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Background: Assessing health-related quality of life in dementia poses challenges due to patients’ cognitive impairment. It is unknown if the newly introduced EQ-5D five-level version (EQ-5D-5L) is superior to the 3-level version (EQ-5D-3L) in this cognitively impaired population group. Objective: To assess the psychometric properties of the EQ-5D-5L in comparison to the EQ-5D-3L in patients living with dementia (PwD). Methods: The EQ-5D-3L and EQ-5D-5L were assessed via interviews with n = 78 PwD at baseline and three and six months after, resulting in 131 assessments. The EQ-5D-3L and EQ-5D-5L were evaluated in terms of acceptability, agreement, ceiling effects, redistribution properties and inconsistency, informativity as well as convergent and discriminative validity. Results: Mean index scores were higher for the EQ-5D-5L than the EQ-5D-3L (0.70 versus 0.64). Missing values occurred more frequently in the EQ-5D-5L than the EQ-5D-3L (8%versus 3%). Agreement between both measures was acceptable but poor in PwD with moderate to severe cognitive impairment. The index value’s relative ceiling effect decreased from EQ-5D-3L to EQ-5D-5L by 17%. Inconsistency was moderate to high (13%). Absolute and relative informativity increased in the EQ-5D-5L compared to the 3L. The EQ-5D-5L demonstrated a lower discriminative ability and convergent validity, especially in PwD with moderate to severe cognitive deficits. Conclusion: The EQ-5D-5L was not superior as a self-rating instrument due to a lower acceptability and discriminative ability and a high inconsistency, especially in moderate to severe dementia. The EQ-5D-3L had slightly better psychometric properties and should preferably be used as a self-rating instrument in economic evaluations in dementia.

BackgroundGeneric preference-based measures (GPBMs) are health-related quality of life (HRQoL) measures commonly used to evaluate the cost-utility of interventions in healthcare. However, the degree to which the content of GPBMs reflect the HRQoL of individuals with chronic obstructive pulmonary disease (COPD) has not yet been assessed. The purpose of this study was to examine the content and convergent validity of GPBMs in people with COPD.MethodsCOPD patients were recruited from healthcare centers in Ontario, Canada. The Patient-Generated Index (PGI) (an individualized HRQoL measure) and the RAND-36 (to obtain SF-6D scores; a GPBM) were administered. Life areas nominated with the PGI were coded using the International Classification of Functioning Disability and Health and mapped onto GPBMs.ResultsWe included 60 participants with a mean age of 70 and FEV1% predicted of 43. The mean PGI score was 34.55/100 and the top three overarching areas that emerged were: ‘mobility’ (25.93%), ‘recreation and leisure’ (25.19%) and ‘domestic life’ (19.26%). Mapping of the nominated areas revealed that the Quality of Well-Being scale covered the highest number of areas (84.62%), Health Utilities Indices covered the least (15.38% and 30.77%) and other GPBMs covered between 46 and 62%. A correlation of 0.32 was calculated between the SF-6D and the PGI.ConclusionsThe majority of GPBMs covered approximately half of the areas reported as being important to individuals with COPD. When areas relevant to COPD are not captured, HRQoL scores generated by these measures may inaccurately reflect patients’ values and affect cost-effectiveness decisions.

Preference-based measures allow patients to report their level of health, and the responses are then scored using preference weights from a representative general population sample for use in cost utility analysis. The development process of new preference-based measures should ensure that valid items are selected to reflect the constructs of interest included in the measure and that are suitable for use in preference-elicitation exercises. Existing criteria on patient-reported outcome measures (PROMs) development were reviewed, and additional considerations were taken into account in order to generate criteria to support development of new preference-based measures. Criteria covering 22 different aspects related to item selection for preference-based measures are presented. These include criteria related to how items are phrased to ensure accurate completion, the coverage of items in terms of range of domains as well as focus on current outcomes and whether items are suitable for valuation. The criteria are aimed at supporting the development of new preference-based measures with discussion to ensure that even where there is conflict between criteria, issues have been considered at the item selection stage. This would minimize problems at valuation stage by harmonizing established criteria and expanding lists to reflect the unique characteristics of preference-based measures.

Background Assessing the cost-effectiveness of interventions for people with dementia, based on cost per quality-adjusted life years (QALYs) gained, requires that the measures used to derive QALYs are preference-based whilst also being valid, feasible to use, comprehensible and acceptable for people with dementia. The aim of this study was to assess the content and face validity of six preference-based measures (PBMs) within the context of dementia. Methods Qualitative focus groups and interviews were conducted with community-dwelling individuals with mild dementia and carers of people with dementia. After exploring participants’ understanding of ‘quality of life’ (QoL), six PBMs were assessed for content and face validity: two measures assessing health-related QoL (EQ-5D-5L and AQoL-8D); two covering broader aspects of capability wellbeing and social care-related QoL (ICECAP-O and ASCOT); and two dementia-specific QoL measures (DEMQOL-U and AD-5D). A random mix of one health-related QoL measure, one wellbeing measure, and one dementia-specific measure was explored in each session. All sessions were audiotaped and transcribed verbatim. Data were analysed thematically. Results Nine individuals with mild dementia and 17 carers of people with dementia participated across 4 focus groups and 10 interviews. Participants perceived 9 broad QoL domains as relevant to them: Activity, Autonomy, Cognition, Communication, Coping, Emotions, End-of-Life, Physical Functioning, and Relationships. These domains had limited overlap with the content of the six PBMs. Assessment of face validity was summarized into eight themes: (1) ambiguous questions, (2) double –barrelled questions, (3) difficult/abstract questions, (4) judgemental/confronting questions, (5) lack of relevance and comprehensiveness, (6) response options, (7) layout/format and (8) proxy-response. There was no clear preference for one of the six measures explored; participants identified advantages and disadvantages across all measures. Although particularly designed for individuals with dementia, dementia-specific QoL measures were not always favoured over non-specific measures. Conclusion Given the shortcomings of PBMs identified in this study, further empirical comparative analyses are necessary to guide the selection of PBMs for future dementia research.

Background: To translate and linguistically validate the Assessment of Quality of Life 8-dimensions (AQoL-8D) for use in the Netherlands and to compare the psychometric properties of AQoL-8D with the EuroQol 5-dimensions 5-levels (EQ-5D-5L) in two patient samples. Methods: AQoL-8D was translated from English into Dutch. The translated AQoL-8D was then administered alongside the EQ-5D-5L at baseline and follow-up of two Dutch randomized controlled trials among patients with epilepsy and schizophrenia. These data were subjected to a post-hoc analysis assessing the psychometric properties of AQol-8D vis-à-vis EQ-5D-5L in terms of known-groups construct validity, responsiveness, and floor/ceiling effects. Results: In total, 103 epilepsy patients and 99 schizophrenia patients were included in this study. In both datasets, the two instruments discriminated between known-groups, but in schizophrenia, AQoL-8D showed higher responsiveness than EQ-5D-5L, while both instruments showed equal responsiveness in epilepsy. Ceiling effects were only found for EQ-5D-5L in both epilepsy (26.6%) and schizophrenia (6.1%). Conclusion: Our results have shown that, among other things, AQoL-8D presents better ability to discriminate between known-groups and shows no ceiling effect. Based on our results, we would recommend the use of AQoL-8D in addition to EQ-5D-5L in trials assessing patient’s quality of life in patients with epilepsy or schizophrenia.

Background Economic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D (EQ-5D-5 L) and the ICEpop CAPability measure for Adults (ICECAP-A) from the three commonly used clinical measures; the CORE-OM, the LDQ and the TOP measures. Methods Models were estimated using pilot trial data of heroin users in opiate substitution treatment. In the trial the EQ-5D-5 L, ICECAP-A, CORE-OM, LDQ and TOP were administered at baseline, three and twelve month time intervals. Mapping was conducted using estimation and validation datasets. The normal estimation dataset, which comprised of baseline sample data, used ordinary least squares (OLS) and tobit regression methods. Data from the baseline and three month time periods were combined to create a pooled estimation dataset. Cluster and mixed regression methods were used to map from this dataset. Predictive accuracy of the models was assessed using the root mean square error (RMSE) and the mean absolute error (MAE). Algorithms were validated using sample data from the follow-up time periods. Results Mapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5 L in the context of opiate dependence. Although both measures can be predicted, the ICECAP-A was better predicted by the clinical measures. There were no advantages of pooling the data. There were 6 chosen mapping algorithms, which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178. Conclusion It is possible to predict the scores of the ICECAP-A and the EQ-5D-5 L with the use of mapping. In the context of opiate dependence, these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options. Trial registration ISRCTN22608399. Date of registration: 27/04/2012. Date of first randomisation: 14/08/2012. Electronic supplementary material The online version of this article (10.1186/s12955-018-0926-7) contains supplementary material, which is available to authorized users.

© 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Objectives: To describe the use of a novel approach in health valuation of a discrete-choice experiment (DCE) including a cost attribute to value a recently developed classification system for measuring the quality-of-life impact (both health and treatment experience) of self-management for diabetes. Methods: A large online survey was conducted using DCE with cost on UK respondents from the general population (n = 1497) and individuals with diabetes (n = 405). The data were modeled using a conditional logit model with robust standard errors. The marginal rate of substitution was used to generate willingness-to-pay (WTP) estimates for every state defined by the classification system. Robustness of results was assessed by including interaction effects for household income. Results: There were some logical inconsistencies and insignificant coefficients for the milder levels of some attributes. There were some differences in the rank ordering of different attributes for the general population and diabetic patients. The WTP to avoid the most severe state was £1118.53 per month for the general population and £2356.02 per month for the diabetic patient population. The results were largely robust. Conclusions: Health and self-management can be valued in a single classification system using DCE with cost. The marginal rate of substitution for key attributes can be used to inform cost-benefit analysis of self-management interventions in diabetes using results from clinical studies in which this new classification system has been applied. The method shows promise, but found large WTP estimates exceeding the cost levels used in the survey.

Objective Generic preference-based measures such as the EuroQol five-dimensional questionnaire (EQ-5D) are used in economic evaluation, but may not be appropriate for all conditions. When this happens, a possible solution is adding bolt-ons to expand their descriptive systems. Using review-based methods, studies published to date claimed the relevance of bolt-ons in the presence of poor psychometric results. This approach does not identify the specific dimensions missing from the Generic preference-based measure core descriptive system, and is inappropriate for identifying dimensions that might improve the measure generically. This study explores the use of principal-component analysis (PCA) and confirmatory factor analysis (CFA) for bolt-on identification in the EQ-5D. Methods Data were drawn from the international Multi-Instrument Comparison study, which is an online survey on health and well-being measures in five countries. Analysis was based on a pool of 92 items from nine instruments. Initial content analysis provided a theoretical framework for PCA results interpretation and CFA model development. PCA was used to investigate the underlining dimensional structure and whether EQ-5D items were represented in the identified constructs. CFA was used to confirm the structure. CFA was cross-validated in random halves of the sample. Results PCA suggested a nine-component solution, which was confirmed by CFA. This included psychological symptoms, physical functioning, and pain, which were covered by the EQ-5D, and satisfaction, speech/cognition,relationships, hearing, vision, and energy/sleep which were not. These latter factors may represent relevant candidate bolt-ons. Conclusions PCA and CFA appear useful methods for identifying potential bolt-ons dimensions for an instrument such as the EQ-5D.

PURPOSE: The Quality of Life after Brain Injury overall scale (QOLIBRI-OS) measures health-related quality of life (HRQoL) after traumatic brain injury (TBI). The aim of this study was to derive value sets for the QOLIBRI-OS in three European countries, which will allow calculation of utility scores for TBI health states. METHODS: A QOLIBRI-OS value set was derived by using discrete choice experiments (DCEs) and visual analogue scales (VAS) in general population samples from the Netherlands, United Kingdom and Italy. A three-stage procedure was used: (1) A selection of health states, covering the entire spectrum of severity, was defined; (2) General population samples performed the health state valuation task using a web-based survey with three VAS questions and an at random selection of sixteen DCEs; (3) DCEs were analysed using a conditional logistic regression and were then anchored on the VAS data. Utility scores for QOLIBRI-OS health states were generated resulting in estimates for all potential health states. RESULTS: The questionnaire was completed by 13,623 respondents. The biggest weight increase for all attributes is seen from "slightly" to "not at all satisfied", resulting in the largest impact on HRQoL. "Not at all satisfied with how brain is working" should receive the greatest weight in utility calculations in all three countries. CONCLUSION: By transforming the QOLIBRI-OS into utility scores, we enabled the application in economic evaluations and in summary measures of population health, which may be used to inform decision-makers on the best interventions and strategies for TBI patients., Hannelore Kohl Stiftung (Germany) OneMind (USA) Integra LifeSciences Corporation (USA)

Study Design. Systematic review. Objective. This systematic review examines validity and responsiveness of three generic preference-based measures in patients with low back pain (LBP). Summary of Background Data. LBP is a very common incapacitating disease with a significant impact on health-related quality of life (HRQoL). Health state utility values can be derived from various preference-based HRQoL instruments, and among them the most widely ones are EuroQol 5 dimensions (EQ-5D), Short Form 6 Dimensions (SF-6D), and Health Utilities Index 3 (HUI III). The ability of these instruments to reflect HRQoL has been tested in various contexts, but never for LBP populations. Methods. A systematic search on electronic literature databases was undertaken to identify studies of patients with LBP where health state utility values were reported. Records were screened using a set of predefined eligibility criteria. Data on validity (correlations and known group methods) and responsiveness (effect sizes, standardized response means, tests of statistical significance) of instruments were extracted using a customized extraction template, and assessed using predefined criteria. Results. There were substantial variations in the 37 included papers identified in relation to study design and outcome measures used. EQ-5D demonstrated good convergent validity, as it was able to distinguish between known groups. EQ-5D was also able to capture changes of health states as results of different interventions. Evidence for SF-6D and HUI III was limited to allow an appropriate evaluation. Conclusion. EQ-5D performs well in LBP population and its scores seem to be suitable for economic evaluation of LBP interventions. However, the paucity of information on the other instruments makes it impossible to determine its relative validity and responsiveness compared with them. Level of Evidence: 2

ObjectiveThis article presents the development of the Dutch value set for the Child Health Utility 9D, a pediatric preference-based measure of quality of life that can be used to generate quality-adjusted life-years.MethodsA large online survey was conducted using a discrete choice experiment including a duration attribute with adult members of the Netherlands general population (N = 1276) who were representative in terms of age, gender, marital status, employment, education, and region. Respondents were asked which of two health states they prefer, where each health state was described using the nine dimensions of the Child Health Utility 9D (worried, sad, pain, tired, annoyed, school work/homework, sleep, daily routine, able to join in activities) and duration. The data were modeled using conditional logit with robust standard errors to produce utility values for every health state described by the Child Health Utility 9D.ResultsThe majority of the dimension level coefficients were monotonic, leading to a decrease in utility as severity increases. There was, however, evidence of some logical inconsistencies, particularly for the school work/homework dimension. The value set produced was based on the ordered model and ranges from –0.568 for the worst state to 1 for the best state.ConclusionThe valuation of the Child Health Utility 9D using online discrete choice experiment with duration with adult members of the Dutch general population was feasible and produced a valid model for use in cost utility analysis. Normative questions are raised around the valuation of pediatric preference-based measures, including the appropriate perspective for imagining hypothetical pediatric health states.

Background No current guidance is available in the UK on the choice of preference-based measure (PBM) that should be used in obtaining health-related quality of life from children. The aim of this study is to review the current usage of PBMs for obtaining health state utility values in child and adolescent populations, and to obtain information on patient and parent–proxy respondent preferences in completing PBMs in the UK. Methods A literature review was conducted to determine which instrument is most frequently used for child-based economic evaluations and whether child or proxy responses are used. Instruments were compared on dimensions, severity levels, elicitation and valuation methods, availability of value sets and validation studies, and the range of utility values generated. Additionally, a series of focus groups of parents and young people (11–20 years) were convened to determine patient and proxy preferences. Results Five PBMs suitable for child populations were identified, although only the Health Utilities Index 2 (HUI2) and Child Heath Utility 9D (CHU-9D) have UK value sets. 45 papers used PBMs in this population, but many used non-child-specific PBMs. Most respondents were parent proxies, even in adolescent populations. Reported missing data ranged from 0.5 to 49.3%. The focus groups reported their experiences with the EQ-5D-Y and CHU-9D. Both the young persons’ group and parent/proxy groups felt that the CHU-9D was more comprehensive but may be harder for a proxy to complete. Some younger children had difficulty understanding the CHU-9D questions, but the young persons’ group nonetheless preferred responding directly. Conclusion The use of PBMs in child populations is increasing, but many studies use PBMs that do not have appropriate value sets. Parent proxies are the most common respondents, but the focus group responses suggest it would be preferred, and may be more informative, for older children to self-report or for child–parent dyads to respond. Electronic supplementary material The online version of this article (10.1007/s11136-018-1831-6) contains supplementary material, which is available to authorized users.

Background Condition-specific measures are frequently used to assess the health-related quality of life of people with multiple sclerosis (MS). Such measures are unsuitable for use in economic evaluations that require estimates of cost per quality-adjusted life-year because they are not based on preferences. Objectives To report the estimation of a preference-based single index for an eight-dimensional instrument for MS, the Multiple Sclerosis Impact Scale – Eight Dimensions (MSIS-8D), derived from an MS-specific measure of health-related quality of life, the 29-item Multiple Sclerosis Impact Scale (MSIS-29). Methods We elicited preferences for a sample of MSIS-8D states (n = 169) from a sample (n = 1702) of the UK general population. Preferences were elicited using the time trade-off technique via an Internet-based survey. We fitted regression models to these data to estimate values for all health states described by the MSIS-8D. Estimated values were assessed against MSIS-29 scores and values derived from generic preference-based measures in a large, representative sample of people with MS. Results Participants reported that the time trade-off questions were easy to understand. Observed health state values ranged from 0.08 to 0.89. The best-performing model was a main effects, random effects model (mean absolute error=0.04). Validation analyses support the performance of the MSIS-8D index: it correlated more strongly than did generic measures with MSIS-29 scores, and it discriminated effectively between subgroups of people with MS. Conclusions The MSIS-8D enables health state values to be estimated from the MSIS-29, adding to the methods available to assess health outcomes and to estimate quality-adjusted life-years for MS for use in health technology assessment and decision-making contexts.

Objective.To understand the limitations with current patient-reported outcome measures (PROM) used to generate quality-adjusted life-years (QALY) in rheumatology, and set a research agenda.Methods.Two activities were undertaken. The first was a scoping review of published studies that have used PROM to generate QALY in rheumatology between 2011 and 2016. The second was an interactive “eyeball test” exercise at Outcome Measures in Rheumatology 13 that compared subdomains of widely used generic PROM, as identified through the scoping review, to subdomains of the Assessment of SpondyloArthritis Health Index (ASAS-HI) condition-specific PROM for ankylosing spondylitis.Results.The scoping review included 39 studies. Five different PROM have been used to generate QALY in rheumatology; however, the EQ-5D and Short Form 6 Dimensions (SF-6D) were used most frequently (in 32 and 9 of included studies, respectively). Special interest group participants identified energy/drive and sleep as 2 key subdomains of the ASAS-HI instrument that may be missed by the EQ-5D, and sexual function as potentially missed by the SF-6D. Participants also expressed concerns that aspects of the process of care and non-health outcomes may be missed. Three ways of incorporating additional subdomains were discussed, including using an alternative generic PROM, modifying an existing generic PROM with “bolt-on” subdomain(s), and generating societal weights for a condition-specific PROM.Conclusion.Three priorities for future research were identified: understanding whether the EQ-5D and SF-6D identify what matters to patients with different rheumatic conditions, analyzing how much patients value process or non-health outcomes, and identifying which approaches to incorporating a greater number of subdomains into the QALY are being undertaken in other disease areas.

Objective To investigate the responsiveness of and correlation between the EQ-5D-5L and the QOLIE-31P in patients with epilepsy, and develop a mapping function to predict EQ-5D-5L values based on the QOLIE-31P for use in economic evaluations. Methods The dataset was derived from two clinical trials, the ZMILE study in the Netherlands and the SMILE study in the UK. In both studies, patients’ quality of life using the EQ-5D-5L and QOLIE-31P was measured at baseline and 12 months follow-up. Spearman’s correlations, effect sizes (EF) and standardized response means (SRM) were calculated for both the EQ-5D-5L and QOLIE-31P domains and sub scores. Mapping functions were derived using ordinary least square (OLS) and censored least absolute deviations models. Results A total of 509 patients were included in this study. Low to moderately strong significant correlations were found between both instruments. The EQ-5D-5L showed high ceiling effects and small EFs and SRMs, whereas the QOLIE-31P did not show ceiling effects and also showed small to moderate EFs and SRMs. Results of the different mapping functions indicate that the highest adjusted R 2 we were able to regress was 0.265 using an OLS model with squared terms, leading to a mean absolute error of 0.103. Conclusions Results presented in this study emphasize the shortcomings of the EQ-5D-5L in epilepsy and the importance of the development of condition-specific preference-based instruments which can be used within the QALY framework. In addition, the usefulness of the constructed mapping function in economic evaluations is questionable. Electronic supplementary material The online version of this article (doi:10.1007/s10198-017-0928-0) contains supplementary material, which is available to authorized users.

Background Profile instruments are frequently used to assess health-related quality of life and other patient-reported outcomes. However, preference-based measures are required for health-economic cost-utility evaluations. Results Although regression-based approaches are commonly used to map from profile measures to preference measures, we show that this results in biased estimates because of regression to the mean. Conclusions Linking (scale-aligning) is proposed as an alternative.

PurposeDocumenting the impact of different types of cancer on daily functioning and well-being is important for understanding burden relative to other chronic medical conditions. This study examined the impact of 10 different cancers and 13 other chronic medical conditions on health-related quality of life.MethodsHealth-related quality of life data were gathered on the Medicare Health Outcomes Survey (MHOS) between 1998 and 2002. Cancer information was ascertained using the National Cancer Institute's surveillance, epidemiology, and end results program and linked to MHOS data.ResultsThe average SF-6D score was 0.73 (SD = 0.14). Depressive symptoms had the largest unique association with the SF-6D, followed by arthritis of the hip, chronic obstructive pulmonary disease/asthma, stroke, and sciatica. In addition, the majority of cancer types were significantly associated with the SF-6D score, with significant negative weights ranging from -0.01 to -0.02 on the 0-1 health utility scale. Distant stage of cancer was associated with large decrements in the SF-6D ranging from -0.04 (prostate) to -0.08 (female breast).ConclusionA large number of chronic conditions, including cancer, are associated uniquely with decrements in health utility. The cumulative effects of comorbid conditions have substantial impact on daily functioning and well-being of Medicare beneficiaries.

Objectives To describe how qualitative methods can be used in the development of descriptive systems of preference-based measures (PBMs) of health-related quality of life. Methods The requirements of the National Institute for Health and Clinical Excellence and other agencies together with the increasing use of patient-reported outcome measures has led to an increase in the demand for PBMs. Recently, interest has grown in developing new PBMs and while previous research on PBMs has mainly focused on the methods of valuation, research into the methods of developing descriptive systems is an emerging field. Results Traditionally, descriptive systems of PBMs were developed by using top-down methods, where content was derived from existing measures, the literature, or health surveys. A contrasting approach is a bottom-up methodology, which takes the views of patients or laypeople on how their life is affected by their health. This approach generally requires the use of qualitative methods. Qualitative methods lend themselves well to the development of PBMs. They also ensure that the measure has appropriate language, content validity, and responsiveness to change. While the use of qualitative methods in the development of non-PBMs is fairly standard, their use in developing PBMs was until recently nonexistent. Conclusions In this article, we illustrate the use of qualitative methods by presenting two case studies of recently developed PBMs, one generic and one condition specific. We outline the stages involved, discuss the strengths and weaknesses of the approach, and compare with the top-down approach used in the majority of PBMs to date.

Background A five-level version of the EuroQol five-dimensional (EQ-5D) descriptive system (EQ-5D-5L) has been developed, but value sets based on preferences directly elicited from representative general population samples are not yet available. The objective of this study was to develop values sets for the EQ-5D-5L by means of a mapping ("crosswalk") approach to the currently available three-level version of the EQ-5D (EQ-5D-3L) values sets. Methods The EQ-5D-3L and EQ-5D-5L descriptive systems were coadministered to respondents with conditions of varying severity to ensure a broad range of levels of health across EQ-5D questionnaire dimensions. We explored four models to generate value sets for the EQ-5D-5L: linear regression, nonparametric statistics, ordered logistic regression, and item-response theory. Criteria for the preferred model included theoretical background, statistical fit, predictive power, and parsimony. Results A total of 3691 respondents were included. All models had similar fit statistics. Predictive power was slightly better for the nonparametric and ordered logistic regression models. In considering all criteria, the nonparametric model was selected as most suitable for generating values for the EQ-5D-5L. Conclusions The nonparametric model was preferred for its simplicity while performing similarly to the other models. Being independent of the value set that is used, it can be applied to transform any EQ-5D-3L value set into EQ-5D-5L index values. Strengths of this approach include compatibility with three-level value sets. A limitation of any crosswalk is that the range of index values is restricted to the range of the EQ-5D-3L value sets.

Objectives Some argue that generic preference-based measures (PBMs) are not sensitive to certain disease-specific improvements. To overcome this problem, new condition-specific PBMs (CS-PBMs) are being developed, but it is not yet clear how such measures compare with existing generic PBMs. Method We generated CS-PBMs from three condition-specific questionnaires (Health Assessment Questionnaire for arthritis, Quality of Life Questionnaire for Cancer 30 for cancer, and Multiple Sclerosis Impact Scale 29 for multiple sclerosis). First, the questionnaires were reduced in content, and then, a time trade-off study was conducted in the general public (N = 402) to obtain weights associated with the dimensions and levels of the new questionnaire. Finally, we compared utilities obtained by using the CS-PBMs with utilities obtained by using the EuroQol five-dimensional (EQ-5D) questionnaire in four data sets. Results Utility values generated by the CS-PBMs were higher than those of the EQ-5D questionnaire. The Health Assessment Questionnaire–based measure for arthritis proved to be insensitive to comorbidities. Measures based on the Multiple Sclerosis Impact Scale 29 and the Quality of Life Questionnaire for Cancer 30 discriminated comorbidities and side effect equally well as the EQ-5D questionnaire and were more sensitive than the EQ-5D questionnaire for mild impairments. Conclusions The introduction of PBMs that are specific to a certain disease may have the merit of sensitivity to disease-specific effects of interventions. That gain, however, is traded off to the loss of comparability of utility values and, in some cases, insensitivity to side effects and comorbidity. The use of a CS-PBM for cost-utility analysis is warranted only under strict conditions.

ObjectivesGeneric health status measures such as the short form health survey (SF-36) and EuroQol-5D (EQ-5D) are increasingly being used to inform health policy. They are claimed to be applicable across disease areas and have started to be used within mental health research. This review aims to assess the construct validity and responsiveness of four generic health status measures in schizophrenia, including the preference-based SF-6D and EQ-5D.MethodA systematic review of the literature was undertaken. Ten databases were searched from inception to August 2009 and reference lists scrutinized to identify relevant studies. Studies were appraised and data extracted. A narrative synthesis was performed of the evidence on construct validity including known groups validity (detecting a difference in health-related quality of life (HRQL) scores between two different groups such as samples from the general population and people with schizophrenia), convergent validity (strength of association between generic HRQL and other measures (e.g., symptom or functional), and responsiveness. Responsiveness was considered by: 1) differences in generic HRQL measure scores in responders/non-responders and 2) correlation between changes on generic HRQL measures and changes in specific measures obtained from patients and clinicians.ResultsThirty-three studies were identified that provided data on the validity and/or responsiveness of the instruments. Most of the evidence concerns the SF-36 and EQ-5D, and for these instruments there was evidence for known group validity. The evidence for convergent validity and responsiveness was mixed, with studies presenting contradictory results.ConclusionAlthough the evidence base is limited in a number of important respects, including problems with the measures used to develop constructs in the validation studies, it is sufficient to raise doubts about the use of generic measures of health like the EQ-5D and SF-36 in patients with schizophrenia.

BACKGROUND: In economic evaluations of care services for older adults health-related quality of life (QoL) measures such as the EQ-5D are increasingly replaced by the ICECAP-O and ASCOT, which cover a broader scope of QoL than health alone. Little is known about the content validity and feasibility of these measures. The purpose of this study was to explore the content validity and feasibility of the EQ-5D-3L, ICECAP-O and ASCOT in older adults.METHODS: Ten older adults were purposively sampled using a maximum variation principle. Think-aloud and verbal probing techniques were used to identify response issues encountered during the interpretation of items and the selection of response options. We used constant comparative methods to analyse the data.RESULTS: Two types of response issues were identified for various items in all three measures: interpretation issues and positive responses. Issues with the mapping of a response on one of the response options were least often encountered for the EQ-5D-3L items. Older adults considered the items of the ICECAP-O and ASCOT valuable though more abstract than the EQ-5D-3L.CONCLUSIONS: Researchers who intend to use the EQ-5D, ICECAP-O or ASCOT in economic evaluations of care services for older adults, should be aware of the response issues that occur during the administration of these measures. Older adults perceived none of the measures as providing a comprehensive picture of their QoL. A preference from older adults for one of the measures depends on the extent to which the items reflect current personal concerns in life.

The validity of the SF-6D, a preference-based measure of health-related quality of life, is not well explored in the context of spinal cord injury (SCI). The aim of this analysis was to assess appropriate measurement properties of the SF-6D in a sample of individuals living with SCI.Longitudinal data from the Rick Hansen Spinal Cord Injury Registry were used. Responses to the 36-item short-form health survey were transformed into SF-6D utility scores. We investigated practicality, floor and ceiling effects, and responsiveness to change. Responsiveness to change was explored using three different anchors that reflected changes in self-reported health, functional independence, and life satisfaction. Discriminative validity was assessed by ten a priori defined hypotheses, with a distinction made between 'strong' and 'weak' hypotheses.Three hundred and fifty-eight individuals with SCI were included in this analysis. Practicality was deemed acceptable based on a completion rate of 94 %. The SF-6D showed low responsiveness to detect important health changes over time, and differences in responsiveness were found between individuals with paraplegia and tetraplegia. All five strong hypotheses and three weak hypotheses were confirmed.The SF-6D demonstrated good practicality and discriminative validity in this sample. The failure to detect self-reported and clinically important health changes requires further consideration. Comparative performance of the SF-6D (i.e., how the SF-6D performs against other preference-based measures) is unknown in the SCI context and requires further research.

BACKGROUND: The ICEpop CAPability measure for Older people (ICECAP-O) and the Adult Social Care Outcomes Toolkit (ASCOT) are preference-based measures for assessing quality of life (QOL) from a broader perspective than do traditional health-related QOL measures such as the EuroQol five-dimensional questionnaire (EQ-5D). Measurement properties of these instruments have not yet been directly compared.OBJECTIVE: The purpose of this study was to compare the test-retest reliability, construct validity, and responsiveness of the three-level EQ-5D (EQ-5D-3L), ICECAP-O, and ASCOT in frail older adults living at home.METHODS: Cross-sectional data and longitudinal data were used. Parameters for reliability (the intraclass correlation coefficient) and agreement (standard error of measurement) were used to assess test-retest reliability after 1 week. We formulated hypotheses about correlations with other measures and tested these to assess construct validity and responsiveness (longitudinal validity).RESULTS: The reliability parameters for all three scales were considered good (intraclass correlation coefficient values above 0.70). Standard error of measurement values were less than 10% of the scale. Hypotheses regarding construct validity were in general accepted; the EQ-5D-3L was more strongly associated with physical limitations than were ICECAP-O and ASCOT and less strongly with instruments measuring aspects beyond health. Longitudinally, as hypothesized, mental health was most strongly associated with ICECAP-O, and self-perceived QOL, mastery, and client-centeredness of home care most strongly with ASCOT.CONCLUSIONS: Our findings support the adoption of ICECAP-O and ASCOT as outcome measures in economic evaluations of care interventions for older adults that have a broader aim than health-related QOL because they are at least as reliable as the EQ-5D-3L and are associated with aspects of QOL broader than health.

Objective Resource allocation informed by cost-utility analysis requires that the benefits be comparable across patient groups and interventions. One option is to recommend the use of one generic utility measure, but this raises the issue of comparability when the preferred measure is inappropriate or unavailable. Many cancer trials do not include generic measures such as the EuroQol five-dimensional (EQ-5D) questionnaire and instead include condition-specific measures and use these to generate utility estimates. We analyze the comparability of generic, condition-specific, and mapped utility values for a multiple myeloma cancer patient data set. Methods Generic EQ-5D, condition-specific EORTC-8D, and EQ-5D utility values mapped from the EORTC QLQ-C30 were compared by using psychometric and statistical analysis to determine discrimination across severity groups, responsiveness, and agreement. Results Generic, condition-specific, and mapped utility estimates were responsive over time and show discriminative validity. The EQ-5D had higher responsiveness and detected a greater change across severity groups and treatment periods than did the EORTC-8D but has a higher proportion of responses at full health (12.8%). Differences in the EQ-5D and the EORTC-8D were due at least in part to differences in the classification system. Mapped EQ-5D estimates had a smaller SD and do not reflect the severe range of health states reported by using the EQ-5D. Conclusions Our findings suggest that condition-specific EORTC-8D or mapped EQ-5D utility estimates are broadly comparable to directly obtained EQ-5D utilities for a multiple myeloma patient data set. However, EORTC-8D estimates captured changes in quality of life for patients in mild health states that were not captured by the EQ-5D, but estimated lower utility gains than did the use of the EQ-5D directly.

Objectives: SF-6D is a preference-based measure of health developed to estimate utility values from the SF-36. The aim of this study was to estimate a weighting system for the SF-6D health states representing the preferences of a sample of the Southern Brazilian general population. Methods: A sample of 248 health states defined by the SF-6D was valued by a sample of the southern Brazilian population using the standard gamble. Mean and individual level multivariate regression models were fitted to the standard gamble valuation data to estimate preference weights for all SF-6D health states. The models were compared with those estimated in the UK study. Results: Five hundred twenty-eight participants were interviewed, but 58 (11%) were excluded for failing to value the worst state. Data from 469 subjects producing 2696 health states valuations were used in the regression analysis. In contrast to the best performing model for the UK data, the best performing model for the Brazilian data was a random effects model using only the main effects variables, highlighting the importance of adopting a country-specific algorithm to derive SF-6D health states values. Inconsistent coefficients were merged to produce the final recommended model, which has all significant coefficients and a mean absolute difference between observed and predicted standard gamble values of 0.07. Conclusions: The results provide the first population-based value set for Brazil for SF-6D health states, making it possible to generate quality-adjusted life years for cost-utility studies using regional data. Besides, utility weights derived using the preferences of a sample from a southern Brazilian population can be derived from existing SF-36 data sets.

Objectives This study establishes the South Korean population-based preference weights for EQ-5D based on values elicited from a representative national sample using the time trade-off (TTO) method. Methods The data for this paper came from a South Korean EQ-5D valuation study where 1307 representative respondents were invited to participate and a total of 101 health states defined by the EQ-5D descriptive system were directly valued. Both aggregate and individual level modeling were conducted to generate values for all 243 health states defined by EQ-5D. Various regression techniques and model specifications were also examined in order to produce the best fit model. Final model selection was based on minimizing the difference between the observed and estimated value for each health state. Results The N3 model yielded the best fit for the observed TTO value at the aggregate level. It had a mean absolute error of 0.029 and only 15 predictions out of 101 had errors exceeding 0.05 in absolute magnitude. Conclusions The study successfully establishes South Korean population-based preference weights for the EQ-5D. The value set derived here is based on a representative population sample, limiting the interpolation space and possessing better model performance. Thus, this EQ-5D value set should be given preference for use with the South Korean population.

ObjectiveExisting estimates of human immunodeficiency virus (HIV)-related health state utilities are inadequate for comparing alternative treatments on the basis of regimen-specific attributes such as dosing requirements or tolerability. The objective of this study was to examine the marginal impact of dosing, adverse events (AEs), and other factors on patients' health state utilities.MethodsTreatment naive and experienced HIV patients participating in five open-label trials of highly active antiretroviral therapy (HAART) completed the 36-Item Short Form Health Survey (SF-36) instrument at various time points. SF-36 responses were converted to utilities using a previously reported algorithm. Expected utilities were estimated as a function of patient demographics, regimen attributes, disease status, and AEs using a mixed-effects maximum likelihood model. Mean utilities for five HIV health states were derived from predicted patient utilities.ResultsNegative predictors of utility included greater age (−0.001), prior acquired immune deficiency syndrome-defining events (−0.036), female gender (−0.038), and injection drug use (−0.056; P < 0.01 for all). Utility also depended on CD4+ cell count (P < 0.01), but not the presence of undetectable viral load. Regimen attributes were marginally associated with changes in utility. Depression was associated with the largest decrease in utility (−0.054, P < 0.001) among the AEs examined. Using the model to generate predicted utilities from the sample provided mean estimates ranging from 0.742 (SD 0.058) to 0.798 (0.052) for CD4+ counts between 0 and 99 and ≥500 cells/mm3, respectively.ConclusionsHIV patients' health-related quality of life may be substantially affected by clinically relevant patient-, disease-, and treatment-related factors, such as injection drug use, disease status, food/drink restrictions, and AEs.

Background: The EORTC QLQ-C30 is one of the most commonly used measures in cancer but in its current form cannot be used in economic evaluation as it does not incorporate preferences. Methods and results: We address this gap by estimating a preference-based single index for cancer from the EORTC QLQ-C30 for use in economic evaluation. Factor analysis, Rasch analysis and other psychometric analyses were undertaken on a clinical trial dataset of 655 patients with multiple myeloma to derive a health state classification from the QLQ-C30 that is amenable to valuation. The resulting health state classification system has 8 dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue and sleep disturbance, nausea, and constipation and diarrhoea) with 4 or 5 levels each. A valuation study was conducted of 350 members of the UK general population using ranking and time trade-off. Mean and individual level additive multivariate regression models including the episodic random utility model were fitted to the valuation data to derive preference weights for the classification system. Mean absolute error ranges from 0.046 to 0.054 and models have few inconsistencies (0 to 2) in estimated preference weights. Conclusions: We conclude that it is feasible to derive a preference-based measure from the EORTC QLQ-C30 for use in economic evaluation, but this work needs to be extended to other countries and replicated across other patient groups.

Background: Many intervention-based studies aiming to improve mental health do not include a multi-attribute utility instrument (MAUI) that produces quality-adjusted life-years (QALYs) and it limits the applicability of the health economic analyses. This study aims to develop 'crosswalk' transformation algorithm between a measure for psychological distress General Health Questionnaire (GHQ-12) and MAUI EuroQoL (EQ-5D-3L). Methods: The study is based on a survey questionnaire sent to a random sample in four counties in Sweden in 2012. The survey included GHQ-12 and EQ-5D instruments, as well as a question about self-rated health. The EQ-5D index was calculated using the UK and the Swedish tariff values. Two OLS models were used to estimate the EQ-5D health state values using the GHQ-12 as exposure, based on the respondents (n = 17, 101) of two counties. The algorithms were applied to the data from two other counties, (n = 15, 447) to check the predictive capacity of the models. Results: The final models included gender, age, self-rated health and GHQ-12 scores as a quantitative variable. The regression equations explained 40 % (UK tariff) and 46 % (Swedish tariff) of the variances. The model showed a satisfying predictive capacity between the observed and the predicted EQ-5D index score, with Pearson correlation = 0.65 and 0.69 for the UK and Swedish models, respectively. Conclusion: The algorithms developed in this study can be used to determine cost-effectiveness of services or interventions that use GHQ-12 as a primary outcome where the utility measures are not collected.