ArticleThe European journal of health economics : HEPAC : health economics in prevention and care2019
Impact of mapped EQ-5D utilities on cost-effectiveness analysis: in the case of dialysis treatments.
Article in The European journal of health economics : HEPAC : health economics in prevention and care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Mapping to estimate health state utility: a systematic review of development and limitations.Health and quality of life outcomes · 2025Pooled it
- Non-disease specific patient-reported outcome measures of health-related quality of life in juvenile idiopathic arthritis: a systematic review of current research and practice.Rheumatology international · 2022Pooled it
- Mapping the Edmonton Symptom Assessment System-Revised: Renal to the EQ-5D-5L in patients with chronic kidney disease.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2022Trial
- EQ-5D-5L is More Responsive than EQ-5D-3L to Treatment Benefit of Cataract Surgery.The patient · 2019Trial
- Psychometric evaluation of the Disability Wellbeing Index (DWI) against the Adult Social Care Outcomes Toolkit (ASCOT) among people with disability.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026Article
- Improving the value of population health data for health policy and decision-making using machine learning algorithms in EQ-5D-5L index estimation.Scientific reports · 2026Article
- Mapping Kansas City cardiomyopathy, Seattle Angina, and minnesota living with heart failure to the MacNew-7D in patients with heart disease.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024Article
- An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values.Health economics · 2022Article
- Comparing the performance of the EQ-5D-3 L and the EQ-5D-5 L in an elderly Chinese population.Health and quality of life outcomes · 2020Article
- Mapping the kidney disease quality of life 36-item short form survey (KDQOL-36) to the EQ-5D-3L and the EQ-5D-5L in patients undergoing dialysis.The European journal of health economics : HEPAC : health economics in prevention and care · 2019Article
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Authors and funding
3 authors.
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Abstract
objectivesThis study aimed to evaluate the performance of EQ-5D data mapped from SF-12 in terms of estimating cost effectiveness in cost-utility analysis (CUA). The comparability of SF-6D (derived from SF-12) was also assessed.
methodsIncremental quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs) were calculated based on two Markov models assessing the cost effectiveness of haemodialysis (HD) and peritoneal dialysis (PD) using utility values based on EQ-5D-5L, EQ-5D using three direct-mapping algorithms and two response-mapping algorithms (mEQ-5D), and SF-6D. Bootstrap method was used to estimate the 95% confidence interval (percentile method) of incremental QALYs and ICERs with 1000 replications for the utilities.
resultsIn both models, compared to the observed EQ-5D values, mEQ-5D values expressed much lower incremental QALYs (range - 14.9 to - 33.2%) and much higher ICERs (range 17.5 to 49.7%). SF-6D also estimated lower incremental QALYs (- 29.0 and - 14.9%) and higher ICERs (40.9 and 17.5%) than did the observed EQ-5D. The 95% confidence interval of incremental QALYs and ICERs confirmed the lower incremental QALYs and higher ICERs estimated using mEQ-5D and SF-6D.
conclusionCompared to observed EQ-5D, EQ-5D mapped from SF-12 and SF-6D would under-estimate the QALYs gained in cost-utility analysis and thus lead to higher ICERs. It would be more sensible to conduct CUA studies using directly collected EQ-5D data and to designate one single preference-based measure as reference case in a jurisdiction to achieve consistency in healthcare decision-making.
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