Hernandez Alava Monica, Wailoo Allan, Grimm Sabine, Pudney Stephen, Gomes Manuel, Sadique Zia, Meads David, O'Dwyer John, Barton Garry, Irvine Lisa
School of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK.
School of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK.
Value Health. 2018 Jan;21(1):49-56. doi: 10.1016/j.jval.2017.09.004. Epub 2017 Oct 18.
To model the relationship between the three-level (3L) and the five-level (5L) EuroQol five-dimensional questionnaire and examine how differences have an impact on cost effectiveness in case studies.
We used two data sets that included the 3L and 5L versions from the same respondents. The EuroQol Group data set (n = 3551) included patients with different diseases and a healthy cohort. The National Data Bank data set included patients with rheumatoid disease (n = 5205). We estimated a system of ordinal regressions in each data set using copula models to link responses of the 3L instrument to those of the 5L instrument and its UK tariff, and vice versa. Results were applied to nine cost-effectiveness studies.
Best-fitting models differed between the EuroQol Group and the National Data Bank data sets in terms of the explanatory variables, copulas, and coefficients. In both cases, the coefficients of the covariates and latent factors between the 3L and the 5L instruments were significantly different, indicating that moving between instruments is not simply a uniform re-alignment of the response levels for most dimensions. In the case studies, moving from the 3L to the 5L caused a decrease of up to 87% in incremental quality-adjusted life-years gained from effective technologies in almost all cases. Incremental cost-effectiveness ratios increased, often substantially. Conversely, one technology with a significant mortality gain saw increased incremental quality-adjusted life-years.
The 5L shifts mean utility scores up the utility scale toward full health and compresses them into a smaller range, compared with the 3L. Improvements in quality of life are valued less using the 5L than using the 3L. The 3L and the 5L can produce substantially different estimates of cost effectiveness. There is no simple proportional adjustment that can be made to reconcile these differences.
构建三级（3L）和五级（5L）欧洲五维健康量表之间的关系模型，并在案例研究中考察差异如何影响成本效益。
我们使用了两个数据集，其中包含来自相同受访者的3L和5L版本。欧洲五维健康量表组数据集（n = 3551）包括患有不同疾病的患者和一个健康队列。国家数据库数据集包括类风湿病患者（n = 5205）。我们在每个数据集中使用copula模型估计了一个有序回归系统，以将3L量表的回答与5L量表及其英国关税的回答联系起来，反之亦然。结果应用于九项成本效益研究。
在解释变量、copula函数和系数方面，欧洲五维健康量表组和国家数据库数据集的最佳拟合模型有所不同。在这两种情况下，3L和5L量表之间协变量和潜在因素的系数存在显著差异，这表明在量表之间转换并非大多数维度上简单的统一重新调整回答水平。在案例研究中，从3L转换到5L几乎在所有情况下都会使有效技术带来的增量质量调整生命年减少高达87%。增量成本效益比增加，且往往大幅增加。相反，一项具有显著死亡率降低效果的技术的增量质量调整生命年有所增加。
与3L相比，5L转换意味着效用得分在效用量表上朝着完全健康的方向上升，并将其压缩到更小的范围。使用5L对生活质量改善的估值低于使用3L。3L和5L可能会产生成本效益的显著不同估计。不存在可以用来调和这些差异的简单比例调整方法。
