EQ-5D in skin conditions: an assessment of validity and responsiveness

Aims and objectives This systematic literature review aims to assess the reliability, validity and responsiveness of three widely used generic preference-based measures of health-related quality of life (HRQL), i.e., EQ-5D, Health Utility Index 3 (HUI3) and SF-6D in patients with skin conditions. Methods A systematic search was conducted to identify studies reporting health state utility values obtained using EQ-5D, SF-6D, or HUI3 alongside other HRQL measures or clinical indices for patients with skin conditions. Data on test-retest analysis for reliability, known group differences or correlation and regression analyses for validity, and change over time or responsiveness indices analysis were extracted and reviewed. Results A total of 16 papers reporting EQ-5D utilities in people with skin conditions were included in the final review. No papers for SF-6D and HUI3 were found. Evidence of reliability was not found for any of these measures. The majority of studies included in the review (12 out of 16) examined patients with plaque psoriasis or psoriatic arthritis and the remaining four studies examined patients with either acne, hidradenitis suppurativa, hand eczema, or venous leg ulcers. The findings were generally positive in terms of performance of EQ-5D. Six studies showed that EQ-5D was able to reflect differences between severity groups and only one reported differences that were not statistically significant. Four studies found that EQ-5D detected differences between patients and the general population, and differences were statistically different for three of them. Further, moderate-to-strong correlation coefficients were found between EQ-5D and other skin-specific HRQL measures in four studies. Eight studies showed that EQ-5D was able to detect change in HRQL appropriately over time and the changes were statistically significant in seven studies. Conclusions Overall, the validity and responsiveness of the EQ-5D was found to be good in people with skin diseases, especially plaque psoriasis or psoriatic arthritis. No evidence on SF-6D and HUI3 was available to enable any judgments to be made on their performance

Mapping Functions in Health-Related Quality of Life: Mapping From Two Cancer-Specific Health-Related Quality-of-Life Instruments to EQ-5D-3L.

BACKGROUND: Clinical trials in cancer frequently include cancer-specific measures of health but not preference-based measures such as the EQ-5D that are suitable for economic evaluation. Mapping functions have been developed to predict EQ-5D values from these measures, but there is considerable uncertainty about the most appropriate model to use, and many existing models are poor at predicting EQ-5D values. This study aims to investigate a range of potential models to develop mapping functions from 2 widely used cancer-specific measures (FACT-G and EORTC-QLQ-C30) and to identify the best model. METHODS: Mapping models are fitted to predict EQ-5D-3L values using ordinary least squares (OLS), tobit, 2-part models, splining, and to EQ-5D item-level responses using response mapping from the FACT-G and QLQ-C30. A variety of model specifications are estimated. Model performance and predictive ability are compared. Analysis is based on 530 patients with various cancers for the FACT-G and 771 patients with multiple myeloma, breast cancer, and lung cancer for the QLQ-C30. RESULTS: For FACT-G, OLS models most accurately predict mean EQ-5D values with the best predicting model using FACT-G items with similar results using tobit. Response mapping has low predictive ability. In contrast, for the QLQ-C30, response mapping has the most accurate predictions using QLQ-C30 dimensions. The QLQ-C30 has better predicted EQ-5D values across the range of possible values; however, few respondents in the FACT-G data set have low EQ-5D values, which reduces the accuracy at the severe end. CONCLUSIONS: OLS and tobit mapping functions perform well for both instruments. Response mapping gives the best model predictions for QLQ-C30. The generalizability of the FACT-G mapping function is limited to populations in moderate to good health

Outcome assessment after hip fracture : is EQ-5D the answer?

Objectives: To study the measurement properties of a joint specific patient reported outcome measure, a measure of capability and a general health-related quality of life (HRQOL) tool in a large cohort of patients with a hip fracture. Methods: Responsiveness and associations between the Oxford Hip Score (a hip specific measure: OHS), ICEpop CAPability (a measure of capability in older people: ICECAP-O) and EuroQol EQ-5D (general health-related quality of life measure: EQ-5D) were assessed using data available from two large prospective studies. The three outcome measures were assessed concurrently at a number of fixed follow-up time-points in a consecutive sequence of patients, allowing direct assessment of change from baseline, inter-measure associations and validity using a range of statistical methods. Results: ICECAP-O was not responsive to change. EQ-5D was responsive to change from baseline, with an estimated standardised effect size for the two datasets of 0.676 and 0.644 at six weeks and four weeks respectively; this was almost as responsive to change as OHS (1.14 at four weeks). EQ-5D correlated strongly with OHS; Pearson correlation coefficients were 0.74, 0.77 and 0.70 at baseline, four weeks and four months. EQ-5D is a moderately good predictor of death at 12 months following hip fracture. Furthermore, EQ-5D reported by proxies (relatives and carers) behaves similarly to self-reported scores. Conclusions: Our findings suggest that a general HRQOL tool such as EQ-5D could be used to measure outcome for patients recovering from hip fracture, including those with cognitive impairment

A comparison of United States and United Kingdom EQ-5D health states valuations using a nonparametric Bayesian method

Few studies have compared preference values of health states obtained in different countries. This paper applies a nonparametric model to estimate and compare EQ-5D health state valuation data obtained from two countries using Bayesian methods. The data set is the US and UK EQ-5D valuation studies where a sample of 42 states defined by the EQ-5D was valued by representative samples of the general population from each country using the time trade-off technique. We estimate a function applicable across both countries which explicitly accounts for the differences between them, and is estimated using the data from both countries. The paper discusses the implications of these results for future applications of the EQ-5D and further work in this field.preference-based health measure; nonparametric methods; time trade-off; EQ-5D

EQ-5D-3L Derived Population Norms for Health Related Quality of Life in Sri Lanka

Background Health Related Quality of Life (HRQoL) is an important outcome measure in health economic evaluation that guides health resource allocations. Population norms for HRQoL are an essential ingredient in health economics and in the evaluation of population health. The aim of this study was to produce EQ-5D-3L-derived population norms for Sri Lanka. Method A population sample (n =  780) was selected from four districts of Sri Lanka. A stratified cluster sampling approach with probability proportionate to size was employed. Twenty six clusters of 30 participants each were selected; each participant completed the EQ-5D-3L in a face-to-face interview. Utility weights for their EQ-5D-3L health states were assigned using the Sri Lankan EQ-5D-3L algorithm. The population norms are reported by age and socio-economic variables. Results The EQ-5D-3L was completed by 736 people, representing a 94% response rate. Sixty per cent of the sample reported being in full health. The percentage of people responding to any problems in the five EQ-5D-3L dimensions increased with age. The mean EQ-5D-3L weight was 0.85 (SD 0.008; 95%CI 0.84-0.87). The mean EQ-5D-3L weight was significantly associated with age, housing type, disease experience and religiosity. People above 70 years of age were 7.5 times more likely to report mobility problems and 3.7 times more likely to report pain/discomfort than those aged 18-29 years. Those with a tertiary education were five times less likely to report any HRQoL problems than those without a tertiary education. A person living in a shanty was 4.3 more likely to have problems in usual activities than a person living in a single house. Conclusion The population norms in Sri Lanka vary with socio-demographic characteristics. The socioeconomically disadvantaged have a lower HRQoL. The trends of population norms observed in this lower middle income country were generally similar to those previously reported in high income countries

A Study of the Relationship Between Health and Subjective Well-being in Parkinson’s Disease Patients

Objectives: In light of the apparent disconnect between traditional measures of societal well-being such as GDP and reported levels of happiness, governments globally are turning their attention to alternative subjective measures of well-being (SWB) to aid policy decisions. In the context of health, there is therefore growing interest in understanding how measures of health-related quality of life (HRQoL), widely used in health technology appraisal, relates to SWB, and whether SWB could provide a sound basis for resource allocation decisions in health and other sectors in the future. This study investigates the relationship between HRQoL, as measured by EQ-5D, and SWB in Parkinson’s disease (PD) and the extent to which patients’ self-reported health can explain (part of) their SWB. Methods: A paper questionnaire including EQ-5D, four key SWB questions taken from the Office for National Statistics Integrated Household Survey in England and other demographic details was distributed to people with PD in the UK. Responses were used to estimate multiple regression models explaining SWB using each of the EQ-5D Index (UK weights), EQ-5D dimensions and EQ-VAS and patient socio-demographic characteristics. Results: 276 questionnaires were distributed and 183 responses received. The EQ-5D Index was a moderate predictor of SWB (adjusted R2 range 0.19-0.38 in OLS models), but EQ-VAS performed better (adjusted R2 range 0.32-0.49). Combining EQ-VAS and EQ-5D dimensions, especially anxiety/depression and mobility, and household status in some cases, yielded the best-fitting models (adjusted R2 range 0.40-0.52). Conclusions: The findings imply that EQ-VAS and some dimensions of the EQ-5D, together with key demographic data, could potentially be used to predict SWB, e.g. via mapping. However, further empirical research into the relationship between SWB and EQ-5D longitudinally, and in different disease areas, is required to corroborate these findings, and further standardisation of SWB measures is recommended

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

© Queen’s Printer and Controller of HMSO 2014Background: 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. 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.UK Medical Research Council (MRC) as part of the MRC-NIHR methodology research programme (reference G0901486

Comparing the mapping between EQ-5D-5L, EQ-5D-3L and the EORTC-QLQ-C30 in non-small cell lung cancer patients

BACKGROUND: Several mapping algorithms have been published with the EORTC-QLQ-C30 for estimating EQ-5D-3L utilities. However, none are available with EQ-5D-5L. Moreover, a comparison between mapping algorithms in the same set of patients has not been performed for these two instruments simultaneously. In this prospective data set of 100 non-small cell lung cancer (NSCLC) patients, we investigate three mapping algorithms using the EQ-5D-3L and EQ-5D-5L and compare their performance. METHODS: A prospective non-interventional cohort of 100 NSCLC patients were followed up for 12 months. EQ-5D-3L, EQ-5D-5L and EORTC-QLQ-C30 were assessed monthly. EQ-5D-5L was completed at least 1 week after EQ-5D-3L. A random effects linear regression model, a beta-binomial (BB) and a Limited Variable Dependent Mixture (LVDM) model were used to determine a mapping algorithm between EQ-5D-3L, EQ-5D-5L and QLQ-C30. Simulation and cross validation and other statistical measures were used to compare the performances of the algorithms. RESULTS: Mapping from the EQ-5D-5L was better: lower AIC, RMSE, MAE and higher R(2) were reported with the EQ-5D-5L than with EQ-5D-3L regardless of the functional form of the algorithm. The BB model proved to be more useful for both instruments: for the EQ-5D-5L, AIC was –485, R(2) of 75 %, MAE of 0.075 and RMSE was 0.092. This was –385, 69 %, 0.099 and 0.113 for EQ-5D-3L respectively. The mean observed vs. predicted utilities were 0.572 vs. 0.577 and 0.515 vs. 0.523 for EQ-5D-5L and EQ-5D-3L respectively, for OLS; for BB, these were 0.572 vs. 0.575 and 0.515 vs. 0.518 respectively and for LVDMM 0.532 vs 0.515 and 0.569 vs 0.572 respectively. Less over-prediction at poorer health states was observed with EQ-5D-5L. CONCLUSIONS: The BB mapping algorithm is confirmed to offer a better fit for both EQ-5D-3L and EQ-5D-5L. The results confirm previous and more recent results on the use of BB type modelling approaches for mapping. It is recommended that in studies where EQ-5D utilities have not been collected, an EQ-5D-5L mapping algorithm is used

Mapping EQ-5D utilities to GBD 2010 and GBD 2013 disability weights : results of two pilot studies in Belgium

Background: Utilities and disability weights (DWs) are metrics used for calculating Quality-Adjusted Life Years and Disability-Adjusted Life Years (DALYs), respectively. Utilities can be obtained with multi-attribute instruments such as the EuroQol 5 dimensions questionnaire (EQ-5D). In 2010 and 2013, Salomon et al. proposed a set of DWs for 220 and 183 health states, respectively. The objective of this study is to develop an approach for mapping EQ-5D utilities to existing GBD 2010 and GBD 2013 DWs, allowing to predict new GBD 2010/2013 DWs based on EQ-5D utilities. Methods: We conducted two pilot studies including respectively four and twenty-seven health states selected from the 220 DWs of the GBD 2010 study. In the first study, each participant evaluated four health conditions using the standard written EQ-5D-5 L questionnaire. In the second study, each participant evaluated four health conditions randomly selected among the twenty-seven health states using a previously developed web-based EQ-5D-5 L questionnaire. The EQ-5D responses were translated into utilities using the model developed by Cleemput et al. A loess regression allowed to map EQ-5D utilities to logit transformed DWs. Results: Overall, 81 and 393 respondents completed the first and the second survey, respectively. In the first study, a monotonic relationship between derived utilities and predicted GBD 2010/2013 DWs was observed, but not in the second study. There were some important differences in ranking of health states based on utilities versus GBD 2010/2013 DWs. The participants of the current study attributed a relatively higher severity level to musculoskeletal disorders such as ‘Amputation of both legs’ and a relatively lower severity level to non-functional disorders such as ‘Headache migraine’ compared to the participants of the GBD 2010/2013 studies. Conclusion: This study suggests the possibility to translate any utility derived from EQ-5D scores into a DW, but also highlights important caveats. We observed a satisfactory result of this methodology when utilities were derived from a population of public health students, a written questionnaire and a small number of health states in the presence of a study leader. However the results were unsatisfactory when utilities were derived from a sample of the general population, using a web-based questionnaire. We recommend to repeat the study in a larger and more diverse sample to obtain a more representative distribution of educational level and age

การเปรียบเทียบ 5 วิธีในการวัดค่าอรรถประโยชน์ของคุณภาพชีวิตด้านสุขภาพ ของนักศึกษาปริญญาตรี A Comparison of Five Approaches for Measuring Utility Values of Health-related Quality of Life among Undergraduate Students

บทคัดย่อ   วัตถุประสงค์: เพื่อทดสอบคุณสมบัติและความสอดคล้องกันของคะแนนอรรถประโยชน์จาก 5 วิธี คือ EQ-5D-3L, EQ-5D-5L (cTTO model), EQ-5D-5L (DCE model), EQ-5D-5L (Hybrid model) และ VAS ของนักศึกษาระดับปริญญาตรี วิธีการศึกษา: การศึกษาเชิงสำรวจแบบภาพตัดขวางเก็บข้อมูลระหว่างมีนาคมถึงเมษายน 2565 กับกลุ่มตัวอย่าง 393 คน ใช้สถิติสัมประสิทธิ์สหสัมพันธ์ภายในชั้น (Intraclass Correlation Coefficient; ICC) เพื่อทดสอบความสอดคล้องของค่าอรรถประโยชน์ 5 วิธี การวิเคราะห์การถดถอยเชิงเส้นพหุคูณเพื่อเปรียบเทียบค่าอรรถประโยชน์ตามกลุ่มย่อยตามลักษณะทางประชากร ได้แก่ เพศ อายุ โรคประจำตัว ประวัติการสูบบุหรี่ และประวัติการดื่มเหล้าหรือเครื่องดื่มผสมแอลกอฮอล์ ผลการศึกษา: ค่าอรรถประโยชน์เฉลี่ย (SD) จากน้อยไปหามาก คือ 0.79 ± 0.13 (VAS), 0.84 ± 0.18 (EQ-5D-3L), 0.92 ± 0.11 (Hybrid model)  0.93 ± 0.12 (cTTO model) และ 0.94 ± 0.10 (DCE model) ค่า ICC แสดงคู่วิธีที่สอดคล้องกันในระดับยอดเยี่ยม ได้แก่ cTTO model-Hybrid model, cTTO model-DCE model, DCE model-Hybrid model แต่พบว่า VAS และ EQ-5D-3L และ EQ-5D-5L มีความสอดคล้องระดับแย่ พบว่าเพศหญิงและผู้สูบบุหรี่มีค่าอรรถประโยชน์ EQ-5D-3L, cTTO model, DCE model และ Hybrid model ต่ำกว่าเพศชายและผู้ที่ไม่สูบบุหรี่ (P-value < 0.05) สรุป: EQ-5D-5L (DCE model) เป็นวิธีที่ดีที่สุดในการหาประเมินอรรถประโยชน์สำหรับนักศึกษาปริญญาตรีเพราะสามารถจำแนกค่าอรรถประโยชน์ได้ระหว่างกลุ่มย่อย คำสำคัญ: คุณภาพชีวิตทางด้านสุขภาพ, ค่าอรรถประโยชน์, แบบสอบถามอีคิวไฟว์ดีทรีแอล, แบบสอบถามอีคิวไฟว์ดีไฟว์แอล, ความสอดคล้องกัน    Abstract Objective: To investigate the performance and agreement of utility scores elicited from various elicitation methods of EQ-5D-3L, the three value sets of the EQ-5D-5L (cTTO model, DCE model, and Hybrid model), and VAS among undergraduate students. Methods: A cross-sectional survey study was conducted with 393 undergraduate students between March and April 2022. Intraclass correlation (ICC) was used to determine the agreement of utility values derived from five approaches. Multiple regression was used to compare the utility values with differences in gender, age, smoking status, alcohol consumption and medical conditions. Results: The mean (SD) utility values derived from five approaches were as follows: 0.79 ± 0.13 (VAS), 0.84 ± 0.18 (EQ-5D-3L), 0.92 ± 0.11 (Hybrid model)  0.93 ± 0.12 (cTTO model), and 0.94 ± 0.10 (DCE model). The ICC showed excellent agreement among these following pairs: cTTO model-Hybrid model, cTTO model-DCE model, DCE model-Hybrid model. However, the agreement of utility values from VAS and EQ-5D-3L and EQ-5D-5L was poor. Females and smokers reported lower the utility values from EQ-5D-3L, cTTO model, DCE model, and the Hybrid model than their counterparts (P-value < 0.05).  Conclusion: The EQ-5D-5L (DCE model) is the best elicitation method among undergraduate students because it can discriminate utility scores between predefined subgroups. Keywords: Health-related quality of life, Utility scores, EQ-5D-3L, EQ-5D-5L, agreemen