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      A review of health utilities using the EQ-5D in studies of cardiovascular disease

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          Abstract

          Background

          The EQ-5D has been extensively used to assess patient utility in trials of new treatments within the cardiovascular field. The aims of this study were to review evidence of the validity and reliability of the EQ-5D, and to summarise utility scores based on the use of the EQ-5D in clinical trials and in studies of patients with cardiovascular disease.

          Methods

          A structured literature search was conducted using keywords related to cardiovascular disease and EQ-5D. Original research studies of patients with cardiovascular disease that reported EQ-5D results and its measurement properties were included.

          Results

          Of 147 identified papers, 66 met the selection criteria, with 10 studies reporting evidence on validity or reliability and 60 reporting EQ-5D responses (VAS or self-classification). Mean EQ-5D index-based scores ranged from 0.24 (SD 0.39) to 0.90 (SD 0.16), while VAS scores ranged from 37 (SD 21) to 89 (no SD reported). Stratification of EQ-5D index scores by disease severity revealed that scores decreased from a mean of 0.78 (SD 0.18) to 0.51 (SD 0.21) for mild to severe disease in heart failure patients and from 0.80 (SD 0.05) to 0.45 (SD 0.22) for mild to severe disease in angina patients.

          Conclusions

          The published evidence generally supports the validity and reliability of the EQ-5D as an outcome measure within the cardiovascular area. This review provides utility estimates across a range of cardiovascular subgroups and treatments that may be useful for future modelling of utilities and QALYs in economic evaluations within the cardiovascular area.

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          Most cited references67

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          The estimation of a preference-based measure of health from the SF-36.

          This paper reports on the findings of a study to derive a preference-based measure of health from the SF-36 for use in economic evaluation. The SF-36 was revised into a six-dimensional health state classification called the SF-6D. A sample of 249 states defined by the SF-6D have been valued by a representative sample of 611 members of the UK general population, using standard gamble. Models are estimated for predicting health state valuations for all 18,000 states defined by the SF-6D. The econometric modelling had to cope with the hierarchical nature of the data and its skewed distribution. The recommended models have produced significant coefficients for levels of the SF-6D, which are robust across model specification. However, there are concerns with some inconsistent estimates and over prediction of the value of the poorest health states. These problems must be weighed against the rich descriptive ability of the SF-6D, and the potential application of these models to existing and future SF-36 data set.
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            US valuation of the EQ-5D health states: development and testing of the D1 valuation model.

            The EQ-5D is a brief, multiattribute, preference-based health status measure. This article describes the development of a statistical model for generating US population-based EQ-5D preference weights. A multistage probability sample was selected from the US adult civilian noninstitutional population. Respondents valued 13 of 243 EQ-5D health states using the time trade-off (TTO) method. Data for 12 states were used in econometric modeling. The TTO valuations were linearly transformed to lie on the interval [-1, 1]. Methods were investigated to account for interaction effects caused by having problems in multiple EQ-5D dimensions. Several alternative model specifications (eg, pooled least squares, random effects) also were considered. A modified split-sample approach was used to evaluate the predictive accuracy of the models. All statistical analyses took into account the clustering and disproportionate selection probabilities inherent in our sampling design. Our D1 model for the EQ-5D included ordinal terms to capture the effect of departures from perfect health as well as interaction effects. A random effects specification of the D1 model yielded a good fit for the observed TTO data, with an overall R of 0.38, a mean absolute error of 0.025, and 7 prediction errors exceeding 0.05 in absolute magnitude. The D1 model best predicts the values for observed health states. The resulting preference weight estimates represent a significant enhancement of the EQ-5D's utility for health status assessment and economic analysis in the US.
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              Swedish population health-related quality of life results using the EQ-5D.

              Health-related quality of life (HRQoL) measured on population level may be useful to guide policies for health. This study aims to describe the HRQoL; in EQ-5D dimensions, mean rating scale (RS) scores and mean EQ-5D index values, in the general population, by certain disease and socio-economic groups, in Stockholm County 1998. The EQ-5D self-classifier and a RS were included in the 1998 cross-sectional postal Stockholm County public health survey to a representative sample (n = 4950, 20-88 years), 63% response rate. Mean RS score ranged from 0.90 (20-29 years) to 0.69 (80-88 years), mean EQ-5D index value ranged from 0.89 (20-29 years) to 0.74 (80-88 years). For different diseases mean RS scores ranged from 0.80 (asthma) to 0.69 (angina pectoris), mean EQ-5D index values ranged from 0.79 (asthma) to 0.66 (low back pain). The mean health state scores (RS and EQ-5D index) were 0.06 lower in the unskilled manual group than in the higher non-manual group after controlling for age and sex (p < 0.0001). This difference was 0.03 after controlling also for different diseases (p < 0.0001). In conclusion, our results show that the HRQoL varies greatly between socio-economic and disease groups. Furthermore, after controlling for age, sex and disease, HRQoL is lower in manual than in non-manual groups.
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                Author and article information

                Journal
                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central
                1477-7525
                2010
                28 January 2010
                : 8
                : 13
                Affiliations
                [1 ]Health Economics Research Group, Brunel University, Uxbridge, UK
                [2 ]Papworth Hospital NHS Trust, Cambridge UK
                [3 ]MRC Biostatistics Unit, Institute of Public Health, Cambridge, UK
                [4 ]National Collaborating Centre for Mental Health, The Royal College of Psychiatrists, London, UK
                Article
                1477-7525-8-13
                10.1186/1477-7525-8-13
                2824714
                20109189
                760b7f12-9de6-496a-9b70-fd3dd6bb1dae
                Copyright ©2010 Dyer et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 July 2009
                : 28 January 2010
                Categories
                Research

                Health & Social care
                Health & Social care

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