Does EQ-5D Tell the Whole Story? Statistical Methods for Comparing the Thematic Coverage of Clinical and Generic Outcome Measures, With Application to Breast Cancer.

OBJECTIVES: This study aimed to develop the following: (1) methods for assessing claims in any specific application that a generic outcome measure, such as EQ-5D is deficient in its coverage of 1 or more specified domains, and (2) a simple method of judging whether any such deficiency is likely to be quantitatively important enough to call into question evaluations based on the generic instrument. Also to demonstrate the applicability of the methods in the important area of breast cancer. METHODS: The methodology requires a data set with observations from a generic instrument (eg, EQ-5D) and also a more comprehensive clinical instrument (eg, FACT-B [Functional Assessment of Cancer Therapy - Breast]). A standardized 3-component statistical analysis is proposed for investigating the claim that the generic measure inadequately captures some specified dimension covered by the latter instrument. A theoretically based upper bound on the bias induced by deficient coverage is derived based on the assumption that the designers of the (k-dimensional) generic instrument did succeed in identifying the k most important domains. RESULTS: Data from the MARIANNE breast cancer trial were analyzed and results suggested that impacts on personal appearance and relationships may be inadequately represented by EQ-5D. Nevertheless, the indications are that the bias in quality-adjusted life-year differences from deficient coverage by EQ-5D is likely to be modest. CONCLUSIONS: The methodology offers a systematic approach to determining whether there is clear evidence consistent with any claim that a generic outcome measure such as EQ-5D misses an important specific domain. The approach is readily implementable using data sets that are available in many randomized controlled trials.

Economic gradients in loneliness, social isolation and social support: Evidence from the UK Biobank.

Despite the substantial literature on how loneliness is associated with poor health and premature mortality, there is little detailed research on the extent of its economic gradients. We provide this evidence using a sample of around 400,000 respondents aged 40-70 years from the UK Biobank, who were assessed between 2006 and 2010. We focus on differences in loneliness, as well as social isolation and a lack of social support, across educational attainment, household income, local area deprivation, and recent experience of financial stress. We employ two statistical approaches, the first exploiting the large sample size and detailed geographical information about where respondents live, so we compare individuals who differ in their economic status but reside within the same postcode district. The second approach exploits the fact that for around 36,000 respondents we observe their social health and economic circumstances at two points in time (second wave of assessment conducted between 2014 and 2020), so we conduct a panel analysis that accounts for intercorrelations between the social health measures, and controls for incomplete follow-up of panel members. Across both approaches, we find a substantially higher probability of reporting loneliness, social isolation and a lack of social support, for men and women with lower economic status. Together with the existing health-loneliness literature, these findings establish a 'loneliness pathway' contributing to health inequalities, and consequently a need for effective interventions that might address loneliness and social isolation as part of a broad policy initiative on health inequalities.

Mapping between EQ-5D-3L and EQ-5D-5L: A survey experiment on the validity of multi-instrument data.

EQ-5D is a 5-item questionnaire instrument designed to measure health-related quality of life. It is extremely important, since it is used to measure health benefits in many studies providing evidence for reimbursement decisions by the National Institute for Health and Care Excellence in England and similar policy bodies in other countries. EQ-5D has been redesigned in a more detailed form (EQ-5D-5L), but much existing cost-effectiveness evidence is based on the older version (EQ-5D-3L). Statistical mapping from one version to another is widely used, exploiting data from multi-instrument surveys incorporating both variants. However, little is known about the robustness of data from such multi-instrument surveys. We design a randomized experiment to investigate whether inclusion of both versions at different stages in a single interview gives a reliable picture of the relationship between health measures from the two instruments and embed it in individual interviews from the UK Understanding Society household panel. We find that sequencing of the two versions of EQ-5D within an interview has a significant impact not only on the resulting data but also on the estimated mapping models. We illustrate the non-negligible effects in two real-world cost-effectiveness examples and discuss the implications for future multi-instrument survey design.

Market concentration, supply, quality and prices paid by local authorities in the English care home market.

We investigate the impact of exogenous local conditions which favor high market concentration on supply, price and quality in local markets for care homes for older people in England. We extend the existing literature in: (i) considering supply capacity as a market outcome alongside price and quality; (ii) taking account of the chain structure of care home supply and differences between the nursing home and residential care home sectors; (iii) using an econometric approach based on reduced form relationships that treats market concentration as a jointly determined outcome of a complex market. We find that areas susceptible to a high degree of market concentration tend to have greatly restricted supply of care home places and (to a lesser extent) a higher average public cost, than areas susceptible to low degree of market concentration. There is no significant evidence that conditions favoring high market concentration affect average care home quality.

An International Comparison of EQ-5D-5L and EQ-5D-3L for Use in Cost-Effectiveness Analysis.

OBJECTIVES: To estimate the impact of using EQ5D-5L (5L) compared with EQ5D-3L (3L) in cost-effectiveness analyses in 6 countries with 3L and 5L values: Germany, Japan, Korea, The Netherlands, China, and Spain. METHODS: Eight cost-effectiveness analyses based on clinical studies with 3L provided 11 pairwise comparisons. We estimated cost-effectiveness by applying the appropriate country values for 3L to observed responses. We re-estimated cost-effectiveness for each country by predicting the 5L tariff score for each respondent, for each country, using a previously published mapping method. We compared results in terms of impact on estimated incremental quality-adjusted life-year (QALY) gain and cost-effectiveness ratios. RESULTS: For most countries the impact of moving from 3L to 5L is to lower the incremental QALY gain in the majority of comparisons. The only exception to this was Japan, where 4 out of 11 cases (37%) saw lower QALYs gained when using 5L. The mean and median reductions in health gain, in those case studies where 5L does lead to lower health gain, are largest in The Netherlands (84% mean reduction, 41% median reduction), Germany (68% and 27%), and Spain (30% and 31%). For most countries, those studies where 5L leads to lower health gain see larger reductions than the gains in studies showing the opposite tendency. CONCLUSIONS: Overall, 3L and 5L are not interchangeable in these countries. Differences between results are large, but the direction of change can be unpredictable. These findings should prompt further investigation into the reasons for differences.

Biomarkers, disability and health care demand.

Using longitudinal data from a representative UK panel, we focus on a group of apparently healthy individuals with no history of disability or major chronic health condition at baseline. A latent variable structural equation model is used to analyse the predictive role of latent baseline biological health, indicated by a rich set of biomarkers, and other personal characteristics, in determining the individual's disability state and health service utilisation five years later. We find that baseline biological health affects future health service utilisation very strongly, via progression to functional disability channel. We also find systematic income gradients in future disability risks, with those of higher income experiencing a lower progress to disability. Our model reveals that observed pro-rich inequity in health care utilisation, is driven by the fact that higher-income people tend to make greater use of health care treatment, for any given biological health and disability status; this is despite the lower average need for treatment shown by the negative association of income with both baseline ill biological health and disability progression risk. Factor loadings for latent baseline health show that a broader set of blood-based biomarkers, rather than the current focus mainly on blood pressure, cholesterol and adiposity, may need to be considered for public health screening programs.

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

BACKGROUND: 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. OBJECTIVES: 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. DATA SOURCES: 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. MAIN METHODS DEVELOPED: 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. RESULTS: 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. LIMITATIONS: 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. CONCLUSIONS: 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). FUTURE RESEARCH PRIORITIES: 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. FUNDING: 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).

Coherent decisions about which health services and treatments to provide rely on economic analysis to weigh potential health benefits against costs. For decisions to be consistent across the whole health service, benefits need to be counted in the same way for patients with different health problems. This is accomplished by using a unit of measurement for treatment outcomes called the quality-adjusted life-year. The best way to calculate quality-adjusted life-years is to ask patients taking part in clinical studies to fill in specially designed questionnaires to describe their health in a simple, standardised way. However, clinical trials often record patient outcomes in different ways, leaving economic analysts without the necessary information to calculate quality-adjusted life-years. A way to overcome this problem (known as 'statistical mapping') is to use the available clinical data to predict the responses that would have been made by trial participants to the standard questionnaire. This requires analysis of data from an additional study in which patients have provided both types of outcome data to construct a statistical 'mapping model'. Mapping is widely used in practice, but it is often based on simple mapping models that in some circumstances systematically mispredict and may consequently give a false picture of the real health benefits of treatments. This is important because it influences decisions about which treatments are available in the NHS; it has real effects on patients, clinicians, industry and the general public. Our objectives are to develop promising new statistical mapping models specifically designed for different clinical contexts and to compare them using patient data in different disease areas. We have also developed an approach for judging the outcome of a mapping study. We find that the new methods work better than existing methods in terms of their ability to fit the data and avoid systematic bias.

Using biomarkers to predict healthcare costs: Evidence from a UK household panel.

We investigate the extent to which healthcare service utilisation and costs can be predicted from biomarkers, using the UK Understanding Society panel. We use a sample of 2314 adults who reported no history of diagnosed long-lasting health conditions at baseline (2010/11), when biomarkers were collected. Five years later, their GP, outpatient (OP) and inpatient (IP) utilisation was observed. We develop an econometric technique for count data observed within ranges and a method of combining administrative reference cost data with the survey data without exact individual-level matching. Our composite biomarker index (allostatic load) is a powerful predictor of costs: for those with a baseline allostatic load of at least one standard deviation (1-s.d.) above mean, a 1-s.d. reduction reduces GP, OP and IP costs by around 18%.

The EQ-5D-5L Value Set for England: Findings of a Quality Assurance Program.

OBJECTIVES: Five-level EuroQol 5-dimensional questionnaire (EQ-5D-5L) values for several countries now exist. Decision makers require confidence in the underlying data and statistical analyses before advocating their use. Independent quality assurance of the published English value set is reported here. METHODS: Data from 996 participants, and code to run published statistical models, were provided for inspection. The main elements of the study were 10 lead-time trade-off (TTO) experiments and 7 discrete choice experiments (DCEs). Data quality was examined and tested with respect to subsequent assumptions made in the statistical analysis. We examined the statistical analysis including model specification and estimation methods. RESULTS: The TTO experiments covered less than 3% of the possible 3125 5-level health states. There is strong evidence, both direct (self-reported) and indirect (poor data quality), that many participants found tasks difficult or did not engage effectively. Forty-seven percent of respondents valued more than 20% of states inconsistently, which is double the 3-level rate. The DCEs covered 12.5% of possible states and 0.01% of possible 2-state comparisons. The design precludes examination of inconsistent responses. Several aspects of the statistical model conflict with the data and underlying experimental design. The model is unidentified. The Bayesian approach relies on unjustified, informative priors. There is a clear failure to achieve convergence. CONCLUSION: Significant limitations are identified with the quality of the valuation data and the subsequent statistical analysis that underpin the English EQ-5D-5L value set. A new program of further development, including a new data collection initiative, should be considered to put the EQ-5D-5L on a sufficiently firm evidential basis for healthcare decision making.

Biomarkers as precursors of disability.

Some social surveys now collect physical measurements and markers derived from biological samples, in addition to self-reported health assessments. This information is expensive to collect; its value in medical epidemiology has been clearly established, but its potential contribution to social science research is less certain. We focused on disability, which results from biological processes but is defined in terms of its implications for social functioning and wellbeing. Using data from waves 2 and 3 of the UK Understanding Society panel survey as our baseline, we estimated predictive models for disability 2-4 years ahead, using a wide range of biomarkers in addition to self-assessed health (SAH) and other socio-economic covariates. We found a quantitatively and statistically significant predictive role for a large set of nurse-collected and blood-based biomarkers, over and above the strong predictive power of self-assessed health. We also applied a latent variable model accounting for the longitudinal nature of observed disability outcomes and measurement error in in SAH and biomarkers. Although SAH performed well as a summary measure, it has shortcomings as a leading indicator of disability, since we found it to be biased in the sense of over- or under-sensitivity to certain biological pathways.

The Impact of Moving from EQ-5D-3L to -5L in NICE Technology Appraisals.

BACKGROUND: The EuroQol-5 Dimension (EQ-5D) instrument is the National Institute for Health and Care Excellence (NICE)'s preferred measure of health-related quality of life (QoL) in adults. The three-level (3L) value set is currently recommended for use, but the five-level (5L) set is increasingly being used in practice. OBJECTIVE: We aimed to explore the impact of moving from 3L to 5L in NICE appraisals. METHODS: We adapted our existing mapping for use with health state utility values derived from a population where the original distribution of utilities was unknown. We used this mapping to estimate 5L utilities for 21 comparisons of interventions from models used in NICE technology appraisal decision making, covering a range of disease areas. RESULTS: All utilities increased using 5L, and the differences between highest and lowest utilities decreased. In ten oncology comparisons, using 5L generally increased the incremental quality-adjusted life-years (QALYs) as the benefit from improving survival increased. In four non-oncology comparisons where the intervention improved QoL only, the incremental QALYs decreased as the benefit of improving QoL was reduced. In seven non-oncology comparisons where interventions improved survival and QoL, there was a trade-off between increasing the benefit from survival and decreasing the benefit from improving QoL. CONCLUSION: 3L and 5L lead to substantially different estimates of incremental QALYs and cost effectiveness. The direction and magnitude of the change is not consistent across case studies. Using 5L instead of 3L may lead to different reimbursement decisions. NICE will face inconsistencies in decision making if it uses 3L and 5L concurrently.

EQ-5D-5L versus EQ-5D-3L: The Impact on Cost Effectiveness in the United Kingdom.

OBJECTIVES: To model the relationship between the three-level (3L) and the five-level (5L) EuroQol five-dimensional questionnaire and examine how differences have an impact on cost effectiveness in case studies. METHODS: We used two data sets that included the 3L and 5L versions from the same respondents. The EuroQol Group data set (n = 3551) included patients with different diseases and a healthy cohort. The National Data Bank data set included patients with rheumatoid disease (n = 5205). We estimated a system of ordinal regressions in each data set using copula models to link responses of the 3L instrument to those of the 5L instrument and its UK tariff, and vice versa. Results were applied to nine cost-effectiveness studies. RESULTS: Best-fitting models differed between the EuroQol Group and the National Data Bank data sets in terms of the explanatory variables, copulas, and coefficients. In both cases, the coefficients of the covariates and latent factors between the 3L and the 5L instruments were significantly different, indicating that moving between instruments is not simply a uniform re-alignment of the response levels for most dimensions. In the case studies, moving from the 3L to the 5L caused a decrease of up to 87% in incremental quality-adjusted life-years gained from effective technologies in almost all cases. Incremental cost-effectiveness ratios increased, often substantially. Conversely, one technology with a significant mortality gain saw increased incremental quality-adjusted life-years. CONCLUSIONS: The 5L shifts mean utility scores up the utility scale toward full health and compresses them into a smaller range, compared with the 3L. Improvements in quality of life are valued less using the 5L than using the 3L. The 3L and the 5L can produce substantially different estimates of cost effectiveness. There is no simple proportional adjustment that can be made to reconcile these differences.

Concordance of health states in couples: Analysis of self-reported, nurse administered and blood-based biomarker data in the UK Understanding Society panel.

We use self-reported health measures, nurse-administered measurements and blood-based biomarkers to examine the concordance between health states of partners in marital/cohabiting relationships in the UK. A model of cumulative health exposures is used to interpret the empirical pattern of between-partner health correlation in relation to elapsed relationship duration, allowing us to distinguish non-causal correlation due to assortative mating from potentially causal effects of shared lifestyle and environmental factors. We find important differences between the results for different health indicators, with strongest homogamy correlations observed for adiposity, followed by blood pressure, heart rate, inflammatory markers and cholesterol, and also self-assessed general health and functional difficulties. We find no evidence of a "dose-response relationship" for marriage duration, and show that this suggests - perhaps counterintuitively - that shared lifestyle factors and homogamous partner selection make roughly equal contributions to the concordance we observe in most of the health measures we examine.

Econometric modelling of multiple self-reports of health states: The switch from EQ-5D-3L to EQ-5D-5L in evaluating drug therapies for rheumatoid arthritis.

EQ-5D is used in cost-effectiveness studies underlying many important health policy decisions. It comprises a survey instrument describing health states across five domains, and a system of utility values for each state. The original 3-level version of EQ-5D is being replaced with a more sensitive 5-level version but the consequences of this change are uncertain. We develop a multi-equation ordinal response model incorporating a copula specification with normal mixture marginals to analyse joint responses to EQ-5D-3L and EQ-5D-5L in a survey of people with rheumatic disease, and use it to generate mappings between the alternative descriptive systems. We revisit a major cost-effectiveness study of drug therapies for rheumatoid arthritis, mapping the original EQ-5D-3L measure onto a 5L valuation basis. Working within a comprehensive, flexible econometric framework, we find that use of simpler restricted specifications can make very large changes to cost-effectiveness estimates with serious implications for decision-making.

Birth-cohort trends in older-age functional disability and their relationship with socio-economic status: Evidence from a pooling of repeated cross-sectional population-based studies for the UK.

We examine birth-cohort trends behind recent changes in the prevalence of functional disability in the older population living in private households in the United Kingdom (UK). By using three different socio-economic indicators available in the nationally representative cross-sectional data on older individuals interviewed between 2002 and 2012 in the Family Resource Survey (FRS) (96,733 respondents), we investigate the extent to which the overall trends have been more favourable among more advantaged than disadvantaged socioeconomic groups. Compared to the cohort of people born in 1924, successive cohorts of older men have lower odds of having at least one functional difficulty (FD), whereas no significant trend was found for women. Among people with at least one FD, however, the number of disabilities increases for each successive cohort of older women (incidence rate ratio 1.027, 95% confidence interval 1.023 to 1.031, P < 0.001) and men (incidence rate ratio 1.028, 95% confidence interval 1.024 to 1.033, P < 0.001). By allowing interactions between birth cohort and SES indicators, a significant increasing cohort trend in the number of reported FDs was found among older men and women at lower SES, whereas an almost stable pattern was observed at high SES. Our results suggest that the overall slightly increasing birth-cohort trend in functional difficulties observed among current cohorts of older people in the UK hides underlying increases among low SES individuals and a relative small reduction among high SES individuals. Further studies are needed to understand the causes of such trends and to propose appropriate interventions. However, if the SES differentials in trends in FDs observed in the past continue, this could have important implications for the future costs of the public system of care and support for people with care needs.

Do household surveys give a coherent view of disability benefit targeting?: a multisurvey latent variable analysis for the older population in Great Britain.

We compare three major UK surveys, the British Household Panel Survey, Family Resources Survey and the English Longitudinal Study of Ageing, in terms of the picture that they give of the relationship between disability and receipt of the attendance allowance benefit. Using the different disability indicators that are available in each survey, we use a structural equation approach involving a latent concept of disability in which probabilities of receiving attendance allowance depend on disability. Despite major differences in design, once sample composition has been standardized through statistical matching, the surveys deliver similar results for the model of disability and receipt of attendance allowance. Provided that surveys offer a sufficiently wide range of disability indicators, the detail of disability measurement appears relatively unimportant.