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04-07-2018 | Uitgave 11/2018 Open Access

Quality of Life Research 11/2018

Mapping between HAQ-DI and EQ-5D-5L in a Chinese patient population

Tijdschrift:
Quality of Life Research > Uitgave 11/2018
Auteurs:
Thomas Patton, Hao Hu, Luan Luan, Keqin Yang, Shu-Chuen Li
Belangrijke opmerkingen

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s11136-018-1925-1) contains supplementary material, which is available to authorized users.

Abstract

Objectives

In order to address the current deficiency of health utility evidence relevant for economic evaluations involving treatments for rheumatoid arthritis (RA) in the Chinese setting, this study aims to develop a mapping algorithm linking the Health Assessment Questionnaire (HAQ) and EQ-5D-5L in a Chinese population of patients with RA.

Methods

An estimation sample was obtained from a cross-sectional study that collected HAQ, the pain Visual Analogue Scale, and EQ-5D-5L in RA patients in two tertiary referral hospitals in China. Mapping algorithms were derived in this study using two alternative regression methods: the beta regression and a multivariate ordered probit regression. The internal validity of the mapping algorithms was assessed in each case by calculating predictive performance using a bootstrapping procedure.

Results

Of the several algorithms developed using these data, predictive performance was shown to be better when VAS pain was included as a predictor and when the multivariate ordered probit regression method was used, rather than the beta regression method. The algorithms developed were shown to be comparable, in terms of predictive performance, to existing mapping studies despite the small sample size of the estimation data.

Conclusion

It is hoped that the availability of these algorithms will facilitate the development of cost-effectiveness studies evaluating RA treatments in the Chinese health care setting.

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Extra materiaal
Supplementary material 1 (DOCX 121 KB)
11136_2018_1925_MOESM1_ESM.docx
Supplementary material 2 (DOCX 129 KB)
11136_2018_1925_MOESM2_ESM.docx
Literatuur
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