Development of Methods for the Mapping of Utilities Using Mixture Models: Mapping the AQLQ-S to the EQ-5D-5L and the HUI3 in Patients with Asthma

被引:38
作者
Gray, Laura A. [1 ]
Alava, Monica Hernandez [1 ]
Wailoo, Allan J. [1 ]
机构
[1] Univ Sheffield, Sch Hlth & Related Res, Sheffield, S Yorkshire, England
基金
英国医学研究理事会;
关键词
EQ-5D; HUI; mapping; utility; QUALITY-OF-LIFE; HEALTH-STATE UTILITY; LUNG-CANCER PATIENTS; ECONOMIC-EVALUATION; QUESTIONNAIRE; REGRESSION; INSTRUMENTS; INDEX; OUTCOMES; VALUES;
D O I
10.1016/j.jval.2017.09.017
中图分类号
F [经济];
学科分类号
02 ;
摘要
Background: Studies have shown that methods based on mixture models work well when mapping clinical to preference-based methods. Objectives: To develop these methods in different ways and to compare performance in a case study. Methods: Data from 856 patients with asthma allowed mapping between the Asthma Quality of Life Questionnaire and both the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) and the health utilities index mark 3 (HUB). Adjusted limited dependent variable mixture models and beta-based mixture models were estimated. Optional inclusion of the gap between full health and the next value as well as a mass point at the next feasible value were explored. Results: In all cases, model specifications formally modeling the gap between full health and the next feasible value were an improvement on those that did not. Mapping to the HUB required more components in the mixture models than did mapping to the EQ-5D-5L because of its uneven distribution. The optimal beta-based mixture models mapping to the HUB included a probability mass at the utility value adjacent to full health. This is not the case when estimating the EQ-5D-5L, because of the low proportion of observations at this point. Conclusions: Beta based mixture models marginally outperformed adjusted limited dependent variable mixture models with the same number of components in this data set. Nevertheless, they require a larger number of parameters and longer estimation time. Both mixture model types closely fit both EQ-5D-5L and HUI data. Standard mapping approaches typically lead to biased estimates of health gain. The mixture model approaches exhibit no such bias. Both can be used with confidence in applied cost-effectiveness studies. Future mapping studies in other disease areas should consider similar methods.
引用
收藏
页码:748 / 757
页数:10
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