Ades A E, Sculpher Mark, Sutton Alex, Abrams Keith, Cooper Nicola, Welton Nicky, Lu Guobing
Medical Research Council Health Services Research Collaboration, University of Bristol, Bristol, England.
Pharmacoeconomics. 2006;24(1):1-19. doi: 10.2165/00019053-200624010-00001.
Recently, health systems internationally have begun to use cost-effectiveness research as formal inputs into decisions about which interventions and programmes should be funded from collective resources. This process has raised some important methodological questions for this area of research. This paper considers one set of issues related to the synthesis of effectiveness evidence for use in decision-analytic cost-effectiveness (CE) models, namely the need for the synthesis of all sources of available evidence, although these may not 'fit neatly' into a CE model. Commonly encountered problems include the absence of head-to-head trial evidence comparing all options under comparison, the presence of multiple endpoints from trials and different follow-up periods. Full evidence synthesis for CE analysis also needs to consider treatment effects between patient subpopulations and the use of nonrandomised evidence. Bayesian statistical methods represent a valuable set of analytical tools to utilise indirect evidence and can make a powerful contribution to the decision-analytic approach to CE analysis. This paper provides a worked example and a general overview of these methods with particular emphasis on their use in economic evaluation.
最近，国际卫生系统已开始将成本效益研究作为正式依据，用于决定哪些干预措施和项目应从集体资源中获得资金支持。这一过程给该研究领域带来了一些重要的方法学问题。本文探讨了与综合有效性证据以用于决策分析成本效益（CE）模型相关的一系列问题，即需要综合所有可用证据来源，尽管这些证据可能无法“完美适配”CE模型。常见问题包括缺乏比较所有对比选项的直接试验证据、试验存在多个终点以及不同的随访期。CE分析的全面证据综合还需要考虑患者亚组之间的治疗效果以及非随机证据的使用。贝叶斯统计方法是利用间接证据的一组有价值的分析工具，可为CE分析的决策分析方法做出重要贡献。本文提供了一个实例及这些方法的概述，特别强调了它们在经济评估中的应用。
