School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China.
Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
Eur J Health Econ. 2024 Feb;25(1):7-19. doi: 10.1007/s10198-023-01566-x. Epub 2023 Jan 29.
To explore the comparative performance and develop the mapping algorithms between EQ-5D-5L and SF-6Dv2 in China.
Respondents recruited from the Chinese general population completed both EQ-5D-5L and SF-6Dv2 during face-to-face interviews. Ceiling/floor effects were reported. Discriminative validity in self-reported chronic conditions was investigated using the effect sizes (ES). Test-retest reliability was evaluated using intra-class correlation coefficient (ICC) and Bland-Altman plots in a subsample. Correlation and absolute agreements between the two measures were estimated with Spearman's rank correlation coefficient and ICC, respectively. Ordinary least squares (OLS), generalized linear model, Tobit model, and robust MM-estimator were explored to estimate mapping equations between EQ-5D-5L and SF-6Dv2.
3320 respondents (50.3% males; age 18-90 years) were recruited. 51.1% and 12.2% of respondents reported no problems on all EQ-5D-5L and SF-6Dv2 dimensions, respectively. The mean EQ-5D-5L utility was higher than SF-6Dv2 (0.947 vs. 0.827, p < 0.001). Utilities were significantly different across all chronic conditions groups for both measures. The mean absolute difference of utilities between the two tests for EQ-5D-5L was smaller (0.033 vs. 0.043) than SF-6Dv2, with a slightly higher ICC (0.859 vs. 0.827). Fair agreement (ICC = 0.582) was observed in the utilities between the two measures. Mapping algorithms generated by the OLS models performed the best according to the goodness-of-fit indicators.
Both measures showed comparable discriminative validity. Systematic differences in utilities were found, and on average, the EQ-5D-5L generates higher values than the SF-6Dv2. Mapping algorithms between the EQ-5D-5L and SF-6Dv2 are reported to enable transformations between these two measures in China.
探索 EQ-5D-5L 和 SF-6Dv2 在中国的比较性能并建立两者之间的映射算法。
通过面对面访谈招募来自中国一般人群的受访者，让他们同时完成 EQ-5D-5L 和 SF-6Dv2 量表。报告了天花板/地板效应。使用效应量（ES）研究了自我报告的慢性疾病的判别有效性。在子样本中，使用组内相关系数（ICC）和 Bland-Altman 图评估了重测信度。使用 Spearman 秩相关系数和 ICC 分别估计了两种测量方法之间的相关性和绝对一致性。探索了普通最小二乘法（OLS）、广义线性模型、Tobit 模型和稳健 MM 估计器来估计 EQ-5D-5L 和 SF-6Dv2 之间的映射方程。
共招募了 3320 名受访者（50.3%为男性；年龄 18-90 岁）。分别有 51.1%和 12.2%的受访者在 EQ-5D-5L 和 SF-6Dv2 所有维度上均报告没有问题。EQ-5D-5L 效用均值高于 SF-6Dv2（0.947 比 0.827，p<0.001）。两种测量方法在所有慢性疾病组之间的效用均存在显著差异。EQ-5D-5L 两次测试之间的效用平均绝对差值较小（0.033 比 0.043），ICC 略高（0.859 比 0.827）。两种测量方法的效用之间观察到了良好的一致性（ICC=0.582）。根据拟合优度指标，OLS 模型生成的映射算法表现最佳。
两种测量方法均表现出相当的判别有效性。发现效用存在系统差异，平均而言，EQ-5D-5L 产生的数值高于 SF-6Dv2。报告了 EQ-5D-5L 和 SF-6Dv2 之间的映射算法，以实现在中国这两种测量方法之间的转换。
