Al Sayah Fatima, Jin Xuejing, Short Hilary, McClure Nathan S, Ohinmaa Arto, Johnson Jeffrey A
Alberta PROMs and EQ-5D Research and Support Unit, School of Public Health, University of Alberta, Edmonton, AB, Canada.
Centre for Evidence-based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Value Health. 2025 Mar;28(3):470-476. doi: 10.1016/j.jval.2024.11.006. Epub 2024 Dec 16.
We aimed to provide a comprehensive summary, synthesis, and appraisal of minimally important difference (MID) estimates for EQ-5D instruments.
We conducted a systematic search using relevant terms related to "minimally/clinically, meaningful/ important difference/change" and "EQ-5D" in 6 major databases, including MEDLINE, Embase, PsycINFO, CINAHL, Scopus, and Cochrane Library (up to January 2023). We included studies that provided at least 1 original MID estimate for the EQ-5D.
A total of 90 studies reporting 840 MID estimates were included. MID estimates for the EQ-5D-3L index score ranged from 0.075 to 0.8 using distribution-based approaches (239 estimates; 20 studies), from 0.003 to 0.72 using anchor-based approaches (189 estimates; 43 studies), and from 0.038 to 0.082 using instrument-defined approaches (4 estimates; 1 study). For the EQ-5D-5L, MID estimates ranged from 0.023 to 0.115 using distribution-based approaches (17 estimates; 12 studies), from 0.01 to 0.41 using anchor-based approaches (97 estimates; 15 studies), and from 0.037 to 0.101 using instrument-defined approaches (62 estimates; 8 studies). For the EQ visual analog scale, MID estimates ranged from 0.96 to 16.6 using distribution-based approaches (87 estimates; 14 studies) and from 0.42 to 51.0 using anchor-based approaches (84 estimates; 24 studies). MID estimates varied by underlying clinical conditions, baseline scores, and direction of change.
A wide range of MID estimates for EQ-5D instruments were identified, highlighting the variability of MID across populations, estimation methods, direction of change, baseline scores, and EQ-5D versions. These factors should be carefully considered when selecting an appropriate MID for interpreting EQ-5D scores.
我们旨在对EQ-5D量表的最小重要差异（MID）估计值进行全面的总结、综合和评估。
我们在6个主要数据库（包括MEDLINE、Embase、PsycINFO、CINAHL、Scopus和Cochrane图书馆，截至2023年1月）中使用与“最小/临床有意义/重要差异/变化”和“EQ-5D”相关的术语进行了系统检索。我们纳入了至少提供1个EQ-5D原始MID估计值的研究。
共纳入90项报告了840个MID估计值的研究。EQ-5D-3L指数得分的MID估计值，基于分布的方法范围为0.075至0.8（239个估计值；20项研究），基于锚定的方法范围为0.003至0.72（189个估计值；43项研究），基于工具定义的方法范围为0.038至0.082（4个估计值；1项研究）。对于EQ-5D-5L，基于分布的方法MID估计值范围为0.023至0.115（17个估计值；12项研究），基于锚定的方法范围为0.01至0.41（97个估计值；15项研究），基于工具定义的方法范围为0.037至0.101（62个估计值；8项研究）。对于EQ视觉模拟量表，基于分布的方法MID估计值范围为0.96至16.6（87个估计值；14项研究），基于锚定的方法范围为0.42至51.0（84个估计值；24项研究）。MID估计值因潜在临床状况、基线得分和变化方向而异。
确定了EQ-5D量表的广泛MID估计值，突出了MID在人群、估计方法、变化方向以及基线得分和EQ-5D版本方面的变异性。在选择合适的MID来解释EQ-5D得分时，应仔细考虑这些因素。
