Department of Pharmacy Systems, Outcomes and Policy, University of Illinois at Chicago, Chicago, IL (EHL, ASP, SMW, TAL).
Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada (FX).
Med Decis Making. 2018 Nov;38(8):968-982. doi: 10.1177/0272989X18802797.
To compare and contrast EQ-5D-5L (5L) and EQ-5D-3L (3L) health state values derived from a common sample.
Data from the 2017 US EQ-5D valuation study were analyzed. Value sets were estimated with random-effects linear regression based on composite time trade-off (cTTO) valuations for 3L and 5L health states with 2 approaches to model specification: main effects only and additional N3/N45 terms. Properties of the descriptive system and value set characteristics were compared by examining distributions of predicted index scores, ceiling effects, and single-level transition values from adjacent corner health states. Mean transition values were calculated for all predicted 3L and 5L health states and plotted against baseline index scores.
A total of 1062 respondents were included in the analysis. The observed mean cTTO values for the worst possible 3L and 5L health states were -0.423 and -0.343, respectively. The range of scale was larger with the 3L, compared to the 5L, for both main effects and N term models. Values for the mildest 5L health states (range, 0.857-0.924) were similar to 11111 for the 3L. Parameter estimates for matched dimension levels differed by <|0.07| except for the most severe level of Mobility. For the main effects model, 3L mean transition values were greater for more severe baseline 3L index scores, whereas 5L mean transition values remained constant irrespective of the baseline index score.
Compared to the 3L, the 5L exhibited a lower ceiling effect and improved measurement properties. There was a larger range of scale for the 3L compared to 5L; however, this difference was driven by differences in preference for the most severe level of problems in Mobility.
比较和对比源自同一样本的 EQ-5D-5L（5L）和 EQ-5D-3L（3L）健康状态值。
分析了 2017 年美国 EQ-5D 估值研究的数据。基于复合时间权衡（cTTO）对 3L 和 5L 健康状态的估值，使用随机效应线性回归估计价值集，模型规格有两种方法：仅主效应和附加 N3/N45 项。通过检查预测指数得分的分布、上限效应和来自相邻角健康状态的单级转换值，比较描述性系统和价值集特征。为所有预测的 3L 和 5L 健康状态计算了平均转换值，并与基线指数得分进行了比较。
共纳入 1062 名受访者进行分析。最差可能的 3L 和 5L 健康状态的观察到的平均 cTTO 值分别为-0.423 和-0.343。与 5L 相比，主效应和 N 项模型下，3L 的量表范围更大。5L 中最轻微的健康状态（范围为 0.857-0.924）的值与 3L 的 11111 相似。除了最严重的移动能力水平外，匹配维度水平的参数估计值差异<|0.07|。对于主效应模型，3L 的平均转换值随基线 3L 指数得分的增加而增加，而 5L 的平均转换值则保持不变，而与基线指数得分无关。
与 3L 相比，5L 表现出较低的上限效应和改进的测量特性。3L 的量表范围比 5L 大；然而，这种差异是由移动能力最严重水平的偏好差异驱动的。
