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Review
. 2018 May;19(4):557-570.
doi: 10.1007/s10198-017-0902-x. Epub 2017 May 30.

What Is the Evidence for the Performance of Generic Preference-Based Measures? A Systematic Overview of Reviews

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Free PMC article
Review

What Is the Evidence for the Performance of Generic Preference-Based Measures? A Systematic Overview of Reviews

Aureliano Paolo Finch et al. Eur J Health Econ. .
Free PMC article

Abstract

Objective: To assess the evidence on the validity and responsiveness of five commonly used preference-based instruments, the EQ-5D, SF-6D, HUI3, 15D and AQoL, by undertaking a review of reviews.

Methods: Four databases were investigated using a strategy refined through a highly sensitive filter for systematic reviews. References were screened and a search for grey literature was performed. Identified citations were scrutinized against pre-defined eligibility criteria and data were extracted using a customized extraction template. Evidence on known group validity, convergent validity and responsiveness was extracted and reviewed by narrative synthesis. Quality of the included reviews was assessed using a modified version of the AMSTAR checklist.

Results: Thirty reviews were included, sixteen of which were of excellent or good quality. The body of evidence, covering more than 180 studies, was heavily skewed towards EQ-5D, with significantly fewer studies investigating HUI3 and SF-6D, and very few the 15D and AQoL. There was also lack of head-to-head comparisons between GPBMs and the tests reported by the reviews were often weak. Where there was evidence, EQ-5D, SF-6D, HUI3, 15D and AQoL seemed generally valid and responsive instruments, although not for all conditions. Evidence was not consistently reported across reviews.

Conclusions: Although generally valid, EQ-5D, SF-6D and HUI3 suffer from some problems and perform inconsistently in some populations. The lack of head-to-head comparisons and the poor reporting impedes the comparative assessment of the performance of GPBMs. This highlights the need for large comparative studies designed to test instruments' performance.

Keywords: Preference based measures; Psychometric properties; Quality of life; Review.

Conflict of interest statement

No funding was received for this project.

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References

    1. Brazier J, Ratcliffe J, Salomon JA, Tsuchiya A. Measuring and valuing health benefits for economic evaluation. Oxford: Oxford University Press; 2008.
    1. Richardson J, Iezzi A, Khan MA. Why do multi-attribute utility instruments produce different utilities: the relative importance of the descriptive systems, scale and “micro-utility effects”. Qual. Life Res. 2015;24:2045. doi: 10.1007/s11136-015-0926-6. - DOI - PMC - PubMed
    1. Brazier, J., Rowen, D., Nice, D.S.U.: Technical support document 11: Alternatives to EQ5D for generating health state utility values. Report by Decision Support Unit. Mar. http://www.nicedsu.org.uk/TSD11%20Alternatives%20to%20EQ-5D_final.pdf (2011) - PubMed
    1. Nord E, Richardson J, Macarounas-Kirchmann K. Social evaluation of health care versus personal evaluation of health states. Int. J. Technol. Assess. Healthc. 1993;9:463–468. doi: 10.1017/S0266462300005390. - DOI - PubMed
    1. Tsuchiya A, Brazier B, Roberts J. Comparison of valuation methods used to generate the EQ5D and the SF6D value sets in the UK. J. Health Econ. 2006;25(2):334–346. doi: 10.1016/j.jhealeco.2005.09.003. - DOI - PubMed
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