Correspondence between EQ-5D health state classifications and EQ VAS scores

<p>Abstract</p> <p>Background</p> <p>The EQ-5D health-related quality of life instrument comprises a health state classification followed by a health evaluation using a visual analogue scale (VAS). The EQ-5D has been employed frequently in economic evaluations, yet the...

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Main Author: Whynes David K
Format: Article
Language:English
Published: BMC 2008-11-01
Series:Health and Quality of Life Outcomes
Online Access:http://www.hqlo.com/content/6/1/94
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spelling doaj-59dfef74647a448b83c820c4f32b16522020-11-25T00:06:34ZengBMCHealth and Quality of Life Outcomes1477-75252008-11-01619410.1186/1477-7525-6-94Correspondence between EQ-5D health state classifications and EQ VAS scoresWhynes David K<p>Abstract</p> <p>Background</p> <p>The EQ-5D health-related quality of life instrument comprises a health state classification followed by a health evaluation using a visual analogue scale (VAS). The EQ-5D has been employed frequently in economic evaluations, yet the relationship between the two parts of the instrument remains ill-understood. In this paper, we examine the correspondence between VAS scores and health state classifications for a large sample, and identify variables which contribute to determining the VAS scores independently of the health states as classified.</p> <p>Methods</p> <p>A UK trial of management of low-grade abnormalities detected on screening for cervical pre-cancer (TOMBOLA) provided EQ-5D data for over 3,000 women. Information on distress and multi-dimensional health locus of control had been collected using other instruments. A linear regression model was fitted, with VAS score as the dependent variable. Independent variables comprised EQ-5D health state classifications, distress, locus of control, and socio-demographic characteristics. Equivalent EQ-5D and distress data, collected at twelve months, were available for over 2,000 of the women, enabling us to predict changes in VAS score over time from changes in EQ-5D classification and distress.</p> <p>Results</p> <p>In addition to EQ-5D health state classification, VAS score was influenced by the subject's perceived locus of control, and by her age, educational attainment, ethnic origin and smoking behaviour. Although the EQ-5D classification includes a distress dimension, the independent measure of distress was an additional determinant of VAS score. Changes in VAS score over time were explained by changes in both EQ-5D severities and distress. Women allocated to the experimental management arm of the trial reported an increase in VAS score, independently of any changes in health state and distress.</p> <p>Conclusion</p> <p>In this sample, EQ VAS scores were predictable from the EQ-5D health state classification, although there also existed other group variables which contributed systematically and independently towards determining such scores. These variables comprised psychological disposition, socio-demographic factors such as age and education, clinically-important distress, and the clinical intervention itself.</p> <p>Trial registration</p> <p>ISRCTN34841617</p> http://www.hqlo.com/content/6/1/94
collection DOAJ
language English
format Article
sources DOAJ
author Whynes David K
spellingShingle Whynes David K
Correspondence between EQ-5D health state classifications and EQ VAS scores
Health and Quality of Life Outcomes
author_facet Whynes David K
author_sort Whynes David K
title Correspondence between EQ-5D health state classifications and EQ VAS scores
title_short Correspondence between EQ-5D health state classifications and EQ VAS scores
title_full Correspondence between EQ-5D health state classifications and EQ VAS scores
title_fullStr Correspondence between EQ-5D health state classifications and EQ VAS scores
title_full_unstemmed Correspondence between EQ-5D health state classifications and EQ VAS scores
title_sort correspondence between eq-5d health state classifications and eq vas scores
publisher BMC
series Health and Quality of Life Outcomes
issn 1477-7525
publishDate 2008-11-01
description <p>Abstract</p> <p>Background</p> <p>The EQ-5D health-related quality of life instrument comprises a health state classification followed by a health evaluation using a visual analogue scale (VAS). The EQ-5D has been employed frequently in economic evaluations, yet the relationship between the two parts of the instrument remains ill-understood. In this paper, we examine the correspondence between VAS scores and health state classifications for a large sample, and identify variables which contribute to determining the VAS scores independently of the health states as classified.</p> <p>Methods</p> <p>A UK trial of management of low-grade abnormalities detected on screening for cervical pre-cancer (TOMBOLA) provided EQ-5D data for over 3,000 women. Information on distress and multi-dimensional health locus of control had been collected using other instruments. A linear regression model was fitted, with VAS score as the dependent variable. Independent variables comprised EQ-5D health state classifications, distress, locus of control, and socio-demographic characteristics. Equivalent EQ-5D and distress data, collected at twelve months, were available for over 2,000 of the women, enabling us to predict changes in VAS score over time from changes in EQ-5D classification and distress.</p> <p>Results</p> <p>In addition to EQ-5D health state classification, VAS score was influenced by the subject's perceived locus of control, and by her age, educational attainment, ethnic origin and smoking behaviour. Although the EQ-5D classification includes a distress dimension, the independent measure of distress was an additional determinant of VAS score. Changes in VAS score over time were explained by changes in both EQ-5D severities and distress. Women allocated to the experimental management arm of the trial reported an increase in VAS score, independently of any changes in health state and distress.</p> <p>Conclusion</p> <p>In this sample, EQ VAS scores were predictable from the EQ-5D health state classification, although there also existed other group variables which contributed systematically and independently towards determining such scores. These variables comprised psychological disposition, socio-demographic factors such as age and education, clinically-important distress, and the clinical intervention itself.</p> <p>Trial registration</p> <p>ISRCTN34841617</p>
url http://www.hqlo.com/content/6/1/94
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