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Arch Public Health. 2017 Feb 6;75:6. doi: 10.1186/s13690-017-0174-z. eCollection 2017.

Mapping EQ-5D utilities to GBD 2010 and GBD 2013 disability weights: results of two pilot studies in Belgium.

Author information

1
Institute of Health and Society (IRSS), Université catholique de Louvain Clos Chapelle-aux-Champs, 30 bte B1.30.15, Brussels, 1200 Belgium.
2
Department of Public Health and Surveillance, Scientific Institute of Public Health, Rue Juliette Wytsman 14, 1050 Brussels, Belgium.
3
National Institute for Public Health and the Environment, Centre for Health and Society, P.O. Box 1, 3720, BA Bilthoven, The Netherlands.
4
Department of Public Health, Erasmus MC, Dr. Molewaterplein 50, 3015 GE Rotterdam, The Netherlands.
5
Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121 USA.

Abstract

BACKGROUND:

Utilities and disability weights (DWs) are metrics used for calculating Quality-Adjusted Life Years and Disability-Adjusted Life Years (DALYs), respectively. Utilities can be obtained with multi-attribute instruments such as the EuroQol 5 dimensions questionnaire (EQ-5D). In 2010 and 2013, Salomon et al. proposed a set of DWs for 220 and 183 health states, respectively. The objective of this study is to develop an approach for mapping EQ-5D utilities to existing GBD 2010 and GBD 2013 DWs, allowing to predict new GBD 2010/2013 DWs based on EQ-5D utilities.

METHODS:

We conducted two pilot studies including respectively four and twenty-seven health states selected from the 220 DWs of the GBD 2010 study. In the first study, each participant evaluated four health conditions using the standard written EQ-5D-5 L questionnaire. In the second study, each participant evaluated four health conditions randomly selected among the twenty-seven health states using a previously developed web-based EQ-5D-5 L questionnaire. The EQ-5D responses were translated into utilities using the model developed by Cleemput et al. A loess regression allowed to map EQ-5D utilities to logit transformed DWs.

RESULTS:

Overall, 81 and 393 respondents completed the first and the second survey, respectively. In the first study, a monotonic relationship between derived utilities and predicted GBD 2010/2013 DWs was observed, but not in the second study. There were some important differences in ranking of health states based on utilities versus GBD 2010/2013 DWs. The participants of the current study attributed a relatively higher severity level to musculoskeletal disorders such as 'Amputation of both legs' and a relatively lower severity level to non-functional disorders such as 'Headache migraine' compared to the participants of the GBD 2010/2013 studies.

CONCLUSION:

This study suggests the possibility to translate any utility derived from EQ-5D scores into a DW, but also highlights important caveats. We observed a satisfactory result of this methodology when utilities were derived from a population of public health students, a written questionnaire and a small number of health states in the presence of a study leader. However the results were unsatisfactory when utilities were derived from a sample of the general population, using a web-based questionnaire. We recommend to repeat the study in a larger and more diverse sample to obtain a more representative distribution of educational level and age.

KEYWORDS:

DW; EQ-5D; GBD2010; GBD2013; Mapping; Utilities

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