A new version of the EQ-5D, the EQ-5D-5L, is available. The aim of this study is to produce a value set to support use of EQ-5D-5L data in decision-making. The study design followed an international research protocol. Randomly selected members of the English general public completed 10 time trade-off and 7 discrete choice experiment tasks in face-to-face interviews. A 20-parameter hybrid model was used to combine time trade-off and discrete choice experiment data to generate values for the 3,125 EQ-5D-5L health states. Valuation data are available for 996 respondents. Face validity of the data has been demonstrated, with more severe health states generally given lower values. Problems with pain/discomfort and anxiety/depression received the greatest weight. Compared to the existing EQ-5D-3L value set, there are considerably fewer "worse than dead" states (5.1%, compared with over one third), and the minimum value is higher. Values range from -0.285 (extreme problems on all dimensions) to 0.950 (for health states 11211 and 21111). Results have important implications for users of the EQ-5D-5L both in England and internationally. Quality-adjusted life year gains from interventions seeking to improve very poor health may be smaller using this value set and may previously have been overestimated.

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Valuing health-related quality of life: An EQ-5D-5L value set for England.

The terms health, health-related quality of life (HRQoL), and quality of life (QoL) are used interchangeably. Given that these are three key terms in the literature, their appropriate and clear use is important. This paper reviews the history and definitions of the terms and considers how they have been used. It is argued that the definitions of HRQoL in the literature are problematic because some definitions fail to distinguish between HRQoL and health or between HRQoL and QoL. Many so-called HRQoL questionnaires actually measure self-perceived health status and the use of the phrase QoL is unjustified. It is concluded that the concept of HRQoL as used now is confusing. A potential solution is to define HRQoL as the way health is empirically estimated to affect QoL or use the term to only signify the utility associated with a health state.

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Health, Health-Related Quality of Life, and Quality of Life: What is the Difference?

Over the period 1987-1991 an inter-disciplinary five-country group developed the EuroQol instrument, a five-dimensional three-level generic measure subsequently termed the 'EQ-5D'. It was designed to measure and value health status. The salient features of its development and its consolidation and expansion are discussed. Initial expansion came, in particular, in the form of new language versions. Their development raised translation and semantic issues, experience with which helped feed into the design of two further instruments, the EQ-5D-5L and the youth version EQ-5D-Y. The expanded usage across clinical programmes, disease and condition areas, population surveys, patient-reported outcomes, and value sets is outlined. Valuation has been of continued relevance for the Group as this has allowed its instruments to be utilised as part of the economic appraisal of health programmes and their incorporation into health technology assessments. The future of the Group is considered in the context of: (1) its scientific strategy, (2) changes in the external environment affecting the demand for EQ-5D, and (3) a variety of issues it is facing in the context of the design of the instrument, its use in health technology assessment, and potential new uses for EQ-5D outside of clinical trials and technology appraisal.

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EQ-5D and the EuroQol Group: Past, Present and Future.

BACKGROUND: Generic preference-based measures of health like the EQ-5D and SF-6D(®) are increasingly being used in economic evaluation and outcome assessment. However, there are concerns as to whether or not these generic measures are appropriate for use in people with mental health problems. OBJECTIVES: The EQ-5D and SF-36(®) (including its derivatives the SF-12(®) and SF-6D) were assessed using the psychometric criteria of validity and responsiveness using quantitative and qualitative methods. Another aim was to estimate mapping functions between the EQ-5D and SF-6D and condition-specific measures, where appropriate. DESIGN: Four studies were undertaken to examine the appropriateness of the measures: (1) a systematic review of quantitative evidence on validity and responsiveness; (2) a further quantitative assessment of these criteria using existing data sets; (3) a review of qualitative research on the quality of life of people with mental health problems; and (4) qualitative semistructured interviews of people with a full range of problems. A fifth study estimated mapping functions between mental health-specific measures and the EQ-5D and SF-6D. SETTING: A choice of venue was offered for the interviews including the participant's own home, a room at the university or a centre frequently used by mental health services. PARTICIPANTS: The interviews were undertaken with 19 people with a broad range of mental health problems at varying levels of severity. MAIN OUTCOME MEASURES: The reviews included the EQ-5D and SF-36 (and the SF-12 and SF-6D). The psychometric analysis included the Hospital Anxiety and Depression Scale (HADS), Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM), Generalised Anxiety Disorder Assessment (GAD-7), General Health Questionnaire (GHQ-12) and Patient Health Questionnaire (PHQ-9). RESULTS: (1) and (2) The EQ-5D and SF-36 achieved an adequate level of performance in depression, and to some extent in anxiety and personality disorder. Results from the psychometric analyses in schizophrenia and bipolar disorder have been more mixed. (3) A framework analysis of 13 studies identified six major themes. (4) The interview data fitted the themes from the review well and resulted in minor modifications to the themes. The final set of themes comprised: well-being and ill-being; control, autonomy and choice; self-perception; belonging; activity; hope and hopelessness; and physical health. CONCLUSIONS: The EQ-5D and SF-36 achieved mixed results in the quantitative testing against psychometric criteria. The qualitative analysis suggests this is because they provide a very limited coverage of themes identified by people with mental health problems. Recommendations for future work include the development of new preference-based measures in mental health that are based on, or substantially revise, an existing measure.

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A systematic review, psychometric analysis and qualitative assessment of generic preference-based measures of health in mental health populations and the estimation of mapping functions from widely used specific measures.

BACKGROUND: Disorders of bone metabolism, most notably osteoporosis, are highly prevalent and predispose to fractures, causing high patient morbidity and mortality. Diagnosis and monitoring of bone metabolic defects can present a major challenge as these disorders are largely asymptomatic and radiographic measures of bone mass respond slowly to changes in bone physiology. CONTENT: Bone turnover markers (BTMs) are a series of protein or protein derivative biomarkers released during bone remodeling by osteoblasts or osteoclasts. BTMs can offer prognostic information on fracture risk that supplements radiographic measures of bone mass, but testing using BTMs has to take into account the large number of preanalytic factors and comorbid clinical conditions influencing BTM levels. BTMs respond rapidly to changes in bone physiology, therefore, they have utility in determining patient response to and compliance with therapies for osteoporosis. SUMMARY: BTMs are a useful adjunct for the diagnosis and therapeutic monitoring of bone metabolic disorders, but their use has to be tempered by the known limitations in their clinical utility and preanalytic variables complicating interpretation.

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Bone Turnover Markers in the Diagnosis and Monitoring of Metabolic Bone Disease.

Background: The National Institute for Health and Care Excellence recommends the use of generic
preference-based measures (GPBMs) of health for its Health Technology Assessments (HTAs). However,
these data may not be available or appropriate for all health conditions.
Objectives: To determine whether GPBMs are appropriate for some key conditions and to explore
alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate.
Design: The project was conducted in three stages: (1) A systematic review of the psychometric properties
of three commonly used GPBMs [EQ-5D, SF-6D and Health Utilities Index Mark 3 (HUI3)] in four broadly
defined conditions: visual impairment, hearing impairment, cancer and skin conditions. (2) Potential
modelling approaches to ‘map’ EQ-5D values from condition-specific and clinical measures of health
[European Organisation for Research and Treatment of Cancer Quality-of-life Questionnaire Core 30
(EORTC QLQ-C30) and Functional Assessment of Cancer Therapy – General Scale (FACT-G)] are compared
for predictive ability and goodness of fit using two separate data sets. (3) Three potential extensions to the
EQ-5D are developed as ‘bolt-on’ items relating to hearing, tiredness and vision. They are valued using the
time trade-off method. A second valuation study is conducted to fully value the EQ-5D with and without
the vision bolt-on item in an additional sample of 300 people.
Setting: The valuation surveys were conducted using face-to-face interviews in the respondents’ homes.
Participants: Two representative samples of the UK general population from Yorkshire (n = 600).
Interventions: None.
Main outcome measures: Comparisons of EQ-5D, SF-6D and HUI3 in four conditions with various
generic and condition-specific measures. Mapping functions were estimated between EORTC QLQ-C30
and FACT-G with EQ-5D. Three bolt-ons to the EQ-5D were developed: EQ + hearing/vision/tiredness.
A full valuation study was conducted for the EQ + vision.
Results: (1) EQ-5D was valid and responsive for skin conditions and most cancers; in vision, its
performance varied according to aetiology; and performance was poor for hearing impairments. The HUI3
performed well for hearing and vision disorders. It also performed well in cancers although evidence was
limited and there was no evidence in skin conditions. There were limited data for SF-6D in all four
conditions and limited evidence on reliability of all instruments. (2) Mapping algorithms were estimated to
predict EQ-5D values from alternative cancer-specific measures of health. Response mapping using all the
domain scores was the best performing model for the EORTC QLQ-C30. In an exploratory analysis, a
limited dependent variable mixture model performed better than an equivalent linear model. In the full
analysis for the FACT-G, linear regression using ordinary least squares gave the best predictions followed
by the tobit model. (3) The exploratory valuation study found that bolt-on items for vision, hearing and
tiredness had a significant impact on values of the health states, but the direction and magnitude of
differences depended on the severity of the health state. The vision bolt-on item had a statistically
significant impact on EQ-5D health state values and a full valuation model was estimated.
Conclusions: EQ-5D performs well in studies of cancer and skin conditions. Mapping techniques
provide a solution to predict EQ-5D values where EQ-5D has not been administered. For conditions
where EQ-5D was found to be inappropriate, including some vision disorders and for hearing, bolt-ons
provide a promising solution. More primary research into the psychometric properties of the generic
preference-based measures is required, particularly in cancer and for the assessment of reliability.
Further research is needed for the development and valuation of bolt-ons to EQ-5D.
Funding: This project was funded by the UK Medical Research Council (MRC) as part of the MRC-NIHR
methodology research programme (reference G0901486) and will be published in full in Health Technology
Assessment; Vol. 18, No. 9. See the NIHR Journals Library website for further project information.

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Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: a systematic review, statistical modelling and survey

A Devianee Keetharuth

Papers

Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: a systematic review, statistical modelling and survey