Bayesian Meta-Analysis of Health State Utility Values: A Tutorial with a Practical Application in Heart Failure.

IF 4.4 3区 医学 Q1 ECONOMICS PharmacoEconomics Pub Date : 2024-07-01 Epub Date: 2024-05-20 DOI:10.1007/s40273-024-01387-7
Joseph Alvin Ramos Santos, Robert Grant, Gian Luca Di Tanna
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Abstract

Researchers incorporate health state utility values as inputs to inform economic models. However, for a particular health state or condition, multiple utility values derived from different studies typically exist and a single study is often insufficient to represent the best available source of utility needed to inform policy decisions. The purpose of this paper is to provide an introductory guidance for conducting Bayesian meta-analysis of health state utility values to generate a single parameter input for economic evaluation, using R. The tutorial is illustrated using data from a systematic review of health state utilities of patients with heart failure, with 21 studies that reported utilities measured using the EuroQol-5D (EQ-5D). Explanations, key considerations and suggested readings are provided for each step of the tutorial, adhering to a clear workflow for conducting Bayesian meta-analysis: (1) setting-up the data; (2) employing methods to impute missing standard deviations; (3) defining the priors; (4) fitting the model; (5) diagnosing model convergence; (6) interpreting the results; and (7) performing sensitivity analyses. The posterior distributions for the pooled effect size (i.e. mean health state utility) and between-study heterogeneity are discussed and interpreted in light of the data, priors and models used. We hope that this tutorial will foster interest in Bayesian methods and their applications in the meta-analysis of utilities.

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健康状态效用值的贝叶斯元分析:心力衰竭实际应用教程》。
研究人员将健康状态效用值作为经济模型的输入信息。然而,对于一种特定的健康状况或病症,通常存在来自不同研究的多个效用值,而单一研究往往不足以代表政策决策所需的最佳效用来源。本文旨在为使用 R 对健康状态效用值进行贝叶斯荟萃分析以生成用于经济评估的单一参数输入提供入门指导。本教程将使用心力衰竭患者健康状态效用的系统综述数据进行说明,其中有 21 项研究报告了使用 EuroQol-5D (EQ-5D) 测量的效用。教程的每个步骤都提供了解释、关键注意事项和建议阅读内容,并遵循了进行贝叶斯荟萃分析的清晰工作流程:(1) 设置数据;(2) 采用方法补偿缺失的标准差;(3) 定义先验;(4) 拟合模型;(5) 诊断模型收敛;(6) 解释结果;(7) 进行敏感性分析。根据所使用的数据、先验和模型,讨论并解释汇总效应大小(即平均健康状况效用)和研究间异质性的后验分布。我们希望本教程能提高人们对贝叶斯方法及其在效用荟萃分析中应用的兴趣。
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来源期刊
PharmacoEconomics
PharmacoEconomics 医学-药学
CiteScore
8.10
自引率
9.10%
发文量
85
审稿时长
6-12 weeks
期刊介绍: PharmacoEconomics is the benchmark journal for peer-reviewed, authoritative and practical articles on the application of pharmacoeconomics and quality-of-life assessment to optimum drug therapy and health outcomes. An invaluable source of applied pharmacoeconomic original research and educational material for the healthcare decision maker. PharmacoEconomics is dedicated to the clear communication of complex pharmacoeconomic issues related to patient care and drug utilization. PharmacoEconomics offers a range of additional features designed to increase the visibility, readership and educational value of the journal’s content. Each article is accompanied by a Key Points summary, giving a time-efficient overview of the content to a wide readership. Articles may be accompanied by plain language summaries to assist readers who have some knowledge of, but not in-depth expertise in, the area to understand the scientific content and overall implications of the article.
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