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EQ-5D-5L 比 EQ-5D-3L 更好吗?来自七个国家的描述性系统和价值体系的头对头比较。

Is EQ-5D-5L Better Than EQ-5D-3L? A Head-to-Head Comparison of Descriptive Systems and Value Sets from Seven Countries.

机构信息

Department of Medical Psychology and Psychotherapy, Erasmus MC, Erasmus University, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.

Department of Public Health, Erasmus MC, Erasmus University, Rotterdam, The Netherlands.

出版信息

Pharmacoeconomics. 2018 Jun;36(6):675-697. doi: 10.1007/s40273-018-0623-8.


DOI:10.1007/s40273-018-0623-8
PMID:29470821
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5954015/
Abstract

OBJECTIVE: This study describes the first empirical head-to-head comparison of EQ-5D-3L (3L) and EQ-5D-5L (5L) value sets for multiple countries. METHODS: A large multinational dataset, including 3L and 5L data for eight patient groups and a student cohort, was used to compare 3L versus 5L value sets for Canada, China, England/UK (5L/3L, respectively), Japan, The Netherlands, South Korea and Spain. We used distributional analyses and two methods exploring discriminatory power: relative efficiency as assessed by the F statistic, and an area under the curve for the receiver-operating characteristics approach. Differences in outcomes were explored by separating descriptive system effects from valuation effects, and by exploring distributional location effects. RESULTS: In terms of distributional evenness, efficiency of scale use and the face validity of the resulting distributions, 5L was superior, leading to an increase in sensitivity and precision in health status measurement. When compared with 5L, 3L systematically overestimated health problems and consequently underestimated utilities. This led to bias, i.e. over- or underestimations of discriminatory power. CONCLUSION: We conclude that 5L provides more precise measurement at individual and group levels, both in terms of descriptive system data and utilities. The increased sensitivity and precision of 5L is likely to be generalisable to longitudinal studies, such as in intervention designs. Hence, we recommend the use of the 5L across applications, including economic evaluation, clinical and public health studies. The evaluative framework proved to be useful in assessing preference-based instruments and might be useful for future work in the development of descriptive systems or health classifications.

摘要

目的:本研究描述了 EQ-5D-3L(3L)和 EQ-5D-5L(5L)价值体系在多个国家的首次实证头对头比较。

方法:利用一个大型的多国数据集,包括 8 个患者群体和一个学生队列的 3L 和 5L 数据,比较了加拿大、中国、英格兰/英国(分别为 5L/3L)、日本、荷兰、韩国和西班牙的 3L 与 5L 价值体系。我们使用分布分析和两种探索区分能力的方法:F 统计量评估的相对效率,以及接收者操作特征方法的曲线下面积。通过从估值效果中分离描述性系统效果,以及通过探索分布位置效果,探讨了结果的差异。

结果:在分布均匀性、规模使用效率和由此产生的分布的表面有效性方面,5L 更为优越,导致健康状况测量的敏感性和精度提高。与 5L 相比,3L 系统地高估了健康问题,从而低估了效用。这导致了偏差,即对区分能力的高估或低估。

结论:我们的结论是,5L 在个体和群体水平上都提供了更精确的测量,无论是在描述性系统数据还是效用方面。5L 的敏感性和精度提高可能适用于纵向研究,如干预设计。因此,我们建议在包括经济评估、临床和公共卫生研究在内的各种应用中使用 5L。评估框架被证明在评估偏好基础工具方面是有用的,并且可能对未来的描述性系统或健康分类的发展工作有用。

相似文献

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本文引用的文献

[1]
Handling Data Quality Issues to Estimate the Spanish EQ-5D-5L Value Set Using a Hybrid Interval Regression Approach.

Value Health. 2017-12-2

[2]
EQ-5D-5L versus EQ-5D-3L: The Impact on Cost Effectiveness in the United Kingdom.

Value Health. 2018-1

[3]
In search of a common currency: A comparison of seven EQ-5D-5L value sets.

Health Econ. 2018-1

[4]
Valuing health-related quality of life: An EQ-5D-5L value set for England.

Health Econ. 2018-1

[5]
Estimating an EQ-5D-5L Value Set for China.

Value Health. 2017-4

[6]
Quality Control Process for EQ-5D-5L Valuation Studies.

Value Health. 2017-3

[7]
EQ-5D and the EuroQol Group: Past, Present and Future.

Appl Health Econ Health Policy. 2017-4

[8]
Comparison of Value Set Based on DCE and/or TTO Data: Scoring for EQ-5D-5L Health States in Japan.

Value Health. 2016

[9]
Dutch Tariff for the Five-Level Version of EQ-5D.

Value Health. 2016-6

[10]
What Determines the Shape of an EQ-5D Index Distribution?

Med Decis Making. 2016-11

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