Interim Scoring for the EQ-5D-5L: Mapping the EQ-5D-5L to EQ-5D-3L Value Sets

被引:1388
作者
van Hout, Ben [2 ]
Janssen, M. F. [3 ]
Feng, You-Shan [4 ]
Kohlmann, Thomas [4 ]
Busschbach, Jan [5 ]
Golicki, Dominik [6 ]
Lloyd, Andrew [8 ]
Scalone, Luciana [7 ,9 ]
Kind, Paul [10 ]
Pickard, A. Simon [1 ]
机构
[1] Univ Illinois, Coll Pharm, Ctr Pharmacoecon Res, Chicago, IL 60612 USA
[2] Univ Sheffield, Sheffield, S Yorkshire, England
[3] EuroQol Grp, Rotterdam, Netherlands
[4] Ernst Moritz Arndt Univ Greifswald, Inst Community Med, Greifswald, Germany
[5] Erasmus Univ, Viersprong, Halsteren, Netherlands
[6] Med Univ Warsaw, Warsaw, Poland
[7] Univ Milano Bicocca, Res Ctr Publ Hlth, Milan, Italy
[8] Oxford Outcomes, Oxford, England
[9] CHARTA Fdn, Milan, Italy
[10] Univ York, Ctr Hlth Econ, York YO10 5DD, N Yorkshire, England
关键词
EQ-5D; mapping; preference-based measures; quality of life; utilities; STANDARD EQ-5D; HEALTH-STATUS; 5-LEVEL VERSION; 3-LEVEL SYSTEM; RASCH MODEL; SF-12;
D O I
10.1016/j.jval.2012.02.008
中图分类号
F [经济];
学科分类号
02 ;
摘要
Background: A five-level version of the EuroQol five-dimensional (EQ-5D) descriptive system (EQ-5D-5L) has been developed, but value sets based on preferences directly elicited from representative general population samples are not yet available. The objective of this study was to develop values sets for the EQ-5D-5L by means of a mapping ("cross-walk") approach to the currently available three-level version of the EQ-5D (EQ-5D-3L) values sets. Methods: The EQ-5D-3L and EQ-5D-5L descriptive systems were coadministered to respondents with conditions of varying severity to ensure a broad range of levels of health across EQ-5D questionnaire dimensions. We explored four models to generate value sets for the EQ-5D-5L: linear regression, nonparametric statistics, ordered logistic regression, and item-response theory. Criteria for the preferred model included theoretical background, statistical fit, predictive power, and parsimony. Results: A total of 3691 respondents were included. All models had similar fit statistics. Predictive power was slightly better for the nonparametric and ordered logistic regression models. In considering all criteria, the nonparametric model was selected as most suitable for generating values for the EQ-5D-5L. Conclusions: The nonparametric model was preferred for its simplicity while performing similarly to the other models. Being independent of the value set that is used, it can be applied to transform any EQ-5D-3L value set into EQ-5D-5L index values. Strengths of this approach include compatibility with three-level value sets. A limitation of any crosswalk is that the range of index values is restricted to the range of the EQ-5D-3L value sets.
引用
收藏
页码:708 / 715
页数:8
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