Valuing SF-6D Health States Using a Discrete Choice Experiment

Quality-Adjusted Life Expectancy by Socioeconomic Disadvantage and Remoteness Area: Population Norms for Australia

OBJECTIVES

Detailed and current information on the social distribution of health across gradients of socioeconomic disadvantage and geographic remoteness in Australia is limited. Quality-adjusted life expectancy (QALE) is a useful summary measure of population health, combining mortality and health-related quality of life. This cross-sectional study estimates QALE by year age for the Australian population across sex, socioeconomic disadvantage, and remoteness groups, providing a baseline for equity-focused health technology assessments.

METHODS

Short Form-6 Dimension data were obtained from the Household, Income, and Labor Dynamics survey for 2022 and 2023, from which mean utility scores by age were estimated using linear regression. Mortality data for 2022 from the Australian Bureau of Statistics were used to construct life tables to generate life expectancy (LE), into which health-related quality of life was incorporated to derive age and sex-specific QALE across quintiles of socioeconomic disadvantage and remoteness areas.

RESULTS

At birth, individuals in the most disadvantaged quintile had an undiscounted LE of 78.7 years and QALE of 43.9 years compared with those in the least-disadvantaged quintile with undiscounted LE of 86.3 years and QALE of 55.6 years. A small gradient existed across remoteness areas, with individuals residing in major cities experiencing 2.6 years greater LE and QALE of 3.8 years (both undiscounted) above those in outer regional or remote areas.

CONCLUSIONS

Our study demonstrates major inequalities associated with socioeconomic disadvantage and remoteness for LE and QALE. The social distribution of health status provided in this study can be used in future equity-informed economic evaluations.

Developing an Australian Value Set for the Recovering Quality of Life-Utility Index Instrument Using Discrete Choice Experiment With Duration

OBJECTIVES

The Recovering Quality of Life-Utility Index (ReQoL-UI) instrument was designed to measure the quality-of-life outcomes for people older than 16 years with mental health problems. We aimed to elicit societal preferences for the ReQoL-UI health states to facilitate better decision making in Australia.

METHODS

A discrete choice experiment with duration was embedded in a self-completed online survey and administered to a representative sample (n = 1019) of the Australian adult population aged 18 years and older stratified by age, sex, and geographic location. A partial subset design discrete choice experiment was used with 3 fixed attributes and 5 varying attributes, containing 240 choice tasks that were divided into 20 blocks so that each respondent was assigned a block of 12 choice tasks. The value set was modeled using the conditional logit model with utility decrements directly anchored on the 0 to 1 dead-full health scale. Preference heterogeneity was tested using a mixed logit model.

RESULTS

The final value set reflects the monotonic nature of the ReQoL-UI descriptive systems where the best health state defined by the descriptive system has a value of 1 and the worst state has a value of -0.585. The most important dimension was physical health problems, whereas the least important attribute was self-perception. Sensitivity and preference heterogeneity analyses revealed the stability of the value set.

CONCLUSIONS

The value set, which reflects the preferences of the Australian population, facilitates the calculation of an index for quality-adjusted life-years in mental health intervention cost-utility analyses.

Muscle growth and anabolism in intensive care survivors (GAINS 2.0): Protocol for a multi-centre randomised; placebo controlled clinical trial of nandrolone in deconditioned adults recovering from critical illness

BACKGROUND

Intensive care patients can experience significant long-term impairment in mobility and function caused by their critical illness. A potential contributory factor apart from critical illness polymyoneuropathy is the low levels of anabolic hormones in these patients. Testosterone levels in critically ill patients are extremely low, even in the latter recovery phase. A potential solution to critical illness myopathy may be to provide anabolic support in addition to standard care (early physiotherapy) to further improve gains in strength.

RESEARCH QUESTION

This project aims to test whether a synthetic testosterone (nandrolone) improves muscle strength in ICU survivors compared to placebo.

METHODS

GAINS 2.0 is a multicentre, randomised, double blinded placebo-controlled trial which will allocate ICU patients in a 1:1 ratio to nandrolone compared to placebo which commenced recruitment in July 2023. Adult patients admitted to the ICU, receiving nutrition for a minimum of 24 hours with an ICU stay of at least 5 days, or patients with significant weakness as result of their ICU stay (such that they are unable to mobilise independently) will be eligible to participate. Sample size will be 54 patients. Patients will be randomised to receive nandrolone 100mg (males) / 50mg(females) weekly for 3 weeks in addition to standard care. The co-primary outcomes are the time to walking with one person assisting (Intensive Care Mobility scale = 8 or more, in days from randomisation), change in muscle strength measured by the Medical Research Council (MRC) muscle strength sum score from enrolment to hospital discharge and number of days out of hospital up to day 90 post-discharge. Secondary outcomes are grip strength measured by hand-held dynamometry. SF-36 scores (quality of life and functional domains), and days to return to work, for those working pre-ICU, will be collected via a 3-month phone follow-up.

CONCLUSIONS

A previous pilot feasibility trial showed that nandrolone is safe and feasible. We hypothesize nandrolone will improve muscle strength and physical functioning at hospital discharge and at follow-up. The results of this trial may have significant interest to clinicians and patients considering the large and increasing number of patients surviving intensive care but with physical impairment. This trial may have significant implications on lowering hospital costs and daily adjusted life years.

TRIAL REGISTRY

anzctr.org.au; No.: ACTRN12623000729628 URL: anzctr.org.au.

Developing a utility value set for the Gambling Quality of Life Scale-Brief (GQoLS-Brief) using a discrete choice experiment

OBJECTIVES

The Gambling Quality of Life Scale -brief (GQoLS-Brief) assesses the impact of gambling disorder (GD) on quality of life (QoL). Preference-based measures are essential for obtaining the quality adjustment weight (i.e. utility score) needed to calculate quality-adjusted life years (QALYs) in economic evaluations. We aimed to derive a value set for the GQoLS-Brief.

METHODS

We employed a discrete choice experiment for preference elicitation. An online survey was administered (n = 928). Respondents completed 10 choice tasks, each presenting two GQoLS-Brief health states alongside life expectancy. Conditional logit regression, parameterized to fit the QALY framework, was used for data analysis. QALY weights for each health state defined by the GQoLS-Brief were calculated.

RESULTS

The estimated coefficients from the conditional logit models aligned with expectations: utility increased with survival time and decreased with QoL impairment. Utility values for health states ranged from - 1.48 (worse than death) to 1.0. "Financial difficulties" exhibited the highest utility decrement, followed by "Sleep disturbance related to financial difficulties."

CONCLUSIONS

This reference set facilitates the calculation of QALYs for economic evaluations of GD interventions. The weight of subjective financial difficulties underscores the need for therapeutic interventions to target this aspect.

Valuation survey for SF-6Dv2 in Japan based on the international protocol

PURPOSE

The SF-6D Classification System was recently updated (SF-6Dv2). We performed a valuation survey to construct a value set for the SF-6Dv2 in Japan.

METHODS

An online discrete choice experiment (DCE) with duration was used to estimate a value set for the SF-6Dv2 for Japan based on public preferences. The target sample number was 3800. Respondents were asked to complete 15 choice tasks. A conditional logit model that estimates interactions between time and each dimension was used to develop the value set.

RESULTS

The collected sample included 3933 respondents for the DCE tasks. The results of all the unconstrained models showed some inconsistencies. In particular, inconsistencies in the two most severe levels of the role limitation (RL) and vitality (VT) dimensions were observed in all models. The number of inconsistencies was smallest in a core model (n = 3) and in a model for core and common health states (n = 2). The physical functioning (PF) and pain (PA) dimensions had the greatest influence on utility at the overall level across all models. RL, VT, and social functioning (SF) had smaller overall impacts on utility. The PF weights for the two most severe levels are much lower than those in the UK and Australia. The Japanese scores tended to be lower compared with the UK SF-6Dv2 scores.

CONCLUSION

We obtained a value set for Japan (model 5). With the development of this value set, it is now possible to calculate quality-adjusted life years for economic evaluation in Japan when the SF-6Dv2 has been used.

A new SF-6Dv2 value set based on a hybrid model using SG, cTTO, and DCE data

OBJECTIVE

To develop a value set for the Short-Form 6-Dimension version 2 (SF-6Dv2) by incorporating societal preferences obtained from three distinct approaches: Standard Gamble (SG), composite Time Trade-Off (cTTO), and Discrete Choice Experiment (DCE).

METHODS

Data were gathered from the general population of Quebec, Canada, using the standardized valuation protocol developed by EuroQol for the cTTO and DCE tasks, as well as the valuation protocol developed by Sheffield University for the SG. The SG and cTTO data were analyzed using OLS, GLS, GLS Tobit, and heteroskedastic Tobit models. Conditional logit model was used for the DCE, while hybrid, hybrid Tobit, and heteroskedastic hybrid were applied to analyze the combined data from SG, cTTO, and DCE. The performance of models was assessed using mean absolute error (MAE), the logical consistency of the parameters, and significance levels.

RESULTS

Over 56,000 observations collected from the SG, cTTO, and DCE were analyzed. The utility values generated by DCE were generally lower than those provided by cTTO and SG. Among the models tested, the heteroskedastic hybrid model demonstrated the best fit in terms of logical consistency and statistically significant coefficients. This model generated a value set ranging from -0.216 for the worst health state (555655) to 1 for full health (111111), with 0.52% of the values being negative and a MAE of 0.281. Among dimensions, the largest decrements were consistently found in the pain dimension, highlighting its significant impact on overall health state valuations.

CONCLUSION

A heteroskedastic hybrid model using data from SG, cTTO, and DCE was identified as the most effective approach for generating the SF-6Dv2 value set and is expected to provide key input for healthcare decision-making.

Evaluation of health-related quality of life changes in an Australian rapid access chest pain clinic

OBJECTIVE

To evaluate the impact of absolute cardiovascular risk counselling on quality-of-life indices within a chest pain clinic.

DATA SOURCES AND STUDY SETTING

Primary data was collected at the Royal Hobart Hospital, Australia, between 2014 and 2020.

STUDY DESIGN

Patients attending an Australian chest pain clinic were randomised into a prospective, open-label, blinded-endpoint study over a minimum 12-months follow-up.

DATA COLLECTION / EXTRACTION METHODS

The SF-36 questionnaire was completed at baseline/follow-up and SF-6D multi-attribute utility instrument's health state utilities (HSU) were generated using SF-36 responses and the SF-6D's Australian tariff. SF-6D minimal important difference was 0.04 points. Absolute cardiovascular risk was also stratified into high/intermediate/low-risk categories for exploratory analysis of summary HSUs and dimensional scores. ANZCTR registration number 12617000615381 (registered 28/4/17).

PRINCIPAL FINDINGS

Of n = 189 patients enrolled, HSUs were generated for 96% at baseline (intervention n = 93, usual care n = 88) and 61% at follow-up. There were no statistical differences in age, sex, absolute cardiovascular risk or mean HSU between groups at baseline. Summary HSUs improved more for the intervention group and the median between-group difference exceeded the minimal important difference threshold (intervention 0.16 utility points, control 0.10 utility points). For Intervention patients with high absolute risk (≥ 15%), HSU did not significantly change.

CONCLUSIONS

Absolute cardiovascular risk counselling in a chest pain clinic yielded clinically meaningful improvement in health-related quality of life.

The Short Form 6 Dimensions (SF-6D): Development and Evolution

This paper considers the development and evolution of the short-form 6 dimensions (SF-6D), a generic preference-weighted measure consisting of a health classification with accompanying value set that was developed from one of the widest used health related quality of life measures, the SF-36 health survey. This enabled health state utility values to be directly generated from SF-36 and SF-12 data for a range of purposes, including to produce quality adjusted life years for use in economic evaluation of healthcare interventions across a range of different conditions and treatments. This paper considers the rationale for the development of the measure, the development process, performance and how the SF-6D has evolved since its conception. This includes the development of an updated version, SF-6D version 2 (SF-6Dv2), which was generated to deal with some criticisms of the first version, and now includes a standalone version for inclusion in studies without relying on use of SF-36 or SF-12. Valuation methods have also evolved, from standard gamble in-person interviews to online discrete choice experiment surveys. International work related to the SF-6Dv1 and SF-6Dv2 is considered. We also consider recommendations for use, highlighting key psychometric evidence and reimbursement agency recommendations.

Deriving a Preference-Weighted Measure for People With Hypoglycemia From the Hypo-RESOLVE QoL

OBJECTIVES

Hypoglycemia affects the health-related quality of life (HRQoL) of people living with diabetes (PwD), and existing preference-weighted measures do not capture all important aspects. The study aimed to generate a preference-weighted measure capturing the HRQoL impact of hypoglycemia in PwD.

METHODS

Items for the health-state classification system were selected from the hypoglycemia-specific Hypo-RESOLVE QoL measure using relevance in cognitive interviews, translatability, suitability for valuation, endorsement by patient advisors and experts, and psychometric performance in a large survey of PwD. Second, an online valuation survey using discrete choice experiment (DCE) with survival attribute was conducted with members of the UK public. DCE data were modeled using conditional logit analysis and results scaled to produce preference weights for the classification system on a scale in which 1 is equivalent to full health, 0 is equivalent to dead, and below 0 is worse than dead.

RESULTS

The health-state classification system consists of 8 items reflecting the factors of the Hypo-RESOLVE QoL (psychological, social, and physical aspects). The valuation survey was completed by 1000 members of the UK public, representative for age and sex. Good understanding of DCE tasks was demonstrated. The item "do what I want to do in my life" had the largest preference weight, and "find it hard to stop thinking about my glucose levels" had the smallest.

CONCLUSIONS

This study generated Hypo-RESOLVE QoL-8D, a preference-weighted measure capturing the HRQoL impact of hypoglycemia in PwD, with UK general public preference weights. The measure can be generated from Hypo-RESOLVE QoL data.

How Much Better is Faster? Empirical Tests of QALY Assumptions in Health-Outcome Sequences

OBJECTIVES

This study was designed to test hypotheses regarding the path dependence of health-outcome values in the form of linear additivity of health-state utilities and diminishing marginal utility of health outcomes.

METHODS

We employed a discrete-choice experiment to quantify patient treatment preferences for major depressive disorder. In a series of choice questions, participants evaluated seven symptom-improvement sequences and out-of-pocket costs over 6-week durations. Money-equivalent values were derived from a deductive latent-class mixed-logit analysis.

RESULTS

The discrete-choice experiment was completed by 751 respondents with self-reported major depressive disorder recruited from an online commercial panel. The class-membership probability was 0.83 for latent-class preferences consistent with supporting relative importance weights for all symptom-improvement sequences in the study design. First, we found strong support for diminishing marginal utility in symptom-improvement sequences. The money-equivalent value of an initial week of normal mood was $147 (95% confidence interval: $128, $166) and a second week of normal mood was $70 ($49, $91). Furthermore, for short treatment durations where conventional discounting was not a factor, equivalent changes in health status were valued more highly for an earlier onset of effect: holding subsequent symptom patterns constant, $338 (211, 454) versus $70 (49, 91) for improvements starting in week 2 versus week 3 and $147 ($128, $166) versus $29 (-$4, $64) for improvements starting in week 3 versus week 4.

CONCLUSIONS

Our findings imply that conventional quality-adjusted life-year calculations in which health values are assumed to be path independent can understate the value of health improvements that appear earlier in a sequence.

Quality of life impacts associated with comorbid insomnia and depression in adult population

PURPOSE

Health-related quality of life (HRQoL) impacts of insomnia and depression (as separated entities) have been well investigated in previous studies. However, little is known about the effect of comorbid insomnia and depression on HRQoL. This study aimed to assess the impacts of insomnia and depression, in combination or alone, on HRQoL in Australian adults.

METHODS

Data used in this study were obtained from the large-scale longitudinal Household, Income and Labour Dynamics in Australia (HILDA) survey. Insomnia was defined using key insomnia criteria of DSM-V. Depression was based on validated cut-off points of the Mental Health Inventory-5 (MHI-5) (scores ≤ 62) in the base case analysis. HRQoL expressed as utility scores (ranging from 0 to 1) were measured using the Short-Form 6-Dimension (SF-6D) converted from the SF-36 and valued using an Australian scoring algorithm. Multi-level modelling was applied to assess the effect of insomnia and/or depression on utility scores.

RESULTS

The study analysed 30,972 observations from 10,324 individuals (age [mean ± SD]: 45.7 ± 16.5, female: 54.6%). The proportion of individuals with insomnia only, depression only, and comorbid insomnia and depression was 11.3%, 11.6%, and 8.2%, respectively. The interaction effect suggested the combined impact of insomnia and depression on health-related quality of life beyond the sum of their individual effects. Marginal mean difference in utility scores for insomnia only, depression only, and the comorbidity relative to no insomnia or depression was -0.058 (SE: 0.003, Cohen's d: 0.420, small effect), -0.210 (SE: 0.003, Cohen's d: 1.530, large effect), and -0.291 (SE: 0.004, Cohen's d: 2.120, large effect), respectively.

CONCLUSION

Comorbid depression and insomnia appear to have very large quality-of-life impacts. Furthermore, this is the first study that has estimated the magnitude of the impact of comorbid insomnia and depression on utility scores which can be utilised in future clinical or economic studies.

Japanese value set for the EORTC QLU-C10D: A multi-attribute utility instrument based on the EORTC QLQ-C30 cancer-specific quality-of-life questionnaire

PURPOSE

This study aimed to develop a Japanese value set for the EORTC QLU-C10D, a multi-attribute utility measure derived from the cancer-specific health-related quality-of-life (HRQL) questionnaire, the EORTC QLQ-C30. The QLU-C10D contains ten HRQL dimensions: physical, role, social and emotional functioning, pain, fatigue, sleep, appetite, nausea, and bowel problems.

METHODS

Quota sampling of a Japanese online panel was used to achieve representativeness of the Japanese general population by sex and age (≥ 18 years). The valuation method was an online discrete choice experiment. Each participant considered 16 choice pairs, randomly assigned from 960 choice pairs. Each pair included two QLU-C10D health states and life expectancy. Data were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life-year framework. Preference weights were calculated as the ratio of each dimension-level coefficient to the coefficient for life expectancy.

RESULTS

A total of 2809 eligible panel members consented, 2662/2809 (95%) completed at least one choice pair, and 2435/2662 (91%) completed all choice pairs. Within dimensions, preference weights were generally monotonic. Physical functioning, role functioning, and pain were associated with the largest utility weights. Intermediate utility weights were associated with social functioning and nausea; the remaining symptoms and emotional functioning were associated with smaller utility decrements. The value of the worst health state was - 0.221, lower than that seen in most other existing QLU-C10D country-specific value sets.

CONCLUSIONS

The Japan-specific QLU-C10D value set is suitable for evaluating the cost and utility of oncology treatments for Japanese health technology assessment and decision-making.

Estimating the SF-6Dv1 Value Set for a Population-Based Sample in Lebanon

OBJECTIVES

The SF-6Dv1 is a preference-based measure derived from the SF-36 for use in quality-adjusted life-year estimation for cost-utility analysis. Country-specific value sets for SF-6Dv1 are needed to reflect societal preferences but none are available for Lebanon and other Arabic countries. This study aimed to generate a value set for SF-6Dv1 for Lebanon and to compare results with the UK set.

METHODS

A sample of 249 health states defined by the SF-6Dv1 were valued by a representative sample of 577 members of the Lebanon general population, using standard gamble. Several multivariate regression models at mean and individual level were fitted to estimate utilities for all SF-6Dv1 states with selection of best fitting models based on predictive ability, consistency, and model fit. The best fitting models were compared with those fitted in the UK study.

RESULTS

Data from 553 eligible respondents providing 3308 valuations were used for the analysis. Lebanese values were consistently higher than UK values, indicating differences in preferences, and there were no negative values. The random effects model using only main effects was the best performing model. There were inconsistencies in 2 dimensions, thereby consistent models were estimated with values ranging from 0.367 to 1. The results are consistent with the UK results.

CONCLUSIONS

This study provides the first population-based value set for SF-6Dv1 health states for Lebanon, making it possible to generate quality-adjusted life-years for cost-utility analysis studies. The potential for applications of a standardized utility measure is enormous both in Lebanon and all Arab countries.

Development and Valuation of a Preference-Weighted Measure in Age-Related Macular Degeneration From the Vision Impairment in Low Luminance Questionnaire: A MACUSTAR Report

OBJECTIVES

This study generates VILL-UI (Vision Impairment in Low Luminance - Utility Index), a preference-weighted measure (PWM) derived from the VILL-33 measure for use in patients with age-related macular degeneration (AMD) and valued to generate United Kingdom and German preference weights.

METHODS

A PWM consists of a classification system to describe health and utility values for every state described by the classification. The classification was derived using existing data collected as part of the MACUSTAR study, a low-interventional study on AMD, conducted at 20 clinical sites across Europe. Items were selected using psychometric and Rasch analyses, published criteria around PWM suitability, alongside instrument developer views and concept elicitation work that informed VILL-33 development. An online discrete choice experiment (DCE) with duration of the health state was conducted with the United Kingdom and German public. Responses were modeled to generate utility values for all possible health states.

RESULTS

The classification system has 5 items across the 3 domains of VILL-33: reading and accessing information, mobility and safety, and emotional well-being. The DCE samples (United Kingdom: n = 1004, Germany: n = 1008) are broadly representative and demonstrate good understanding of the tasks. The final DCE analyses produce logically consistent and significant coefficients.

CONCLUSIONS

This study enables responses to VILL-33 to be directly used to inform economic evaluation in AMD. The elicitation of preferences from both United Kingdom and Germany enables greater application of VILL-UI for economic evaluation throughout Europe. VILL-UI fills a gap in AMD in which generic preference-weighted measures typically lack sensitivity.

Treatment effect of semaglutide 2.4 mg on health-related quality of life from STEP 1 SF-6D derived from SF-36 with Australian weights

AIM

This study aimed to determine the comparative treatment effects of semaglutide 2.4 mg and placebo on health utility index scores [6-dimension short-form survey (SF-6D)] with Australian weights in full analysis set (FAS) and in post-hoc subgroups of the STEP 1 trial, defined according to different body mass index (BMI) cut-off points and presence of comorbidities at baseline. The study also explored the correlation between baseline BMI and SF-6D in the STEP 1 trial population.

METHODS

The 36-item SF survey (SF-36) scores from STEP 1 were mapped to SF-6D health states and converted to utility index scores using an Australian valuation algorithm. The change from baseline in SF-6D utility score (95% confidence intervals) was compared between semaglutide 2.4 mg and placebo at week 68 using the mixed model for repeated measurements approach. The relationship between utility scores and BMI at baseline was assessed by multiple linear regression analyses, controlling for demographic and clinical parameters.

RESULTS

The estimated mean treatment difference in SF-6D utility score favoured semaglutide 2.4 mg, and, at week 68, it was 0.057 (0.038-0.076) for the FAS. A greater treatment effect was noted in subgroups with presence of symptomatic comorbidities, i.e. 0.077 (0.027-0.128) to 0.105 (0.030-0.179) at week 68. A 1-unit increase in BMI was associated with a utility loss of 0.0075 (-0.0089 to -0.0062) for the FAS population, while controlling for demographic and clinical parameters.

CONCLUSION

To our knowledge, this is the first study showing statistically significant and clinically meaningful improvements in SF-6D utility scores with weight-loss pharmacotherapy in Australia.

United States Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument

OBJECTIVES

To develop a value set reflecting the United States (US) general population's preferences for health states described by the Functional Assessment of Cancer Therapy (FACT) eight-dimensions preference-based multi-attribute utility instrument (FACT-8D), derived from the FACT-General cancer-specific health-related quality-of-life (HRQL) questionnaire.

METHODS

A US online panel was quota-sampled to achieve a general population sample representative by sex, age (≥ 18 years), race and ethnicity. A discrete choice experiment (DCE) was used to value health states. The valuation task involved choosing between pairs of health states (choice-sets) described by varying levels of the FACT-8D HRQL dimensions and survival (life-years). The DCE included 100 choice-sets; each respondent was randomly allocated 16 choice-sets. Data were analysed using conditional logit regression parameterized to fit the quality-adjusted life-year framework, weighted for sociodemographic variables that were non-representative of the US general population. Preference weights were calculated as the ratio of HRQL-level coefficients to the survival coefficient.

RESULTS

2562 panel members opted in, 2462 (96%) completed at least one choice-set and 2357 (92%) completed 16 choice-sets. Pain and nausea were associated with the largest utility weights, work and sleep had more moderate utility weights, and sadness, worry and support had the smallest utility weights. Within dimensions, more severe HRQL levels were generally associated with larger weights. A preference-weighting algorithm to estimate US utilities from responses to the FACT-General questionnaire was generated. The worst health state's value was -0.33.

CONCLUSIONS

This value set provides US population utilities for health states defined by the FACT-8D for use in evaluating oncology treatments.

Should the Preference-Based Index Set of Values Be Country or Disease Specific? An Analysis Using Data From Women With Symptoms of Overactive Bladder

OBJECTIVES

Overactive bladder (OAB) and urinary incontinence (UI) are common conditions among women. We aimed to verify the difference between the preference-based index extracted from short-form six-dimension version one (SF-6Dv1) in women with OAB using different country-specific value sets, translate and cross-culturally adapt the King's Health Questionnaire Five Dimension (KHQ-5D) into Brazilian Portuguese, and examine the association between preference-based index obtained by the SF-6Dv1 and KHQ-5D.

METHODS

This cross-sectional study included 387 women with OAB, divided into groups with and without UI. The participants answered the sociodemographic questionnaire, KHQ, KHQ-5D, and SF-6Dv1. A two-way mixed analysis of variance, with post hoc to multiple comparisons were applied and a Spearman's test was applied to verify the correlation between the preference-based index of SF-6Dv1 and KHQ-5D.

RESULTS

The main analysis showed a statistically significant interaction between the presence of UI and the value set obtained from the different countries (P = .005, Cohen's d = 0.02). The post hoc analyses showed that there was a statistically significant main effect of the value sets obtained from different countries (P < .001, d = 0.63) and in the presence of UI (P = .012, d = 0.02). The correlations between the preference-based index obtained from different countries using the SF-6Dv1 and KHQ-5D were significant.

CONCLUSIONS

Differences were observed between the preference-based index obtained in different countries and presence of UI, although positive and significant results were observed in the correlation between preference-based index from different countries. The correlation between general and specifics preference-based index was small; the SF-6Dv1 could be used in cost-utility studies for this population.

Whose Time Trade-Off Should Be Used? Anchoring Discrete Choice Experiment Latent Utilities in Health State Valuation

OBJECTIVES

To compare anchored discrete choice experiment (DCE) utility values using own versus others' time trade-off (TTO) responses in the valuation of SF-6Dv2.

METHODS

A representative sample of the general population was recruited in China. Through face-to-face interviews, both DCE and TTO data were collected from a randomly selected half of the respondents (own TTO sample), whereas only TTO data were collected from the other half (others' TTO sample). Conditional logit model was used to estimate DCE latent utilities. Three anchoring methods, including using the observed and the modeled TTO values for the worst state, and mapping DCE values onto TTO, were used to scale the latent utilities to health utilities. Prediction accuracy was assessed using intraclass correlation coefficient, mean absolute difference, and root mean squared difference compared with the mean observed TTO values between the anchoring results using the own versus others' TTO data.

RESULTS

Demographic characteristics were comparable between the own TTO sample (n = 252) and the others' TTO sample (n = 251). The mean (SD) observed TTO value for the worst state was -0.259 (0.591) for the own TTO sample and -0.236 (0.616) for the others' TTO sample. Anchoring DCE using own TTOs consistently showed a better prediction accuracy than using others' TTOs across the 3 anchoring methods in terms of the intraclass correlation coefficient (0.835-0.873 vs 0.771-0.804), mean absolute difference (0.127-0.181 vs 0.146-0.203), and root mean squared difference (0.164-0.237 vs 0.192-0.270).

CONCLUSION

When anchoring DCE-derived latent utilities onto the health utility scale, respondents' own TTO data would be preferred to TTO data obtained from a different sample.

Second Version of the Short Form 6-Dimension Value Set Elicited From Patients With Breast and Colorectal Cancer: A Hybrid Approach

BACKGROUND

Quality-adjusted life-year instruments help comparison among programs by capturing their effects in terms of utility. Generic instruments are applicable to everyone, and for this reason, they are known to lack sensitivity when measuring gains in some domains. Specific instruments tend to fill this gap but, in domains like cancer, existing instruments are either nonpreferences-based or based on the general population's preferences.

PATIENTS AND METHODS

This study describes the development of a new value set for a well-known and highly used generic instrument, the Second Version of the Short Form 6-Dimension, to better consider the preferences of patients with cancer. In this aim, a hybrid approach combining the time trade-off and the discrete choice experiment was used. The population of interest was the Quebec population, Canada, with breast or colorectal cancer. Their preferences were elicited in 2 periods: before (T1) and 8 days after the beginning of a chemotherapy procedure (T2).

RESULTS

A total of 2808 observations for the time trade-off and 2520 observations for the discrete choice experiment were used. The parsimonious model encompassing the 2 periods was the preferred model. The new value set allows a greater utility range than the EQ-5D-5L and the Second Version of the Short Form 6-Dimension reference value sets and helps in better considering patients experiencing severe health situations. A good correlation between these 2 instruments and other specific cancer instruments (ie, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, QLU-C10D, and Functional Assessment of Cancer Therapy-General) was observed. Significative differences in utility values were also noted within periods and types of cancer.

Estimating the willingness-to-pay to avoid the consequences of foodborne illnesses: a discrete choice experiment

Lost productivity is one of the largest costs associated with foodborne illness (FBI); however, the methods used to estimate lost productivity are often criticised for overestimating the actual burden of illness. A discrete choice experiment (DCE) was undertaken to elicit preferences to avoid six possible FBIs and estimate whether ability to work, availability of paid sick leave and health-related quality of life affect willingness-to-pay (WTP) to avoid FBI. Respondents (N = 1918) each completed 20 DCE tasks covering two different FBIs [gastrointestinal illness, flu-like illness, irritable bowel syndrome (IBS), Guillain-Barre syndrome (GBS), reactive arthritis (ReA), or haemolytic uraemic syndrome (HUS)]. Attributes included: ability to work, availability of sick leave, treatment costs and illness duration. Choices were modelled using mixed logit regression and WTP was estimated. The WTP to avoid a severe illness was higher than a mild illness. For chronic conditions, the marginal WTP to avoid a chronic illness for one year, ranged from $531 for mild ReA ($1412 for severe ReA) to $1025 for mild HUS ($2195 for severe HUS). There was a substantial increase in the marginal WTP to avoid all the chronic conditions when the ability to work was reduced and paid sick leave was not available, ranging from $6289 for mild IBS to $11,352 for severe ReA. Including factors that reflect productivity and compensation to workers influenced the WTP to avoid a range of FBIs for both acute and chronic conditions. These results have implications for estimating the burden and cost of FBI.

Derivation of a UK preference-based value set for the Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS) to allow estimation of Mental Well-being Adjusted Life Years (MWALYs)

BACKGROUND

The Mental Well-being Adjusted Life Year (MWALY) is an alternative outcome measure to the quality-adjusted life year (QALY) in economic evaluations of interventions aimed at improving mental well-being. However, there is a lack of preference-based mental well-being instruments for capturing population mental well-being preferences.

OBJECTIVES

To derive a UK preference-based value set for the Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS).

METHODS

225 participants that were interviewed between December 2020 and August 2021 completed 10 composite time trade-off (C-TTO) and 10 discrete choice experiment (DCE) interviewer-administered exercises. Heteroskedastic Tobit and conditional logit models were used to model C-TTO and DCE responses respectively. The DCE utility values were rescaled to a C-TTO comparable scale through anchoring and mapping. An inverse variance weighting hybrid model (IVWHM) was used to derive weighted-average coefficients from the modelled C-TTO and DCE coefficients. Model performance was assessed using statistical diagnostics.

RESULTS

The valuation responses confirmed the feasibility and face validity of the C-TTO and DCE techniques. Apart from the main effects models, statistically significant associations were estimated between the predicted C-TTO value and participants' SWEMWBS scores, gender, ethnicities, education levels, and the interaction terms between age and useful feeling. The IVWHM was the most optimal model with the fewest logically inconsistent coefficients and the lowest pooled standard errors. The utility values generated by the rescaled DCE models and the IVWHM were generally higher than those of the C-TTO model. The predictive ability of the two DCE rescaling methods was similar according to the mean absolute deviation and root mean square deviation statistics.

CONCLUSIONS

This study has produced the first preference-based value set for a measure of mental well-being. The IVWHM provided a desirable blend of both C-TTO and DCE models. The value set derived by this hybrid approach can be used for cost-utility analyses of mental well-being interventions.

Development of attributes and levels of mental health insurance services using a discrete choice experiment

BACKGROUND

Despite the fact that mental illness is among the ten top diseases with the highest burden, the health services required by these patients do not have adequate insurance coverage. The purpose of this study is to develop the attributes and levels of mental health insurance services using a discrete choice experiment (DCE).

MATERIALS AND METHOD

This study involved a qualitative phase of the DCE that was conducted in Iran in 2020-2021 and included several stages. First, during a literature review, the attributes and levels were determined. Then, the attributes of health insurance were identified and weighed through virtual and in-person interviews with 16 mental health insurance professionals and policymakers in this field who were selected by purposive sampling. Finally, after a few sessions, through review studies, interviews, and a group of the expert panel, attributes and levels were finalized.

RESULTS

This study showed that coverage of inpatient services, outpatient services, place of receiving services, use of online internet services, limitation of services, and monthly premiums were the most important attributes of mental health insurance services.

CONCLUSION

To promote mental health insurance, policymakers and health insurance organizations should pay attention to premiums to be commensurate with the payment of people, packages of mental health services, and the ability of people to pay in appropriation with inflation. Identifying these attributes can determine people's willingness to pay and preferences for mental health insurance and lead to better planning for more comprehensive coverage for patients and increase the desirability of individuals in receiving services.

The Use of a Discrete Choice Experiment Including Both Duration and Dead for the Development of an EQ-5D-5L Value Set for Australia

BACKGROUND/AIMS

Discrete choice experiments (DCEs) with either duration included an attribute or with dead included as an option can be used as a stand-alone approach to value health states. This paper reports on a DCE with both of these features to develop an EQ-5D-5L value set for Australia.

METHODS

A DCE was undertaken using a large Australian panel of internet respondents, from which a sample of more than 4000 Australian adults was chosen, stratified to be population representative on age and gender. The DCE contained 500 choice triplets, with two EQ-5D-5L health states with duration, and dead as the third option. Each respondent answered 12 choice sets from the 500, stating both the best and worst options from the three available. The design was constructed to estimate a utility algorithm with main effects plus some key interaction terms. A variety of approaches to parameterising interactions, and to anchoring the value set on the required 0-1 scale, were tested. A preferred Australian adult utility algorithm for use in cost-utility analysis was then generated.

RESULTS

In total, 4477 people completed at least one choice set and were included in the analysis. The results reflected the monotonic structure of the EQ-5D-5L, in that moving from no problems to extreme problems led to worsening utility in each dimension. Inclusion of interaction terms demonstrates that the disutility of the first dimension moving to a poor level (defined as either level 5, or level 4 or 5) had a large impact, but subsequent dimensions moving to a poor level had a relatively smaller disutility.

DISCUSSION

This work develops a value set for the EQ-5D-5L in Australia, and also provides a range of methodological insights which can inform future work using a stand-alone DCE to value health in other countries.

Efficient Designs for Valuation Studies That Use Time Tradeoff (TTO) Tasks to Map Latent Utilities from Discrete Choice Experiments to the Interval Scale: Selection of Health States for TTO Tasks

BACKGROUND

In eliciting utilities to value multiattribute utility instruments, discrete choice experiments (DCEs) administered online are less costly than interviewer-facilitated time tradeoff (TTO) tasks. DCEs capture utilities on a latent scale and are often coupled with a small number of TTO tasks to anchor utilities to the interval scale. Given the costly nature of TTO data, design strategies that maximize value set precision per TTO response are critical.

METHODS

Under simplifying assumptions, we expressed the mean square prediction error (MSE) of the final value set as a function of the number J of TTO-valued health states and the variance VJ of the states' latent utilities. We hypothesized that even when these assumptions do not hold, the MSE 1) decreases as VJ increases while holding J fixed and 2) decreases as J increases while holding VJ fixed. We used simulation to examine whether there was empirical support for our hypotheses a) assuming an underlying linear relationship between TTO and DCE utilities and b) using published results from the Dutch, US, and Indonesian EQ-5D-5L valuation studies.

RESULTS

Simulation set (a) supported the hypotheses, as did simulations parameterized using valuation data from Indonesia, which showed a linear relationship between TTO and DCE utilities. The US and Dutch valuation data showed nonlinear relationships between TTO and DCE utilities and did not support the hypotheses. Specifically, for fixed J, smaller values of VJ reduced rather than increased the MSE.

CONCLUSIONS

Given that, in practice, the underlying relationship between TTO and DCE utilities may be nonlinear, health states for TTO valuation should be placed evenly across the latent utility scale to avoid systematic bias in some regions of the scale.

HIGHLIGHTS

Valuation studies may feature a large number of respondents completing discrete choice tasks online, with a smaller number of respondents completing time tradeoff (TTO) tasks to anchor the discrete choice utilities to an interval scale.We show that having each TTO respondent complete multiple tasks rather than a single task improves value set precision.Keeping the total number of TTO respondents and the number of tasks per respondent fixed, having 20 health states directly valued through TTO leads to better predictive precision than valuing 10 health states directly.If DCE latent utilities and TTO utilities follow a perfect linear relationship, choosing the TTO states to be valued by weighting on the 2 ends of the latent utility scale leads to better predictive precision than choosing states evenly across the latent utility scale.Conversely, if DCE latent utilities and TTO utilities do not follow a linear relationship, choosing the states to be valued using TTO evenly across the latent utility scale leads to better predictive precision than weighted selection does.In the context of valuation of the EQ-5D-Y-3L, we recommend valuing 20 or more health states using TTO and placing them evenly across the latent utility scale.

Preferences of older adults for healthcare models designed to improve care coordination: evidence from Western Switzerland

Implementing innovations in care delivery in Switzerland is challenging due to the fragmented nature of the system and the specificities of the political process (i.e., direct democracy, decentralized decision-making). In this context, it is particularly important to account for population preferences when designing policies. We designed a discrete choice experiment to study population preferences for coordination-improving care models. Specifically, we assessed the relative importance of model characteristics (i.e., insurance premium, presence of care coordinator, access to specialists, use of EMR, cost-sharing for chronic patients, incentives for informal care), and predicted uptake under different policy scenarios. We accounted for heterogeneity in preferences for the status quo option using an error component logit model. Respondents attached the highest importance to the price attribute (i.e. insurance premium) (0.31, CI: 0.27- 0.36) and to the presence of a care coordinator (0.27, CI: 0.23 - 0.31). Policy scenarios showed for instance that gatekeeping would be preferred to free access to specialists if the model includes a GP or an interprofessional team as a care coordinator. Although attachment to the status quo is high in the studied population, there are potential ways to improve acceptance of alternative care models by implementation of positively valued innovations.

Trajectories of wellbeing in people who live with gamblers experiencing a gambling problem: An 18-year longitudinal analysis of the Household, Income and Labour Dynamics in Australia (HILDA) survey

In cross-sectional gambling studies, friends, family, and others close to those experiencing gambling problems (concerned significant others 'CSOs') tend to report detriments to their quality of life. To date, however, there have been no large, population-based longitudinal studies examining the health and wellbeing of CSOs. We analyse longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA) survey to examine the 18-year trajectories of general, social, health and financial wellbeing of household CSOs (n = 477) and compare these to those without a gambling problem in the household (n = 13,661). CSOs reported significantly worse long-term wellbeing than non-CSOs in their satisfaction with life, number of life stressors, and social, health and financial wellbeing. However, both social and financial wellbeing showed a temporal effect, declining significantly for CSOs at times closer to the exposure to the gambling problem. This finding suggests a causal link between living in a household with a person with a gambling problem and decreased CSO social and financial wellbeing. Policy responses, such as additional social and financial support, could be considered to assist CSOs impacted by another person's gambling problem.

Preferences of patients with chronic low back pain about nonsurgical treatments: Results of a discrete choice experiment

INTRODUCTION

This study aimed to assess patients' preferences of nonsurgical treatments for chronic low back pain (CLBP).

METHOD

We conducted a discrete choice experiment (DCE) in Quebec, Canada, in 2018. Seven attributes were included: treatment modality, pain reduction, the onset of treatment efficacy, duration effectiveness, difficulties with daily activities, sleep problems, and knowledge of the patient's body and pain location. Treatment modalities were corticosteroid injections, supervised body-mind physical activities, supervised sports physical activities, physical manipulations, self-management courses, and psychotherapy. Utility levels were estimated using a logit model, a latent class model and a Bayesian hierarchical model.

RESULTS

Analyses were conducted on 424 $424$ individuals. According to the Bayesian hierarchical model, the conditional relative importance weights of attributes were as follows: (1) treatment modality (34.79%), (2) pain reduction (18.73%), (3) difficulties with daily activities (11.71%), (4) duration effectiveness (10.06%), (5) sleep problems (10.05%), (6) onset of treatment efficacy (8.60%) and (7) knowledge of the patient's body and pain location (6.06%). According to the latent class model that found six classes of respondents with different behaviours (using Akaike and Bayesian criteria), the treatment modality was the most important attribute for all classes, except for class 4 for which pain reduction was the most important. In addition, classes 2 and 5 refused corticosteroid injections, while psychotherapy was preferred only in class 3.

CONCLUSION

Given the preference heterogeneity found in the analysis, it is important that patient preferences are discussed and considered by the physicians. This will help to improve the patient care pathway in a context of a patient-centred model for a disease with growing prevalence.

PATIENT OR PUBLIC CONTRIBUTION

A small group of patients was involved in the conception, design and interpretation of data. Participants in the DCE were all CLBP patients.

Deciding Between SF-6Dv2 Health States: A Think-Aloud Study of Decision-Making Strategies Used in Discrete Choice Experiments

OBJECTIVE

This study aimed to gain insight into decision-making strategies individuals used when evaluating pairs of SF-6Dv2 health states in discrete choice experiments (DCEs).

METHODS

This qualitative, cross-sectional, noninterventional study asked participants to use a think-aloud approach to compare SF-6Dv2 health states in DCEs. Thematic analysis focused on comprehension and cognitive strategies used to compare health states and make decisions.

RESULTS

Participants (N = 40) used 3 main strategies when completing DCEs: (1) trading, (2) reinterpretation, and (3) relying on previous experience. Trading was the most common strategy, used by everyone at least once, and involved prioritizing key attributes, such as preferring a health state with significant depression but no bodily pain. Reinterpretation was used by 17 participants and involved reconstructing health states by changing underlying assumptions (eg, rationalizing selecting a health state with significant pain because they could take pain medications). Finally, some (n = 13) relied on previous experience when making decisions on some choice tasks. Participants with experience dealing with pain, for instance, prioritized health states with the least impact in this dimension.

CONCLUSIONS

Qualitatively evaluating the decision-making strategies used in DCEs allows researchers to evaluate whether the tasks and attributes are interpreted accurately. The findings from this study add to the understanding of the generation of SF-6Dv2 health utility weights and the validity of these weights (e.g., reinterpreting health states could undermine the validity of DCEs and utility weights), and the overall usefulness of the SF-6Dv2. The methodology described in this study can and should be carried forth in valuing other health utility measures, not just the SF-6Dv2.

The FACT-8D, a new cancer-specific utility algorithm based on the Functional Assessment of Cancer Therapies-General (FACT-G): a Canadian valuation study

Introduction

Utility instruments are used to assess patients’ health-related quality of life for cost-utility analysis (CUA). However, for cancer patients, the dimensions of generic utility instruments may not capture all the information relevant to the impact of cancer. Cancer-specific utilities provide a useful alternative. Under the auspices of the Multi-Attribute Utility in Cancer Consortium, a cancer-specific utility algorithm was derived from the FACT-G. The new FACT-8D contains eight dimensions: pain, fatigue, nausea, sleep, work, support from family/friends, sadness, and worry health will get worse. The aim of the study was to obtain a Canadian value set for the FACT-8D.

Methods

A discrete choice experiment was administered to a Canadian general population online panel, quota sampled by age, sex, and province/territory of residence. Respondents provided responses to 16 choice sets. Each choice set consisted of two health states described by the FACT-8D dimensions plus an attribute representing survival duration. Sample weights were applied and the responses were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life year framework. The results were converted into utility weights by evaluating the marginal rate of substitution between each level of each FACT-8D dimension with respect to duration.

Results

2228 individuals were recruited. The analysis dataset included n = 1582 individuals, who completed at least one choice set; of which, n = 1501 completed all choice sets. After constraining to ensure monotonicity in the utility function, the largest decrements were for the highest levels of pain (− 0.38), nausea (− 0.30), and problems doing work (− 0.23). The decrements of the remaining dimensions ranged from − 0.08 to − 0.18 for their highest levels. The utility of the worst possible health state was defined as − 0.65, considerably worse than dead.

Conclusions

The largest impacts on utility included three generic dimensions (i.e., pain, support, and work) and nausea, a symptom caused by cancer (e.g., brain tumours, gastrointestinal tumours, malignant bowel obstruction) and by common treatments (e.g., chemotherapy, radiotherapy, opioid analgesics). This may make the FACT-8D more informative for CUA evaluating in many cancer contexts, an assertion that must now be tested empirically in head-to-head comparisons with generic utility measures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12955-022-02002-z.

Discrete choice experiment with duration versus time trade-off: a comparison of test-retest reliability of health utility elicitation approaches in SF-6Dv2 valuation

OBJECTIVES

To evaluate and compare the test-retest reliability of discrete choice experiments with duration (DCE_TTO) and time trade-off (TTO) in the Chinese SF-6Dv2 valuation study.

METHODS

During face-to-face interviews, a representative sample of the Chinese general population completed 8 TTO tasks and 10 DCE_TTO tasks. Retest interviews were conducted after two weeks. For both DCE_TTO and TTO, the consistency of raw responses between the two tests was firstly evaluated at the individual level. Regressions were conducted to investigate the association between the test-retest reliability and the respondents' characteristics and the severity of health states. Consistency was then analyzed at the aggregate level by comparing the rank order of the coefficients of dimensions.

RESULTS

In total, 162 respondents (51.9% male; range 18-80 years) completed the two tests. The intraclass correlations coefficient 0.958 for TTO, with identical values accounting for 59.3% of observations. 76.4% of choices were identical for DCE_TTO, with a Kappa statistic of 0.528. Respondents' characteristics had no significant impact while the severity of health states valued in TTO and DCE_TTO tasks had a significant impact on the test-retest reliability. Both approaches produced relatively stable rank order of dimensions in constrained model estimations between test and retest data.

CONCLUSIONS

Individual responses of both approaches are relatively stable over time. The rank orders of dimensions in model estimations between test and retest for TTO and DCE_TTO are also consistent. The differences of utility estimation between the two tests for DCE_TTO need to be further investigated based on a larger sample size.

Cost-utility analysis of breast reduction surgery for women with symptomatic breast hypertrophy

OBJECTIVE

To assess the cost-effectiveness of breast reduction surgery for women with symptomatic breast hypertrophy in Australia.

DESIGN

Cost-utility analysis of data from a prospective cohort study.

SETTING, PARTICIPANTS

Adult women with symptomatic breast hypertrophy assessed for bilateral breast reduction at the Flinders Medical Centre, a public tertiary hospital in Adelaide, April 2007 - February 2018. The control group included women with breast hypertrophy who had not undergone surgery.

MAIN OUTCOME MEASURES

Health care costs (for the surgical admission and other related hospital costs within 12 months of surgery) and SF-6D utility scores (measure of health-related quality of life) were used to calculate incremental costs per quality-adjusted life-year (QALY) gained over 12 months, extrapolated to a 10-year time horizon.

RESULTS

Of 251 women who underwent breast reduction, 209 completed the baseline and at least one post-operation assessment (83%; intervention group); 124 of 350 invited women waiting for breast reduction surgery completed the baseline and 12-month assessments (35%; control group). In the intervention group, the mean SF-6D utility score increased from 0.313 (SD, 0.263) at baseline to 0.626 (SD, 0.277) at 12 months; in the control group, it declined from 0.296 (SD, 0.267) to 0.270 (SD, 0.257). The mean QALY gain was consequently greater for the intervention group (adjusted difference, 1.519; 95% CI, 1.362-1.675). The mean hospital cost per patient was $11 857 (SD, $4322), and the incremental cost-effectiveness ratio (ICER) for the intervention was $7808 per QALY gained. The probability of breast reduction surgery being cost-effective was 100% at a willingness-to-pay threshold of $50 000 per QALY and 88% at $28 033 per QALY.

CONCLUSIONS

Breast reduction surgery for women with symptomatic breast hypertrophy is cost-effective and should be available to women through the Australian public healthcare system.

Not all respondents use a multiplicative utility function in choice experiments for health state valuations, which should be reflected in the elicitation format (or statistical analysis)

Discrete choice experiments (DCEs) that include health states and duration are becoming a common method for estimating quality-adjusted life year (QALY) tariffs. These DCEs need to be analyzed under the assumption that respondents treat health and duration multiplicatively. However, in the most commonly used DCE duration format there is no guarantee that respondents actually do so; in fact, respondents can easily simplify the choice tasks by considering health and duration separately. This would result in valid DCE responses but preclude subsequent QALY tariff calculations. Using a Bayesian latent class model and data from two existing valuation studies, our analyses confirm that in both datasets the majority of respondents do not appear to have used a multiplicative utility function. Moreover, a statistical correction for respondents who used an incorrect function changes the range of the QALY weights. Hence our results imply that one can neither assume that respondents use the theoretically required multiplicative utility function nor assume that the type of utility function that respondents use does not affect the estimated QALY weights. As a solution, we advise researchers to use an alternative, more constrained DCE elicitation format that avoids these behavioral problems.

Protocol for the Metformin Aneurysm Trial (MAT): a placebo-controlled randomised trial testing whether metformin reduces the risk of serious complications of abdominal aortic aneurysm

Background

Multiple observational studies have associated metformin prescription with reduced progression of abdominal aortic aneurysm (AAA). The Metformin Aneurysm Trial (MAT) will test whether metformin reduces the risk of AAA rupture-related mortality or requirement for AAA surgery (AAA events) in people with asymptomatic aneurysms.

Methods

MAT is an international, multi-centre, prospective, parallel-group, randomised, placebo-controlled trial. Participants must have an asymptomatic AAA measuring at least 35 mm in maximum diameter, no diabetes, no contraindication to metformin and no current plans for surgical repair. The double-blind period is preceded by a 6-week, single-blind, active run-in phase in which all potential participants receive metformin. Only patients tolerating metformin by taking at least 80% of allocated medication will enter the trial and be randomised to 1500 mg of metformin XR or an identical placebo. The primary outcome is the proportion of AAA events defined as rupture-related mortality or need for surgical repair. Secondary outcomes include AAA growth, major adverse cardiovascular events and health-related quality of life. In order to test if metformin reduced the risk of AAA events by at least 25%, 616 primary outcome events will be required (power 90%, alpha 0.05).

Discussion

Currently, there is no drug therapy for AAA. Past trials have found no convincing evidence of the benefit of multiple blood pressure lowering, antibiotics, a mast cell inhibitor, an anti-platelet drug and a lipid-lowering medication on AAA growth. MAT is one of a number of trials now ongoing testing metformin for AAA. MAT, unlike these other trials, is designed to test the effect of metformin on AAA events. The international collaboration needed for MAT will be challenging to achieve given the current COVID-19 pandemic. If this challenge can be overcome, MAT will represent a trial unique within the AAA field in its large size and design.

Trial registration

Australian Clinical Trials ACTRN12618001707257. Registered on 16 October 2018

Cost-effectiveness of a complex intervention in general practice to increase uptake of long-acting reversible contraceptives in Australia

Objective The aim of this study was to evaluate the cost-effectiveness of the Australian Contraceptive ChOice pRoject (ACCORd) intervention. Methods An economic evaluation compared the costs and outcomes of the ACCORd intervention with usual care (UC). Data from the ACCORd trial were used to estimate costs and efficacy in terms of contraceptive uptake and quality of life. Rates of contraceptive failure and pregnancy were sourced from the literature. Using a Markov model, within-trial results were extrapolated over 10 years and subjected to univariate sensitivity analyses. Model outputs were expressed as the cost per quality-adjusted life years (QALY) gained and cost per unintended pregnancy resulting in birth (UPB) avoided. Results Over 10 years, compared with UC, initiating contraception through the ACCORd intervention resulted in 0.02 fewer UPB and higher total costs (A$2505 vs A$1179) per woman. The incremental cost-effectiveness of the ACCORd intervention versus UC was A$1172 per QALY gained and A$7385 per UPB averted. If the start-up cost of the ACCORd intervention was removed, the incremental cost-effectiveness ratio was A$81 per QALY gained and A$511 per UPB averted. The results were most sensitive to the probability of contraceptive failure, the probability of pregnancy-related healthcare service utilisation or the inclusion of the costs of implementing the ACCORd intervention. Conclusions From a health system perspective, if implemented appropriately in terms of uptake and reach, and assuming an implicit willingness to pay threshold of A$50 000 the ACCORd intervention is cost-effective. What is known about the topic? The uptake of long-active reversible contraceptives (LARC) in Australia is low. The ACCORd trial assessed the efficacy of providing structured training to general practitioners (GPs) on LARC counselling, together with access to rapid referral to insertion clinics. What does this paper add? This study is the first to assess the cost-effectiveness of a complex intervention in the general practice setting aimed at increasing the uptake of LARC in Australia. What are the implications for practitioners? The results show that implementing a complex intervention in general practice involving GP education and the availability of rapid referral to LARC insertion clinics is a cost-effective approach to increase LARC use and its attending efficacy. If the majority of Australian GPs were able to deliver effectiveness-based contraceptive counselling and either insert LARC or use a rapid referral process to a LARC insertion clinic, the additional cost associated with the purchase of LARC products and their insertion would be offset by reductions to health system costs as a result of fewer UPB and abortions. Moreover, the benefits to women's physical and psychological health of avoiding such events is substantial.

Properties of SF-6D when longitudinal data from 16,398 spine surgery procedures is applied to 9 national SF-6D value sets

Background and purpose - There are several national value sets for SF-6D. For studies conducted in countries without a country-specific value set the authors may use a value set from a neighboring or culturally similar county. We evaluated the consequences of using different national value sets in SF-6D index-based outcome analyses.Patients and methods - Patients surgically treated for lumbar spinal stenosis or lumbar disk herniation between 2007 and 2017 were recruited from the national Swedish spine register. 16,398 procedures were eligible for analysis. The SF-6D health states were coded to SF-6D preference indices using value sets for 9 countries. The SF-6D index distributions were then estimated with kernel density estimation. The change in SF-6D index before and after treatment was evaluated with the standardized response mean (SRM).Results - There was a marked variability in mean and shape for the resulting SF-6D index distributions. There were considerable differences in SF-6D index distribution shape before and after treatment using the same value set. The effect sizes of 2-year change (SRM) were in most cases similar when the 9 value sets were applied on pre- and post-treatment data.Interpretation - We found a marked variability in SF-6D index distributions when a single large data set was applied to 9 national SF-6D value sets. Consequently, we recommend that SF-6D index data from studies conducted in countries without country-specific SF-6D value sets is interpreted with caution.

Valuing SF-6Dv2 in Australia Using an International Protocol

BACKGROUND

The SF-6Dv2 is an updated version of the SF-6D, with improved consistency and dimension descriptors, and value sets are required. The aim of this study was to estimate an SF-6Dv2 value set for Australia using an international protocol, while secondary aims were to compare Australian and UK values and to understand heterogeneity.

METHODS

The study design was based on the SF-6Dv2 valuation protocol, which involved the administration of two different discrete choice experiment (DCE) tasks. The first task presented pairs of SF-6Dv2 health states with duration (Design 1), and the second task presented triplets that appended 'immediate death' to the health state pairs (Design 2). Respondents completed 12 choice sets online (10 from Design 1; 2 from Design 2). Value sets were estimated for Design 1 separately and combining Designs 1 and 2 using a variety of logit model specifications. Value set characteristics were compared descriptively with the UK model.

RESULTS

The sample included 3001 Australians. A range of ordered and consistent models were estimated. The models only including Design 1 data resulted in a relatively wider utility range. The value range was reduced by an interaction added when the health state included a dimension with a severe level. The model matched with the UK value set resulted in a larger utility range and consistent ordering of the most important dimensions.

CONCLUSION

The model including the Design 1 data and moderating interaction was chosen for the Australian value set. This allows the SF-6Dv2 to be used in health technology assessment decision making in Australia.

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

OBJECTIVES

This study generates a preference-based measure for capturing the quality of life of people with Duchenne muscular dystrophy (DMD) from a new measure of quality of life, DMD-QoL.

METHODS

A health state classification system was derived from the DMD-QoL based on psychometric performance of items, factor analysis, and item response theory analysis. Preferences for health states described by the classification system were elicited using an online discrete choice experiment survey with life years as an additional attribute, from members of the UK general population (n = 1043). Discrete choice experiment data was modeled using a conditional fixed-effects logit model and utility estimates were directly anchored on the 1 to 0 full health-dead scale.

RESULTS

The health state classification system has 8 dimensions: mobility, difficulty using hands, difficulty breathing, pain, tiredness, worry, participation, and feeling good about yourself. The standard model had mostly statistically significant coefficients and reflected the instrument's monotonic structure. However, 2 dimensions had inconsistent coefficients (where utility increased as health worsened) and a consistent model was estimated that merged adjacent inconsistent severity levels. The best state defined by the classification system has a value of 1 and the worst state has a value of -0.559.

CONCLUSION

The modeled results enable DMD-QoL-8D utility values to be generated using DMD-QoL or DMD-QoL-8D data to generate QALYs for people with DMD. QALYs can then be used to inform economic models of the cost-effectiveness of interventions in DMD. Future research comparing the psychometric performance of DMD-QoL-8D to existing generic preference-based measures, including EQ-5D-5L, is recommended.

Estimation of an EORTC QLU-C10 Value Set for Spain Using a Discrete Choice Experiment

BACKGROUND

The EORTC QLU-C10D is a preference-based measure derived from the EORTC QLQ-C30. For use in economic evaluations, country-specific value sets are needed. This study aimed to generate an EORTC QLU-C10 value set for Spain.

METHODS

A sample of the Spanish general population completed an online discrete choice experiment. An attribute-balanced incomplete block design was used to select 960 choice tasks, with a total of 1920 health states. Each participant was randomly assigned 16 choice sets without replacement. Data were modelled using generalized estimating equations and mixed logistic regressions.

RESULTS

A total of 1625 panel members were invited to participate, 1010 of whom were included in the study. Dimension decrements were generally monotonic with larger disutilities at increased severity levels. Dimensions associated with larger decrements were physical functioning and pain, while the dimension with the smallest decrement was sleep disturbances. The PITS state (i.e. worst attainable health) for the Spanish population is - 0.043.

CONCLUSIONS

This study generated the first Spanish value set for the QLU-C10D. This can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30.

Modeling SF-6D Health Utilities: Is Bayesian Approach Appropriate?

Background: Valuation studies of preference-based health measures like SF6D have been conducted in many countries. However, the cost of conducting such studies in countries with small populations or low- and middle-income countries (LMICs) can be prohibitive. There is potential to use results from readily available countries’ valuations to produce better valuation estimates. Methods: Data from Lebanon and UK SF-6D value sets were analyzed, where values for 49 and 249 health states were extracted from samples of Lebanon and UK populations, respectively, using standard gamble techniques. A nonparametric Bayesian model was used to estimate a Lebanon value set using the UK data as informative priors. The resulting estimates were then compared to a Lebanon value set obtained using Lebanon data by itself via various prediction criterions. Results: The findings permit the UK evidence to contribute potential prior information to the Lebanon analysis by producing more precise valuation estimates than analyzing Lebanon data only under all criterions used. Conclusions: The positive findings suggest that existing valuation studies can be merged with a small valuation set in another country to produce value sets, thereby making own country value sets more attainable for LMICs.

Implementing work-related Mental health guidelines in general PRacticE (IMPRovE): a protocol for a hybrid III parallel cluster randomised controlled trial

BACKGROUND

The Clinical Guideline for the Diagnosis and Management of Work-related Mental Health Conditions in General Practice (the Guideline) was published in 2019. The objective of this trial is to implement the Guideline in general practice.

TRIAL DESIGN

Implementing work-related Mental health conditions in general PRacticE is a hybrid III, parallel cluster randomised controlled trial undertaken in Australia. Its primary aim is to assess the effectiveness of a complex intervention on the implementation of the Guideline in general practice. Secondary aims are to assess patient health and work outcomes, to evaluate the cost-effectiveness of the trial, and to develop a plan for sustainability.

METHODS

A total of 86 GP clusters will be randomly allocated either to the intervention arm, where they will receive a complex intervention comprising academic detailing, enrolment in a community of practice and resources, or to the control arm, where they will not receive the intervention. GP guideline concordance will be assessed at baseline and 9 months using virtual simulated patient scenarios. Patients who meet the eligibility criteria (>18years, employed, and receiving care from a participating GP for a suspected or confirmed work-related mental health condition) will be invited to complete surveys about their health and work participation and provide access to their health service use data. Data on health service use and work participation compensation claim data will be combined with measures of guideline concordance and patient outcomes to inform an economic evaluation. A realist evaluation will be conducted to inform the development of a plan for sustainability.

RESULTS

We anticipate that GPs who receive the intervention will have higher guideline concordance than GPs in the control group. We also anticipate that higher concordance will translate to better health and return-to-work outcomes for patients, as well as cost-savings to society.

CONCLUSIONS

The trial builds on a body of work defining the role of GPs in compensable injury, exploring their concerns, and developing evidence-based guidelines to address them. Implementation of these guidelines has the potential to deliver improvements in GP care, patient health, and return-to-work outcomes.

TRIAL REGISTRATION

ACTRN12620001163998 , November 2020.

Population norms for quality adjusted life years for the United States of America, China, the United Kingdom and Australia

Health economics uses quality adjusted life years (QALYs) to help healthcare decision makers. However, unlike life expectancy for which age- and sex-dependent national life tables are available, no general population norms exist to use as a benchmark against which to compare observed or modeled projections of QALYs in sub-populations or patients. We developed a 2-state Markov model to generate QALY population norms for the USA, UK, China and Australia. Annual age- and sex-specific probabilities of all-cause mortality were taken from life tables combined with general population country-specific age- and sex-specific health state utilities for the EQ-5D-3L (all countries); and SF-6D (Australia) multi-attribute utility instruments (MAUI). To validate our QALY benchmark model we found that the model closely predicted population life expectancies. Using EQ-5D-3L, undiscounted QALYs for males/females aged 18 years ranged 54.62/58.90 (USA), 55.55/60.21 (China), 57.11/60.16 (Australia), and 58.01/61.43 (UK) years. SF-6D benchmark QALYs for Australia were consistently lower than those generated from the EQ-5D-3L. The gap in undiscounted QALYs between the UK (highest) and the USA (lowest) was 2.53 QALYs in women and 3.39 QALYs in men aged 18 years. Our model's QALY population norms can be used for internal validation of future health economic models for the country-specific value sets for the instruments that we adopted, and when quantifying burden of disease in terms of QALYs lost due to illness compared to the general population. We have created a publicly available repository to continuously include QALY benchmarks that use country-specific value sets for other MAUIs and life expectancies.

The Functional Assessment of Cancer Therapy Eight Dimension (FACT-8D), a Multi-Attribute Utility Instrument Derived From the Cancer-Specific FACT-General (FACT-G) Quality of Life Questionnaire: Development and Australian Value Set

OBJECTIVES

To develop a cancer-specific multi-attribute utility instrument derived from the Functional Assessment of Cancer Therapy - General (FACT-G) health-related quality of life (HRQL) questionnaire.

METHODS

We derived a descriptive system based on a subset of the 27-item FACT-G. Item selection was informed by psychometric analyses of existing FACT-G data (n = 6912) and by patient input (n = 82). We then conducted an online valuation survey, with participants recruited via an Australian general population online panel. A discrete choice experiment (DCE) was used, with attributes being the HRQL dimensions of the descriptive system and survival duration, and 16 choice-pairs per participant. Utility decrements were estimated with conditional logit and mixed logit modeling.

RESULTS

Eight HRQL dimensions were included in the descriptive system: pain, fatigue, nausea, sleep, work, social support, sadness, and future health worry; each with 5 levels. Of 1737 panel members who accessed the valuation survey, 1644 (95%) completed 1 or more DCE choice-pairs and were included in analyses. Utility decrements were generally monotonic; within each dimension, poorer HRQL levels generally had larger utility decrements. The largest utility decrements were for the highest levels of pain (-0.40) and nausea (-0.28). The worst health state had a utility of -0.54, considerably worse than dead.

CONCLUSIONS

A descriptive system and preference-based scoring approach were developed for the FACT-8D, a new cancer-specific multi-attribute utility instrument derived from the FACT-G. The Australian value set is the first of a series of country-specific value sets planned that can facilitate cost-utility analyses based on items from the FACT-G and related FACIT questionnaires containing FACT-G items.

Eliciting SF-6Dv2 health state utilities using an anchored best-worst scaling technique

There is an increasing interest in using ordinal data collection methods, such as the best-worst scaling (BWS), to develop preference-based tariffs (value sets) for health-related quality of life instruments, yet the evidence on their performance is limited. This paper proposed to use an anchored BWS technique (in which the state of "death" served as an anchoring state) to directly develop a utility weight that lies on a scale anchored at 0 = death and 1 = full health for the Simplified Chinese version of the Short Form 6 Dimension version 2 (SF-6Dv2). An online panel from the general population of Mainland China completed an online survey between 20^th July and 19^th August, 2019 and 463 respondents were included in the main analysis. The Conditional Logit (CL) model, which assumes a homogeneous preference, as well as a Hierarchical Bayes (HB) model, which accounts for preference heterogeneity, were used to analyze the BWS data. The model performances were evaluated based on monotonicity and model-fit statistics. The majority of respondents indicated that the BWS questions were easy to understand and complete. Initial analyses suggested that the best and worst choices should not be pooled together. Based on model fit statistics of separated estimations and previous literature on health state valuation studies using BWS, the best choices were used for developing the final algorithm. The HB estimates were found to have better model performance than the CL estimates. This study provides an essential insight into using an anchored BWS approach in health state valuation. Furthermore, it demonstrates the advantage of using HB compared to the traditional CL model in producing preference values.

Valuation of SF-6Dv2 Health States in China Using Time Trade-off and Discrete-Choice Experiment with a Duration Dimension

OBJECTIVES

Our objective was to generate a value set for the SF-6Dv2 using time trade-off (TTO) and a discrete-choice experiment with a duration dimension (DCE_TTO) in China.

METHODS

A large representative sample of the Chinese general population was recruited from eight provinces/municipalities in China, stratified by age, sex, education level, and proportion of urban/rural residence. Respondents completed eight TTO tasks and ten DCE_TTO tasks during face-to-face interviews. Ordinary least squares (OLS), random-effects, fixed-effects, and Tobit models were used for TTO data, and conditional logit and mixed logit models were used for DCE_TTO. The monotonicity of model coefficients and the consistency of the predicted values according to intraclass correlation coefficient (ICC), mean absolute difference (MAD), and mean squared difference (MSD) were compared between the two approaches.

RESULTS

In total, 3320 respondents (50.3% male; range 18-90 years) were recruited. The random-effects model and the conditional logit model were preferred for the TTO and DCE_TTO, respectively. The TTO values ranged from - 0.277 to 1, with 927 (4.94%) states considered as worse than dead (WTD). The corresponding range for DCE_TTO was - 0.535 to 1, with a higher WTD of 8.50%. DCE_TTO presented minor non-monotonicity with the coefficients in two dimensions. Values from the two approaches were highly consistent (ICC 0.9804, MAD 0.0588, MSD 0.0055), albeit those with DCE_TTO were slightly lower than those with TTO. The value set generated by TTO was preferred given the better monotonicity and the statistical significance of coefficients.

CONCLUSIONS

The Chinese value set for the SF-6Dv2 was established based on the TTO approach, but the DCE_TTO also performed well. Minor issues of non-monotonicity did present for DCE_TTO.

United States Utility Algorithm for the EORTC QLU-C10D, a Multiattribute Utility Instrument Based on a Cancer-Specific Quality-of-Life Instrument

BACKGROUND

The EORTC QLU-C10D is a multiattribute utility measure derived from the cancer-specific quality-of-life questionnaire, the EORTC QLQ-C30. The QLU-C10D contains 10 dimensions (physical, role, social and emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems). The objective of this study was to develop a United States value set for the QLU-C10D.

METHODS

A US online panel was quota recruited to achieve a representative sample for sex, age (≥18 y), race, and ethnicity. Respondents undertook a discrete choice experiment, each completing 16 choice-pairs, randomly assigned from a total of 960 choice-pairs. Each pair included 2 QLU-C10D health states and duration. Data were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each dimension-level coefficient to the coefficient for life expectancy.

RESULTS

A total of 2480 panel members opted in, 2333 (94%) completed at least 1 choice-pair, and 2273 (92%) completed all choice-pairs. Within dimensions, weights were generally monotonic. Physical functioning, role functioning, and pain were associated with the largest utility weights. Cancer-specific dimensions, such as nausea and bowel problems, were associated with moderate utility decrements, as were general issues such as problems with emotional functioning and social functioning. Sleep problems and fatigue were associated with smaller utility decrements. The value of the worst health state was 0.032, which was slightly greater than 0 (equivalent to being dead).

CONCLUSIONS

This study provides the US-specific value set for the QLU-C10D. These estimated health state scores, based on responses to the EORTC QLQ-C30 questionnaire, can be used to evaluate the cost-utility of oncology treatments.

Frailty state utility and minimally important difference: findings from the North West Adelaide Health Study

BACKGROUND

frailty is a dynamic condition for which a range of interventions are available. Health state utilities are values that represent the strength of an individual's preference for specific health states, and are used in economic evaluation. This is a topic yet to be examined in detail for frailty. Likewise, little has been reported on minimally important difference (MID), the extent of change in frailty status that individuals consider to be important.

OBJECTIVES

to examine the relationship between frailty status, for both the frailty phenotype (FP) and frailty index (FI), and utility (preference-based health state), and to determine a MID for both frailty measures.

DESIGN AND SETTING

population-based cohort of community-dwelling Australians.

PARTICIPANT

in total, 874 adults aged ≥65 years (54% female), mean age 74.4 (6.2) years.

MEASUREMENTS

frailty was measured using the FP and FI. Utilities were calculated using the short-form 6D health survey, with Australian and UK weighting applied. MID was calculated cross-sectionally.

RESULTS

for both the FP and FI, frailty was significantly statistically associated (P < 0.001) with lower utility in an adjusted analysis using both Australian and UK weighting. Between-person MID for the FP was identified as 0.59 [standard deviation (SD) 0.31] (anchor-based) and 0.59 (distribution-based), whereas for the FI, MID was 0.11 (SD 0.05) (anchor-based) and 0.07 (distribution-based).

CONCLUSIONS

frailty is significantly associated with lower preference-based health state utility. Frailty MID can be used to inform design of clinical trials and economic evaluations, as well as providing useful clinical information on frailty differences that patients consider important.

Absolute risk assessment for guiding cardiovascular risk management in a chest pain clinic

OBJECTIVES

To assess the efficacy of a pro-active, absolute cardiovascular risk-guided approach to opportunistically modifying cardiovascular risk factors in patients without coronary ischaemia attending a chest pain clinic.

DESIGN

Prospective, randomised, open label, blinded endpoint study.

SETTING

The rapid access chest pain clinic of Royal Hobart Hospital, a tertiary hospital.

PARTICIPANTS

Patients who presented to the chest pain clinic between 1 July 2014 and 31 December 2017 who had intermediate to high absolute cardiovascular risk scores (5-year risk ≥ 8%). Patients with known cardiac disease or from groups with clinically determined high risk of cardiovascular disease were excluded.

MAIN OUTCOME MEASURES

The primary endpoint was change in 5-year absolute risk score (Australian absolute risk calculator) at follow-up (at least 12 months after baseline assessment). Secondary endpoints were changes in lipid profile, blood pressure, smoking status, and body mass index, and major adverse cardiovascular events.

RESULTS

The mean change in risk at follow-up was +0.4 percentage points (95% CI, -0.8 to 1.5 percentage points) for the 98 control group patients and -2.4 percentage points (95% CI, -1.5 to -3.4 percentage points) for the 91 intervention group patients; the between-group difference in change was 2.7 percentage points (95% CI, 1.2-4.1 percentage points). Mean changes in lipid profile, systolic blood pressure, and smoking status were larger for the intervention group, but not statistically different from those for the control group.

CONCLUSIONS

An absolute cardiovascular risk-guided, pro-active risk factor management strategy employed opportunistically in a chest pain clinic significantly improved 5-year absolute cardiovascular risk scores.

TRIAL REGISTRATION

Australia New Zealand Clinical Trial Registry, ACTRN12617000615381 (retrospective).

Effects of Metreleptin on Patient Outcomes and Quality of Life in Generalized and Partial Lipodystrophy

Generalized and partial lipodystrophy are rare and complex diseases with progressive clinical and humanistic burdens stemming from selective absence of subcutaneous adipose tissue, which causes reduced energy storage capacity and a deficiency of adipokines such as leptin. Treatment options were limited before leptin replacement therapy (metreleptin) became available. This retrospective study evaluates both clinical and humanistic consequences of the disease and treatment. Chart data were abstracted from a cohort of metreleptin-treated patients with generalized and partial lipodystrophy (n = 112) treated at the US National Institutes of Health. To quantify the quality-of-life consequences of the lipodystrophy disease attributes recorded in chart data, a discrete choice experiment was completed in 6 countries (US, n = 250; EU, n = 750). Resulting utility decrements were used to estimate the quality-adjusted life-year consequences of changes in lipodystrophy attribute prevalence before and after metreleptin. In addition to metabolic impairment, patients with generalized and partial lipodystrophy experienced a range of lipodystrophy consequences, including liver abnormality (94%), hyperphagia (79%), impaired physical appearance (77%), kidney abnormality (63%), reproductive dysfunction (80% of females of reproductive age), and pancreatitis (39%). Improvement was observed in these attributes following initiation of metreleptin. Quality-adjusted life-year gains associated with 12 months of treatment with metreleptin were estimated at 0.313 for generalized and 0.117 for partial lipodystrophy, reducing the gap in quality of life between untreated lipodystrophy and perfect health by approximately 59% and 31%, respectively. This study demonstrates that metreleptin is associated with meaningful clinical and quality-of-life improvements.