Estimating EQ-5D-5L Quality-Adjusted Life-Year Weights From 12-item General Health Questionnaire Mental Health Data: A Large Sample Exploration of 4 Mapping Methods

IF 6.2 2区医学 Q1 ECONOMICS

Value in Health Pub Date : 2026-10-01 Epub Date: 2026-05-23 DOI:10.1016/j.jval.2026.05.001

Zhuxin Mao PhD, Joke Bilcke PhD, Koen Pepermans PhD, Philippe Beutels PhD

{"title":"Estimating EQ-5D-5L Quality-Adjusted Life-Year Weights From 12-item General Health Questionnaire Mental Health Data: A Large Sample Exploration of 4 Mapping Methods","authors":"Zhuxin Mao PhD, Joke Bilcke PhD, Koen Pepermans PhD, Philippe Beutels PhD","doi":"10.1016/j.jval.2026.05.001","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><div>Mental health measures are common in population surveys but cannot be directly used for utility-based economic evaluations. This study explores methods to estimate health utility associated with mental health.</div></div><div><h3>Methods</h3><div>We used data from 12 701 respondents participating in a Belgian population survey. We compared direct methods (linear and inflated beta regression) that could directly generate utility values, with indirect methods that first estimate EuroQol 5-Dimension 5-Level instrument (EQ-5D-5L) dimension responses using non-parametric or ordered logistic regression before generating utilities. Regression models used 12-item General Health Questionnaire (GHQ-12) responses as independent variables, controlling for sociodemographic factors. Model performance was assessed using root mean-squared error and mean absolute errors. We also calculated error statistics stratified by utility quantiles.</div></div><div><h3>Results</h3><div>For overall model performance, root mean-squared error values were identical for the linear and ordered logistic models (0.142), higher for the beta model (0.148), and highest for the nonparametric approach (0.155). Ordered logistic models performed the best in mean absolute errors, followed by linear, beta, and nonparametric approaches. Stratified analyses revealed heterogeneity in prediction accuracy across the utility quantiles. Models showed poorer performance in the lowest utility quantiles. Indirect mapping is conceptually more robust because it aligns with the dimensional structure of EQ-5D-5L and minimizes variations associated with the use of different value sets.</div></div><div><h3>Conclusion</h3><div>This study provides up-to-date algorithms for mapping mental health data to health utility. The mapping models can be applied using GHQ-12 responses and basic sociodemographic variables to generate utility values for use in economic evaluations in which utility data are not available.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"29 10","pages":"Pages 1888-1895"},"PeriodicalIF":6.2000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Value in Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1098301526024514","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/5/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}

引用次数: 0

Abstract

Objectives

Mental health measures are common in population surveys but cannot be directly used for utility-based economic evaluations. This study explores methods to estimate health utility associated with mental health.

Methods

We used data from 12 701 respondents participating in a Belgian population survey. We compared direct methods (linear and inflated beta regression) that could directly generate utility values, with indirect methods that first estimate EuroQol 5-Dimension 5-Level instrument (EQ-5D-5L) dimension responses using non-parametric or ordered logistic regression before generating utilities. Regression models used 12-item General Health Questionnaire (GHQ-12) responses as independent variables, controlling for sociodemographic factors. Model performance was assessed using root mean-squared error and mean absolute errors. We also calculated error statistics stratified by utility quantiles.

Results

For overall model performance, root mean-squared error values were identical for the linear and ordered logistic models (0.142), higher for the beta model (0.148), and highest for the nonparametric approach (0.155). Ordered logistic models performed the best in mean absolute errors, followed by linear, beta, and nonparametric approaches. Stratified analyses revealed heterogeneity in prediction accuracy across the utility quantiles. Models showed poorer performance in the lowest utility quantiles. Indirect mapping is conceptually more robust because it aligns with the dimensional structure of EQ-5D-5L and minimizes variations associated with the use of different value sets.

Conclusion

This study provides up-to-date algorithms for mapping mental health data to health utility. The mapping models can be applied using GHQ-12 responses and basic sociodemographic variables to generate utility values for use in economic evaluations in which utility data are not available.

查看原文本刊更多论文

从GHQ-12心理健康数据估计EQ-5D-5L质量调整生命年权重：四种制图方法的大样本探索

背景：心理健康测量在人口调查中很常见，但不能直接用于基于效用的经济评估。本研究探讨了评估心理健康相关的健康效用的方法。方法：我们使用了参与比利时人口调查的127,01名受访者的数据。我们比较了可以直接产生效用值的直接方法（线性和膨胀β回归）和间接方法，间接方法在产生效用之前首先使用非参数或有序逻辑回归估计EQ-5D-5L维度响应。回归模型使用GHQ-12反应作为自变量，控制社会人口因素。使用均方根误差（RMSE）和平均绝对误差（MAE）评估模型性能。我们还计算了按效用分位数分层的误差统计。结果：对于整体模型性能，线性和有序逻辑模型的RMSE值相同（0.142），贝塔模型的RMSE值更高（0.148），非参数方法的RMSE值最高（0.155）。有序逻辑模型在MAE中表现最好，其次是线性、beta和非参数方法。分层分析揭示了预测准确度在效用分位数上的异质性。模型在最低效用分位数中表现较差。间接映射在概念上更加健壮，因为它与EQ-5D-5L的维度结构一致，并且最小化了与使用不同值集相关的变化。结论：本研究为心理健康数据映射到健康效用提供了最新的算法。利用GHQ-12响应和基本社会人口变量，可以应用映射模型来产生效用值，以便在没有效用数据的情况下用于经济评估。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Value in Health 医学-卫生保健

CiteScore

6.90

自引率

6.70%

发文量

3064

审稿时长

3-8 weeks

期刊介绍： Value in Health contains original research articles for pharmacoeconomics, health economics, and outcomes research (clinical, economic, and patient-reported outcomes/preference-based research), as well as conceptual and health policy articles that provide valuable information for health care decision-makers as well as the research community. As the official journal of ISPOR, Value in Health provides a forum for researchers, as well as health care decision-makers to translate outcomes research into health care decisions.