。在本文中，BSWG的安全子团队探讨了贝叶斯方法在药物安全性荟萃分析和网络荟萃分析中的应用。文中给出了此类分析的实施和报告指南。我们还讨论了不同的结构模型假设，并对先验规范进行了探讨。通过一个涉及非甾体抗炎药心血管安全性的网络荟萃分析的案例研究对这项工作进行了说明。
