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通用多属性效用工具最小重要变化的系统评价及其估计建议。

A systematic review of minimum important changes for generic multi-attribute utility instruments and recommendations for their estimation.

作者信息

Henson Glen J, van der Mei Ingrid, Taylor Bruce V, Scuffham Paul, Chen Gang, Campbell Julie A

机构信息

Menzies Institute for Medical Research (University of Tasmania), 17 Liverpool St, Hobart, TAS, 7000, Australia.

Menzies Health Institute Queensland (Griffith University), G40 Griffith Health Centre, Level 8.86 Gold Coast Campus Griffith University, Southport, QLD, 4215, Australia.

出版信息

Eur J Health Econ. 2025 Apr 16. doi: 10.1007/s10198-025-01778-3.

Abstract

INTRODUCTION

Minimum important changes (MICs) represent thresholds for clinically meaningful change. Multi-attribute utility instruments (MAUIs) generate health state utilities (holistic measures of health-related quality of life). No systematic review of MICs specifically for MAUIs has been conducted. In addition, no guidelines for estimating MICs for MAUIs have been proposed. We aimed to correct these evidence gaps by producing guidelines contextualised by a systematic review.

METHODS

We searched ten databases for relevant records using various search terms. Extracted data were analysed narratively and descriptively. The presence of key reporting items (relating to precision, sensitivity, and concurrent validity) was also evaluated. Guidelines for MIC estimation were informed by the broader MIC literature and contextualised using study results.

RESULTS

The review identified 5035 non-duplicate records, with 68 entering the study. 282 unique, anchor-based MICs were extracted. Of these MICs, 119 (42.20%) pertained to the EQ-5D-3L, 82 (29.08%) to the EQ-5D-5L, and 50 (17.73%) to the SF-6D.v1. The most common anchor-based method used to estimate MICs (107, 37.94%) involved taking the mean change score for a group considered to have experienced a MIC. Distribution-based methods were also common, appearing in 31 (45.59%) of the included studies. The inclusion of key reporting items was generally deficient.

CONCLUSIONS

Deficiencies in reporting and diverse estimation methods raise concerns regarding the extant MAUI MIC literature. Researchers should exercise caution when using existing MAUI MICs. Recommendations presented in our study may assist researchers in effectively estimating MICs for use in health economics.

摘要

引言

最小重要变化(MICs)代表临床有意义变化的阈值。多属性效用工具(MAUIs)产生健康状态效用(与健康相关生活质量的整体衡量指标)。尚未对专门针对MAUIs的MICs进行系统评价。此外,也未提出估计MAUIs的MICs的指南。我们旨在通过进行系统评价并制定相关指南来填补这些证据空白。

方法

我们使用各种检索词在十个数据库中检索相关记录。对提取的数据进行叙述性和描述性分析。还评估了关键报告项目(与精密度、敏感性和同时效度相关)的存在情况。MIC估计指南以更广泛的MIC文献为依据,并根据研究结果进行背景化处理。

结果

该评价共识别出5035条非重复记录,其中68条进入研究。提取了282个独特的基于锚定的MICs。在这些MICs中,119个(42.20%)与EQ-5D-3L相关,82个(29.08%)与EQ-5D-5L相关,50个(17.73%)与SF-6D.v1相关。用于估计MICs的最常见的基于锚定的方法(107种,37.94%)是取被认为经历了MIC的一组的平均变化分数。基于分布的方法也很常见,在所纳入的研究中有31种(45.59%)出现。关键报告项目的纳入普遍不足。

结论

报告方面的缺陷和多样的估计方法引发了对现有MAUI MIC文献的担忧。研究人员在使用现有的MAUI MICs时应谨慎。我们研究中提出的建议可能有助于研究人员有效地估计用于健康经济学的MICs。

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