Multiparameter evidence synthesis in epidemiology and medical decision-making
Multiparameter evidence synthesis in epidemiology and medical decision-making
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DOI：
10.1258/jhsrp.2008.008020
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发表时间：
2008-10-01
影响因子：
2.4
通讯作者：
Lu, Guobing
中科院分区：
文献类型：
--
作者：
Ades, A. E.;Welton, Nicky J.;Lu, Guobing
元分析已经建立了很多年，但很大程度上局限于收集成对对比的证据。更广泛的合成形式也被描述，显然在不同的领域重新发明，每次采用不同的计算方法。贝叶斯估计联合后验参数分布并同时从中抽样进行决策分析的潜在价值也得到了赞赏。然而，应用程序的数量相对较少，有时是程式化的，并且主要呈现给统计方法的受众。因此，流行病学和卫生技术评估中多参数证据综合的潜力在很大程度上仍未得到承认。以WinBUGS的形式出现的贝叶斯马尔可夫链蒙特卡罗的灵活软件使这些早期的工作更广泛地可用。研究人员现在可以在现实的复杂水平上进行合成。布里斯托尔项目不仅对如何综合不同证据结构的文献做出了贡献，而且还对如何检查多个信息来源的一致性以及如何使用所得模型来优先考虑未来的研究做出了贡献。卫生服务研究与政策杂志Vol 13供应3,2008:12-22 (C)皇家医学学会出版社有限公司2008
Meta-analysis has been well-established for many years, but has been largely confined to pooling evidence on pair-wise contrasts. Broader forms of synthesis have also been described, apparently re-invented in disparate fields, each time taking different computational approaches. The potential value of Bayesian estimation of a joint posterior parameter distribution and simultaneously sampling from it for decision analysis has also been appreciated. However, applications have been relatively few in number, sometimes stylized, and presented mainly to a statistical methods audience. As a result, the potential for multiparameter evidence synthesis in both epidemiology and health technology assessment has remained largely unrecognized. The advent of flexible software for Bayesian Markov chain Monte Carlo in the shape of WinBUGS has the made these earlier strands of work more widely available. Researchers can now carry out synthesis at a realistic level of complexity. The Bristol programme has not only contributed to a growing body of literature on how to synthesize different evidence structures, but also on how to check the consistency of multiple information sources and how to use the resulting models to prioritize future research. Journal of Health Services Research & Policy Vol 13 Suppl 3, 2008: 12-22 (C) The Royal Society of Medicine Press Ltd 2008