Generic Preference-based Measures Research Articles

Measuring health-related quality of life and well-being: a head-to-head psychometric comparison of the EQ-5D-5L, ReQoL-UI and ICECAP-A.

ObjectiveThis study aimed to assess the psychometric properties of three generic preference-based measures and compare their performance in a sample of Hong Kong general population.MethodsData used for this analysis were obtained from a cross-sectional telephone-based survey in July 2020. Participants were asked to complete several measures, including The EuroQol five-dimensional five levels (EQ-5D-5L), Recovering Quality of Life-Utility Index (ReQoL-UI) and ICEpop CAPability measure for adults (ICECAP-A). Acceptability, reliability, convergent and discriminant validity of three measures were assessed as well as the agreement between these instruments.ResultsBased on data from 500 participants to the survey, a lower mean score of the ICECAP-A (mean = 0.85) was observed compared to the other two measures (meanReQoL-UI = 0.92; meanEQ-5D-5L = 0.92). All three measures showed an acceptable internal consistency reliability (Cronbach’s alpha = 0.74, 0.82 and 0.77, respectively) as well as good test–retest reliability (intra-class correlation coefficient = 0.74, 0.82 and 0.77, respectively). Correlation analyses confirmed satisfactory convergent validity and the ability of the measures to differentiate between participants with different health or from socioeconomic status groups. The Bland–Altman plot revealed poor agreement between the three measures.ConclusionsThis study confirmed that EQ-5D-5L, ReQoL-UI and ICECAP-A were psychometrically robust to measure HRQoL in the general HK population. The EQ-5D-5L was more suitable for assessing physical HRQoL, whereas the ICECAP-A and ReQoL-UI were more appropriate for measuring interventions aimed at improving people’s well-being and mental health.

Do Generic Preference-Based Measures Accurately Capture Areas of Health-Related Quality of Life Important to Individuals with Amyotrophic Lateral Sclerosis: A Content Validation Study.

ObjectiveThe objectives of this study were to 1) assess the content validity of generic preference-based measures (GPBMs), and (2) examine the convergent validity of the EuroQol 5 Dimension 5 Level (EQ-5D-5L), against the Patient Generated Index (PGI) in Amyotrophic Lateral Sclerosis (ALS).MethodsParticipants were recruited from 3 clinical sites across Canada. The PGI, EQ-5D-5L and Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) were administered through an online or hardcopy survey and scores compared for convergent validation. Domains nominated by participants as important to their health-related quality of life were generated using the PGI, classified using the International Classification of Functioning, Disability and Health (ICF) and mapped onto GPBMs to determine content coverage.ResultsFifty-two participants (N=28 female; 61.3 ± 11.6 mean age ± standard deviation (SD); 3.5 ± 2.9 mean ± SD years since diagnosis) completed this study. The top three ICF domains identified by participants were recreation and leisure, lower limb mobility, and interpersonal relationships. The Quality of Well-Being Self-Administered (QWB-SA) scale had the highest content coverage (87%) and the Health Utilities Index 3 (HUI3) had the lowest (33%). Two domains were covered by all GPBMs and no GPBM included all domains identified as important by participants. A moderate correlation coefficient of 0.52 between the PGI and EQ-5D-5L was found.ConclusionThe majority of GPBMs covered only approximately half of the domains important to individuals with ALS suggesting the need for an ALS specific preference-based measure to better reflect the health-related quality of life of this population.

PNS111 Development of the SF-6DV2 Health Utility Survey: Content Validity and Patient Preference

The SF-6Dv2 is a generic preference-based measure of health assessing health states in six domains – physical functioning, role participation, bodily pain, vitality, social function, and mental health. Scores have previously been derived from 10 items off the SF-36v2. We aimed to develop a six-item standalone SF-6Dv2 Health Utility Survey and evaluate its content validity.

Health-related quality of life in the treatment and survivorship phases of breast cancer.

e18621 Background: Understanding the health-related quality of life (HRQOL) of breast cancer during treatment and survivorship is important; however, little data are available - particularly for long-term ( > 5 year) survivors. Health utility scores anchored between 0 (death) and 1 (perfect/best possible health) have been shown to be a good proxy index score of the overall HRQOL. The aim of this study was to estimate the utilities in the treatment and survivorship of breast cancer using validated preference-based measures(PBMs). Methods: Women (18 years or older) with history of breast cancer (on/off treatment) were recruited via Love Research Army (LRA), an online community of women engaged in breast cancer research. Members of the LRA were invited to participate via email and women who self-selected to be eligible were asked to complete clinical and demographics form and two generic PBMs - EQ-5D and Short Form-12 (SF-12), and one cancer-specific PBM-European Organization for Research and Treatment of Cancer-8D (EORTC-8D). Descriptive statistics and non-parametric analysis of variance tests were used to examine differences between the survivorship groups. Results: 1,636 women aged 46 ± 10 years were included in the analysis. Mean age at primary diagnosis was 35 ± 10 years and most patients were diagnosed with breast cancer stage 0-2 (n = 1362, 83.25%). For women currently on treatments, mean utility values were: chemotherapy (EQ-5D = 0.61, SF-6D = 0.67,EORTC-8D = 0.69), radiation(EQ-5D = 0.71, SF-6D = 0.67, EORTC-8D = 0.66), hormone replacement therapy (EQ-5D = 0.82,SF-6D = 0.76,EORTC-8D = 0.85), targeted therapy (EQ-5D = 0.77, SF-6D = 0.74, EORTC-8D = 0.82), and surgery (EQ-5D = 0.81,SF-6D = 0.69, EORTC-8D = 0.78). For women diagnosed with arm lymphedema (n = 182,11%), utility values were EQ-5D = 0.79,SF-6D = 0.74, EORTC-8D = 0.82. Women who were ≤ 5 years post-primary diagnosis reported slightly lower utility values (EQ-5D = 0.82,SF-6D = 0.76,EORTC-8D = 0.84) than women who were 6-10 years (EQ-5D = 0.83,SF-6D = 0.76,EORTC-8D = 0.85; p = 0.117) post-primary diagnosis. However, when utilities for women who were ≤ 5 years post-primary diagnosis were compared to women who were 11 to 15 years (EQ-5D = 0.86,SF-6D = 0.79,EORTC-8D = 0.88) and over 15 years (EQ-5D = 0.86,SF-6D = 0.81,EORTC-8D = 0.89) post-primary diagnosis, the difference was statistically significant (p = 0.000). Women who belonged to non-White ethnic groups, had lower levels of education (Bachelors or less) and reported less than USD 50,000 annual income in the previous year reported lower utility values across all time points, after adjusting for age and cancer stage. Conclusions: This study shows that the HRQOL decline in the first five years post-primary breast cancer diagnosis persists for several years into survivorship. Further, women from ethnic minority groups and lower socioeconomic background have lower HRQOL, irrespective of their age and cancer stage.

Vignette-Based Utilities: Usefulness, Limitations, and Methodological Recommendations

Health technology assessment agencies often prefer that utilities used to calculate quality-adjusted life years in cost-utility analyses (CUAs) are derived using standardized methods, such as generic preference-based measures completed by patients in clinical trials. However, there are situations when no standardized approach is feasible or appropriate for a specific medical condition or treatment that must be represented in a CUA. When this occurs, vignette-based methods are often used to estimate utilities. A vignette (sometimes called a “scenario,” “health state description,” “health state vignette,” or “health state”) is a description of a health state that is valued in a preference elicitation task to obtain a utility estimate. This method is sometimes the only feasible way to estimate utilities representing a concept that is important for a CUA. Consequently, vignette-based studies continue to be conducted and published, with the resulting utilities used in economic models to inform decision making about healthcare resource allocation. Despite the potential impact of vignette-based utilities on medical decision making, there is no published guidance or review of this methodology. This article provides recommendations for researchers, health technology assessment reviewers, and policymakers who may be deciding whether to use vignette-based methods, designing a vignette study, using vignette-based utilities in a CUA, or evaluating a CUA that includes vignette-based utilities. Recommendations are provided on: (A) when to use vignette-based utilities, (B) methods for developing vignettes, (C) valuing vignettes, (D) use of vignette-based utilities in models, and (E) limitations of vignette methods.

Economic Evaluations of Pharmacologic Treatment for Opioid Use Disorder: A Systematic Literature Review

ObjectiveThe crisis of opioid use puts a strain on resources in the United States and worldwide. There are 3 US Food and Drug Administration–approved medications for treatment of opioid use disorder: methadone, buprenorphine, and injectable extended-release naltrexone (XR-NTX). The comparative effectiveness and cost vary considerably among these 3 medications. Economic evaluations provide evidence that help stakeholders efficiently allocate scarce resources. Our objective was to summarize recent health economic evidence of pharmacologic treatment of opioid use disorder interventions. MethodsWe searched PubMed for peer-reviewed studies in English from August 2015 through December 2019 as an update to a 2015 review. We used the Drummond checklist to evaluate and categorize economic evaluation study quality. We summarized results by economic evaluation methodology and pharmacologic treatment modality. ResultsWe identified 105 articles as potentially relevant and included 21 (4 cost-offset studies and 17 cost-effectiveness/cost-benefit studies). We found strengthened evidence on buprenorphine and methadone, indicating that these treatments are economically advantageous compared with no pharmacotherapy, but found limited evidence on XR-NTX. Only half of the cost-effectiveness studies used a generic preference-based measure of effectiveness, limiting broad comparison across diseases/disorders. The disease/disorder-specific cost-effectiveness measures vary widely, suggesting a lack of consensus on the value of substance use disorder treatment. ConclusionWe found studies that provide new evidence supporting the cost-effectiveness of buprenorphine compared with no pharmacotherapy. We found a lack of evidence supporting superior economic value for buprenorphine versus methadone, suggesting that both are attractive alternatives. Further economic research is needed on XR-NTX, as well as other emerging pharmacotherapies, treatment modalities, and dosage forms.

Deriving a Preference-Based Measure for People With Duchenne Muscular Dystrophy From the DMD-QoL

ObjectivesThis study generates a preference-based measure for capturing the quality of life of people with Duchenne muscular dystrophy (DMD) from a new measure of quality of life, DMD-QoL. MethodsA health state classification system was derived from the DMD-QoL based on psychometric performance of items, factor analysis, and item response theory analysis. Preferences for health states described by the classification system were elicited using an online discrete choice experiment survey with life years as an additional attribute, from members of the UK general population (n = 1043). Discrete choice experiment data was modeled using a conditional fixed-effects logit model and utility estimates were directly anchored on the 1 to 0 full health-dead scale. ResultsThe health state classification system has 8 dimensions: mobility, difficulty using hands, difficulty breathing, pain, tiredness, worry, participation, and feeling good about yourself. The standard model had mostly statistically significant coefficients and reflected the instrument’s monotonic structure. However, 2 dimensions had inconsistent coefficients (where utility increased as health worsened) and a consistent model was estimated that merged adjacent inconsistent severity levels. The best state defined by the classification system has a value of 1 and the worst state has a value of −0.559. ConclusionThe modeled results enable DMD-QoL-8D utility values to be generated using DMD-QoL or DMD-QoL-8D data to generate QALYs for people with DMD. QALYs can then be used to inform economic models of the cost-effectiveness of interventions in DMD. Future research comparing the psychometric performance of DMD-QoL-8D to existing generic preference-based measures, including EQ-5D-5L, is recommended.

What is the best approach to adopt for identifying the domains for a new measure of health, social care and carer-related quality of life to measure quality-adjusted life years? Application to the development of the EQ-HWB?

Economic evaluation combines costs and benefits to support decision-making when assessing new interventions using preference-based measures to measure and value benefits in health or health-related quality of life. These health-focused instruments have limited ability to capture wider impacts on informal carers or outcomes in other sectors such as social care. Sector-specific instruments can be used but this is problematic when the impact of an intervention straddles different sectors.An alternative approach is to develop a generic preference-based measure that is sufficiently broad to capture important cross-sector outcomes. We consider the options for the selection of domains for a cross-sector generic measure including how to identify domains, who should provide information on the domains and how this should be framed. Beyond domain identification, considerations of criteria and stakeholder needs are also identified.This paper sets out the case for an approach that relies on the voice of patients, social care users and informal carers as the main source of domains and describes how the approach was operationalised in the ‘Extending the QALY’ project which developed the new measure, the EQ-HWB (EQ health and wellbeing instrument). We conclude by discussing the strengths and limitations of this approach. The new measure should be sufficiently generic to be used to consistently evaluate health and social care interventions, yet also sensitive enough to pick up important changes in quality of life in patients, social care users and carers.

Response Mapping Methods to Estimate the EQ-5D-5L From the Western Ontario McMaster Universities Osteoarthritis in Patients With Hip or Knee Osteoarthritis

ObjectivesThe mapping technique can estimate generic preference-based measure scores through a specific measure that cannot be used in economic evaluations. This study compared 2 response mapping methods to estimate EQ-5D-5L scores using the Western Ontario McMaster Universities Osteoarthritis (WOMAC). MethodsThe sample consisted of 758 patients with the hip or knee osteoarthritis recruited in baseline. Bayesian networks (BN) and multinomial logistic regression (ML) were used as response mapping models. Predictions were obtained using the 6-month follow-up as a validation sample. The mean absolute error, mean squared error, deviation from the root mean squared error and intraclass correlation coefficient were calculated as precision measures. ResultsThere was 5.5% of missing data, which was removed. The mean age was 69.6 years (standard deviation = 10.5), with 61.6% of women. The BN model presented lower mean absolute error, mean squared error, root mean squared error and higher intraclass correlation coefficient than the ML model. Only the WOMAC items pain and physical function items were related with the EQ-5D-5L dimensions. ConclusionBN response mapping models are more robust methods, with better prediction results, than ML models. The BN model also provided a graphic representation of the dependency relationships between the EQ-5D-5L dimensions and the different WOMAC items that could be useful in the clinical investigation of patients with hip or knee osteoarthritis.

Psychometric Properties of Preference-Based Measures for Economic Evaluation in Amyotrophic Lateral Sclerosis: A Systematic Review.

Objective The aim of this review was to synthesize the psychometric properties of generic preference-based measures (PBMs) of health-related quality of life (HRQL) in Amyotrophic Lateral Sclerosis (ALS). Methods A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Four databases were searched from inception to April 2019: OVID Medline, Embase, PsycINFO, and CINAHL. Studies were included if (1) the sample represented individuals with ALS, (2) a generic PBM was utilized and reported on, and (3) information on the psychometric property of a generic PBM was provided. Results Ninety-one articles were screened, and 39 full-text articles were reviewed. Seven full-text articles were included in this review. The mean age of participants ranged from 58.1 to 63.8 years, and mean time since diagnosis ranged from 20.5 to 44.6 months. Two generic PBMs were found, the EQ-5D-3L (n = 6) and the Quality of Well-Being Self-Administered (QWB-SA) scale (n = 1). Convergent validity of the EQ-5D-3L was large against a global scale of self-perceived health (r = 0.60) and small to large against ALS specific HRQL measures (r = 0.19 to 0.75). For the QWB-SA scale, correlations were small against a generic measure (r = 0.21) and large against ALS specific measures (r = 0.55). The EQ-5D-3L discriminated across different disease severity; however, floor effects were reported. Conclusion This review highlights the need for more rigorously designed studies to assess the psychometric properties of generic PBMs in ALS and the development of an ALS specific PBM that adequately reflects the health concerns of individuals with ALS.

An international mixed methods study to develop a new preference-based measure for women with breast cancer: the BREAST-Q Utility module

BackgroundGeneric preference-based measures (PBM), though commonly used, may not be optimal for use in economic evaluations of breast cancer interventions. No breast cancer-specific PBM currently exists, and the generic PBMs fail to capture the unique concerns of women with breast cancer (e.g., body image, appearance, treatment-specific adverse effects). Hence, the objective of this study was to develop a breast cancer-specific PBM, the BREAST-Q Utility module.MethodsWomen diagnosed with breast cancer (stage 0–4, any treatment) were recruited from two tertiary hospitals in Canada and one in the US. The study followed an exploratory sequential mixed methods approach, whereby semi-structured interviews were conducted and at the end of the interview, participants were asked to list their top five health-related quality of life (HRQOL) concerns and to rate the importance of each item on the BREAST-Q. Interviews were audio-recorded, transcribed verbatim, and coded. Constant comparison was used to refine the codes and develop a conceptual framework. Qualitative and quantitative data were triangulated to develop the content of the Utility module that was refined through 2 rounds of cognitive debriefing interviews with women diagnosed with breast cancer and feedback from experts.ResultsInterviews were conducted with 57 women aged 55 ± 10 years. A conceptual framework was developed from 3948 unique codes specific to breasts, arms, abdomen, and cancer experience. Five top-level domains were HRQOL (i.e., physical, psychological, social, and sexual well-being) and appearance. Data from the interviews, top 5 HRQOL concerns, and BREAST-Q item ratings were used to inform dimensions for inclusion in the Utility module. Feedback from women with breast cancer (N = 9) and a multidisciplinary group of experts (N = 27) was used to refine the module. The field-test version of the HSCS consists of 10 unique dimensions. Each dimension is measured with 1 or 2 candidate items that have 4–5 response levels each.ConclusionThe field-test version of the BREAST-Q Utility module was derived from extensive patient and expert input. This comprehensive approach ensured that the content of the Utility module is relevant, comprehensive, and includes concerns that matter the most to women with breast cancer.

Estimating a Preference-Based Index for Mental Health From the Recovering Quality of Life Measure: Valuation of Recovering Quality of Life Utility Index

BackgroundThere are increasing concerns about the appropriateness of generic preference-based measures to capture health benefits in the area of mental health. ObjectivesThe aim of this study is to estimate preference weights for a new measure, Recovering Quality of Life (ReQoL-10), to better capture the benefits of mental healthcare. MethodsPsychometric analyses of a larger sample of mental health service users (n = 4266) using confirmatory factor analyses and item response theory were used to derive a health state classification system and inform the selection of health states for utility assessment. A valuation survey with members of the UK public representative in terms of age, sex, and region was conducted using face-to-face interviewer administered time-trade-off with props. A series of regression models were fitted to the data and the best performing model selected for the scoring algorithm. ResultsThe ReQoL-Utility Index (UI) classification system comprises 6 mental health items and 1 physical health item. Sixty-four health states were valued by 305 participants. The preferred model was a random effects model, with significant and consistent coefficients and best model fit. Estimated utilities modeled for all health states ranged from −0.195 (state worse than dead) to 1 (best possible state). ConclusionsThe development of the ReQoL-UI is based on a novel application of item response theory methods for generating the classification system and selecting health states for valuation. Conventional time-trade-off was used to elicit utility values that are modeled to enable the generation of QALYs for use in cost-utility analysis of mental health interventions.

Preference-based measurement of mobility-related quality of life: developing the MobQoL-7D health state classification system

Purpose Generic preference-based measures often lack validity in states of impaired mobility. Our aim was to derive a novel health state classification system from the MobQoL tool, for the purpose of preference-based measurement of states of impaired mobility. Materials and methods Data were collected through online and postal surveys. Respondents were recruited through the NHS, charitable organisations and HealthWise Wales. Statistical and psychometric analyses were used to assess the validity and reliability of the MobQoL tool. Exploratory factor analysis and Rasch analysis were used to determine dimensional structure and to select items for the MobQoL health state classification system. Results Three hundred and forty-two respondents completed the survey. Respondents had a wide range of different mobility impairments. Nine of the MobQoL items demonstrated adequate validity and reliability. Exploratory factor analysis and Rasch analysis confirmed two sub-scales within the item structure: 1) physical and role functioning, and 2) mental wellbeing. Seven items were found to have adequate model fit and were retained in the final health state classification system, called the MobQoL-7D. Conclusions The MobQoL-7D contains seven dimensions of mobility-related quality of life: accessibility, contribution, pain/discomfort, independence, self-esteem, mood/emotions and anxiety. Population level preference weights are now needed for different states of mobility impairment. IMPLICATIONS FOR REHABILITATION Mobility impairment has distinct impacts on mental wellbeing and physical/role functioning. The MobQoL-7D will facilitate accurate preference-based outcome measurement in populations with impaired mobility, which in turn will promote methods of economic evaluation in this context. MobQoL-7D offers a concise and valid tool for rehabilitation professionals to measure and monitor mobility-related quality of life as part of routine clinical practice.

Valuation study for a preference-based quality of life measure for dental caries (Dental Caries Utility Index - DCUI) among Australian adolescents - study protocol

IntroductionA new health state classification system has been developed for dental caries - Dental Caries Utility Index (DCUI) to facilitate the assessment of oral health interventions in the cost-utility analysis...

Measuring quality of life for people with common mental health problems

Background It is important to identify valid and acceptable outcome measures so that interventions evaluating common mental health problems can be assessed appropriately. Some advocate the use of generic preference-based measures claimed to be applicable for all health interventions, but others argue that they are insensitive for common mental health problems. The aim of this paper is to evaluate the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM), to be used in cost-effectiveness studies in people with common mental health problems. Method The CORE-OM measure was tested for completeness, acceptability and responsiveness in a pilot study. Analyses for missing data, distribution of scores, and standardised response means (SRMs) were calculated. Results Missing data did not exceed 5% for any of the CORE-6D items both at baseline and follow-up. The overall comprehension rate was high, and only 19 participants (14%) requested clarifications to complete the questionnaire. As expected in a feasibility study, there was a small and non-significant SRM. Conclusion CORE-OM is a valid and acceptable instrument to evaluate quality of life for people with common mental health problems. More research is needed with larger sample sizes to compare CORE-6D with other condition specific quality of life instruments.

EQ-5D-5L and SF-6Dv2 utility scores in people living with chronic low back pain: a survey from Quebec.

ObjectiveTo describe how chronic low back pain (CLBP) impacts on utility scores and which patients’ characteristics most affect these scores in the province of Quebec.SettingsProvince of Quebec, Canada.Participants569 adult patients with CLBP.Methods and outcomesAn online survey on low back pain was conducted between October 2018 and January 2019. The EuroQol Five Dimensions (EQ-5D-5L) and the Short Form Six Dimensions version 2 (SF-6Dv2) are two generic preference-based measures used to evaluate health-related quality of life (HRQoL) and provide quality-adjusted life-year utility values.ResultsThe number of subjects who agreed to participate was 610, but 41 were excluded because 8 had low back pain for less than 3 months and 33 did not start the survey. A total of 569 subjects were analysed, but only 410 completed the survey up to the EQ-5D-5L or SF-6Dv2 sections. Median (range) of EQ-5D-5L was 0.622 (−0.072 to 0.905), and mean (range) of SF-6Dv2 and EQ-Visual Analogue Scale was 0.561 (0.301–0.829) and 51.0 (0–100), respectively. In all multivariate models, health or life satisfaction increased the health utility score, while pain reduced it. Co-occurring health problems were present for a majority (68%) of participants, mainly fatigue/insomnia (57.4%), musculoskeletal disorder (56.2%) and mental disorder (44%).ConclusionThis study provided utility scores with EQ-5D-5L and SF-6Dv2 in patients with CLBP in Quebec, and results were similar to other studies conducted in different settings. These values were well below those reported in the Quebec general population and highlight the association between CLBP and HRQoL.

Filling the psycho-social gap in the EQ-5D: the empirical support for four bolt-on dimensions

PurposeThe EQ-5D is the most widely applied generic preference-based measure (GPBM) of health-related quality of life (HRQoL). Much concern has been raised that its descriptive system is lacking psycho-social dimensions. A recent paper in this journal provided theoretical support for four dimensions to fill this gap. The current paper aims to provide empirical support for these suggested bolt-on dimensions to the EQ-5D.MethodsWe use data from the comprehensive Multi-Instrument-Comparison (MIC) study. The four proposed bolt-on dimensions (Vitality, Sleep, Social Relationships, and Community Connectedness) were selected from the Assessment of Quality of Life (AQoL)-8D. We investigate the relative importance of these four dimensions as compared to the five EQ-5D-5L dimensions on explaining HRQoL (measured by a visual analogue scale; N = 7846) or global life satisfaction (measured by the Satisfaction With Life Scale; N = 8005), using the Shorrocks-Shapely decomposition analysis. Robustness analyses on Vitality was conducted using data from the United States National Health Measurement Study (NHMS) (N = 3812).ResultsAll five EQ-5D-5L dimensions and four bolt-on dimensions significantly explained the variance of HRQoL. Among them, Vitality was found to be the most important dimension with regard to the HRQoL (relative contribution based on the Shorrocks-Shapely decomposition of R2: 23.0%), followed by Usual Activities (15.1%). Self-Care was the least important dimension (relative contribution: 5.4%). As a comparison, when explaining global life satisfaction, Social Relationships was the most important dimension (relative contribution: 24.0%), followed by Anxiety/Depression (23.2%), while Self-Care remained the least important (relative contribution: 1.6%). The importance of the Vitality dimension in explaining HRQoL was supported in the robustness analysis using the NHMS data (relative contribution: 23.7%).ConclusionsWe provide empirical support for complementing the current EQ-5D-5L descriptive system with a coherent set of four bolt-on dimensions that will fill its psycho-social gap. Such an extended health state classification system would in particular be relevant for programme evaluations within the expanding fields of mental health and community care.

Measurement properties of preference-based measures for economic evaluation in COPD: a systematic review.

Preference-based measures can provide measurements of health-related quality of life and be utilized for cost-effectiveness analyses of interventions in individuals with chronic obstructive pulmonary disease (COPD). The purpose of this study is to evaluate whether generic preference-based measures are reliable, valid, and responsive in COPD. A systematic review was performed using the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) guidelines. Three databases were searched: MEDLINE, EMBASE, and CINAHL. Studies were included if the sample represented individuals with COPD and the aim was to evaluate one or more psychometric properties or the interpretability of generic preference-based measures. Six hundred and sixty-seven abstracts were screened, 65 full-text articles were reviewed and 24 articles met the inclusion criteria. Measures which emerged from the search were the EQ-5D, the SF-6D, the Quality of Well-being scale, the 15D, and the Health Utilities Index 3. Evidence for the test-retest reliability of these measures was limited. Construct validity of the measures was well supported with correlations with generic health profiles being 0.37-0.68, and correlations with COPD-specific health profiles being 0.53-0.75. Evidence for known-groups validity of these measures was poor and data on responsiveness were mixed. Generic preference-based measures' sensitivity to change and ability to discriminate between different disease severities in COPD was poorly supported. Future research may consider examining the development of COPD-specific preference-based measures that may allow for a more accurate detection of change and discrimination among disease severities to facilitate cost-effectiveness evaluations.

Mapping clinical outcomes to generic preference-based outcome measures: development and comparison of methods.

Cost-effectiveness analysis using quality-adjusted life-years as the measure of health benefit is commonly used to aid decision-makers. Clinical studies often do not include preference-based measures that allow the calculation of quality-adjusted life-years, or the data are insufficient. 'Mapping' can bridge this evidence gap; it entails estimating the relationship between outcomes measured in clinical studies and the required preference-based measures using a different data set. However, many methods for mapping yield biased results, distorting cost-effectiveness estimates. Develop existing and new methods for mapping; test their performance in case studies spanning different preference-based measures; and develop methods for mapping between preference-based measures. Fifteen data sets for mapping from non-preference-based measures to preference-based measures for patients with head injury, breast cancer, asthma, heart disease, knee surgery and varicose veins were used. Four preference-based measures were covered: the EuroQoL-5 Dimensions, three-level version (n = 11), EuroQoL-5 Dimensions, five-level version (n = 2), Short Form questionnaire-6 Dimensions (n = 1) and Health Utility Index Mark 3 (n = 1). Sample sizes ranged from 852 to 136,327. For mapping between generic preference-based measures, data from FORWARD, the National Databank for Rheumatic Diseases (which includes the EuroQoL-5 Dimensions, three-level version, and EuroQoL-5 Dimensions, five-level version, in its 2011 wave), were used. Mixture-model-based approaches for direct mapping, in which the dependent variable is the health utility value, including adaptations of methods developed to model the EuroQoL-5 Dimensions, three-level version, and beta regression mixtures, were developed, as were indirect methods, in which responses to the descriptive systems are modelled, for consistent multidirectional mapping between preference-based measures. A highly flexible approach was designed, using copulas to specify the bivariate distribution of each pair of EuroQoL-5 Dimensions, three-level version, and EuroQoL-5 Dimensions, five-level version, responses. A range of criteria for assessing model performance is proposed. Theoretically, linear regression is inappropriate for mapping. Case studies confirm this. Flexible, direct mapping methods, based on different variants of mixture models with appropriate underlying distributions, perform very well for all preference-based measures. The precise form is important. Case studies show that a minimum of three components are required. Covariates representing disease severity are required as predictors of component membership. Beta-based mixtures perform similarly to the bespoke mixture approaches but necessitate detailed consideration of the number and location of probability masses. The flexible, bi-directional indirect approach performs well for testing differences between preference-based measures. Case studies drew heavily on EuroQoL-5 Dimensions. Indirect methods could not be undertaken for several case studies because of a lack of coverage. These methods will often be unfeasible for preference-based measures with complex descriptive systems. Mapping requires appropriate methods to yield reliable results. Evidence shows that widely used methods such as linear regression are inappropriate. More flexible methods developed specifically for mapping show that close-fitting results can be achieved. Approaches based on mixture models are appropriate for all preference-based measures. Some features are universally required (such as the minimum number of components) but others must be assessed on a case-by-case basis (such as the location and number of probability mass points). Further research is recommended on (1) the use of the monotonicity concept, (2) the mismatch of trial and mapping distributions and measurement error and (3) the development of indirect methods drawing on methods developed for mapping between preference-based measures. This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 34. See the NIHR Journals Library website for further project information. This project was also funded by a Medical Research Council grant (MR/L022575/1).

Discrete choice experiments to generate utility values for multi-attribute utility instruments: a systematic review of methods.

In recent years, discrete choice experiments (DCEs) have become frequently used to generate utility values, but there are a diverse range of approaches to do this. The primary focus of this systematic review is to summarise the methods used for the design and analysis of DCEs when estimating utility values in both generic and condition-specific preference-based measures. Published literature using DCEs to estimate utility values from preference-based instruments were identified from MEDLINE, Embase, Cochrane Library and CINAHL using PRISMA guidelines. To assess the different DCE methods, standardised information was extracted from the articles including the DCE design method, the number of choice sets, the number of DCE pairs per person, randomisation of questions, analysis method, logical consistency tests and techniques for anchoring utilities. The CREATE checklist was used to assess the quality of the studies. A total of 38 studies with samples from the general population, students and patients were included. Values for health states described using generic multi attribute instruments (MAUIs) (especially the EQ-5D) were the most commonly explored using DCEs. The studies showed considerable methodology and design diversity (number of alternatives, attributes, sample size, choice task presentation and analysis). Despite these differences, the quality of articles reporting the methods used for the DCE was generally high. DCEs are an important approach to measure utility values for both generic and condition-specific instruments. However, a gold standard method cannot yet be recommended.