An Australian discrete choice experiment to value eq-5d health states

Sex differences in quality of life after stroke were explained by patient factors, not clinical care: evidence from the Australian Stroke Clinical Registry

BACKGROUND AND PURPOSE

Women may receive stroke care less often than men. We examined the contribution of clinical care on sex differences and health-related quality of life (HRQoL) after stroke.

METHODS

We included first-ever strokes registered in the Australian Stroke Clinical Registry (2010-2014) with HRQoL assessed between 90 and 180 days after onset (EQ-5D-3L instrument) that were linked to hospital administrative data (up to 2013). Study factors included sociodemographics, comorbidities, walking ability on admission (stroke severity proxy) and clinical care (e.g. stroke unit care). Responses to the EQ-5D-3L were transformed into a total utility value (-0.516 'worse than death' to 1 'best' health). Quantile regression models, adjusted for confounding factors, were used to determine median differences (MD) in utility scores by sex.

RESULTS

Approximately 60% (6852/11 418) of stroke survivors had an EQ-5D-3L assessment (median 139 days; 44% female). Compared with men, women were older (median age 77.1 years vs. men 71.2 years) and fewer could walk on admission (37.9% vs. men 46.1%, P < 0.001). Women had lower utility values than men, and the difference was explained by age and stroke severity, but not clinical care [MD_{adjusted =} -0.039, 95% confidence interval: -0.056, -0.021]. Poorer HRQoL was observed in younger men (aged <65 years), particularly those with more comorbidities, and in older women (aged ≥75 years).

CONCLUSIONS

Stroke severity and comorbidities contribute to the poorer HRQoL in young men and older women. Further studies are needed to understand age-sex interaction to better inform treatments for different subgroups and ensure evidence-based treatments to reduce the severity of stroke are prioritized.

Do Discrete Choice Experiments Approaches Perform Better Than Time Trade-Off in Eliciting Health State Utilities? Evidence From SF-6Dv2 in China

OBJECTIVES

To explore the acceptability, consistency, and accuracy of eliciting health state utility values using discrete choice experiment (DCE) and DCE with life duration dimension (DCE_TTO) as compared with conventional time trade-off (TTO) by using the SF-6Dv2.

METHODS

During face-to-face interviews, a representative sample of the general population in Tianjin, China, completed 8 TTO tasks and 10 DCE/DCE_TTO tasks, with the order of TTO and DCE/DCE_TTO being randomized. The fixed-effect model and conditional logit models were used for TTO and DCEs data estimation, respectively. Acceptability was assessed by self-reported difficulties in understanding/answering. Consistency was observed by the monotonicity of model coefficients. Accuracy was evaluated by investigating differences between observed and predicted TTO values using intraclass correlation coefficient, mean absolute difference, and root mean square difference.

RESULTS

A total of 503 respondents (53.7% male; range, 18-86 years) were included, with comparable characteristics between respondents who completed DCE (N = 252) and DCE_TTO (N = 251). No significant difference was observed in self-reported difficulties among 3 approaches. The monotonicity of coefficients could not be achieved for 2 DCE approaches, even when combining the inconsistent levels. The health state utility values generated by DCE were generally higher than those generated by TTO, whereas DCE_TTO was lower than TTO. The TTO had a better prediction accuracy than the DCEs.

CONCLUSIONS

Two DCE approaches are feasible for eliciting health state utility values; however, they are not considered to be easier to understand/answer than TTO. There are systematic differences in the health state utility values generated by 3 approaches. The issue of non-monotonicity from 2 DCE approaches remains a concern.

The cost-effectiveness of adjunctive corticosteroids for patients with septic shock

OBJECTIVE

To determine whether hydrocortisone is a cost-effective treatment for patients with septic shock.

DESIGN

Data linkage-based cost-effectiveness analysis.

SETTING

New South Wales and Queensland intensive care units.

PARTICIPANTS AND INTERVENTION

Patients with septic shock randomly assigned to treatment with hydrocortisone or placebo in the Adjunctive Glucocorticoid Therapy in Patients with Septic Shock (ADRENAL) trial.

MAIN OUTCOME MEASURES

Health-related quality of life at 6 months using the EuroQoL 5-dimension 5-level questionnaire. Data on hospital resource use and costs were obtained by linking the ADRENAL dataset to government administrative health databases. Clinical outcomes included mortality, health-related quality of life, and quality-adjusted life-years gained; economic outcomes included hospital resource use, costs and cost-effectiveness from the health care payer perspective. We also assessed cost-effectiveness by sex. To increase the precision of cost-effectiveness estimates, we conducted unrestricted bootstrapping.

RESULTS

Of 3800 patients in the ADRENAL trial, 1772 (46.6%) were eligible and 1513 (85.4% of those eligible) were included. There was no difference between hydrocortisone or placebo groups in regards to mortality (218/742 [29.4%] v 227/759 [29.9%]; HR, 0.93; 95% CI, 0.78-1.12; P = 0.47), mean number of QALYs gained (0.10 ± 0.09 v 0.10 ± 0.09; P = 0.52), or total hospital costs (A$73 515 ± 61 376 v A$69 748 ± 61 793; mean difference, A$3767; 95% CI, -A$2891 to A$10 425; P = 0.27). The incremental cost of hydrocortisone was A$1 254 078 per quality-adjusted life-year gained. In females, hydrocortisone was cost-effective in 46.2% of bootstrapped replications and in males it was cost-effective in 2.7% of bootstrapped replications.

CONCLUSIONS

Adjunctive hydrocortisone did not significantly affect longer term mortality, health-related quality of life, health care resource use or costs, and is unlikely to be cost-effective.

Does Device or Connection Type Affect Health Preferences in Online Surveys?

BACKGROUND AND OBJECTIVE

Recent evidence has shown that online surveys can reliably collect preference data, which markedly decrease the cost of health preference studies and expand their representativeness. As the use of mobile technology continues to grow, we wanted to examine its potential impact on health preferences.

METHODS

Two recently completed discrete choice experiments using members of the US general population (n = 15,292) included information on respondent device (cell phone, tablet, Mac, PC) and internet connection (business, cellular, college, government, residential). In this analysis, we tested for differences in respondent characteristics, participation, response quality, and utility values for the 5-level EQ-5D (EQ-5D-5L) by device and connection.

RESULTS

Compared to Mac and PC users, respondents using a cell phone or tablet had longer completion times and were significantly more likely to drop out during the surveys (p < 0.001). Tablet users also demonstrated more logical inconsistencies (p = 0.05). Likewise, respondents using a cellular internet connection exhibit significantly less consistency in their health preferences. However, matched samples for tablets and cell phones produced similar EQ-5D-5L utility values (mean differences < 0.06 on a quality-adjusted life-year [QALY] scale for all potential health states).

CONCLUSION

Allowing respondents to complete online surveys using a cell phone or tablet or over a cellular connection substantially increases the diversity of respondents and the likelihood of obtaining a representative sample, as many individuals have cell phones but not a computer. While the results showed systematic variability in participation and response quality by device and connection type, this study did not show any meaningful changes in utility values.

Implausible States: Prevalence of EQ-5D-5L States in the General Population and Its Effect on Health State Valuation

The EQ-5D is made up of health state dimensions and levels, in which some combinations seem less "plausible" than others. If "implausible" states are used in health state valuation exercises, then respondents may have difficulty imagining them, causing measurement error. There is currently no standard solution: some valuation studies exclude such states, whereas others leave them in. This study aims to address 2 gaps in the literature: 1) to propose an evidence-based set of the least prevalent two-way combinations of EQ-5D-5L dimension levels and 2) to quantify the impact of removing perceived implausible states from valuation designs. For the first aim, we use data from 2 waves of the English General Practitioner Patient Survey (n = 1,639,453). For the second aim, we remodel a secondary data set of a Discrete Choice Experiment (DCE) with duration that valued EQ-5D-5L and compare across models that drop observations involving different health states: 1) implausible states as defined in the literature, 2) the least prevalent states identified in stage 1, and 3) randomly select states, alongside 4) a model that does not drop any observations. The results indicate that two-way combinations previously thought to be implausible actually exist among the general population; there are other combinations that are rarer, and removing implausible states from an experimental design of a DCE with duration leads to value sets with potentially different characteristics depending on the criterion of implausible states. We advise against the routine removal of implausible states from health state valuation studies.

Health-related quality of life in survivors of septic shock: 6-month follow-up from the ADRENAL trial

PURPOSE

To investigate the impact of hydrocortisone treatment and illness severity on health-related quality of life (HRQoL) at 6 months in septic shock survivors from the ADRENAL trial.

METHODS

Using the EuroQol questionnaire (EQ-5D-5L) at 6 months after randomization we assessed HRQoL in patient subgroups defined by hydrocortisone or placebo treatment, gender, illness severity (APACHE II < or ≥ 25), and severity of shock (baseline peak catecholamine doses < or ≥ 15 mcg/min). Additionally, in subgroups defined by post-randomisation variables; time to shock reversal (days), treatment with renal replacement therapy (RRT), and presence of bacteremia.

RESULTS

At 6 months, there were 2521 survivors. Of these 2151 patients (85.3%-1080 hydrocortisone and 1071 placebo) completed 6-month follow-up. Overall, at 6 months the mean EQ-5D-5L visual analogue scale (VAS) was 70.8, mean utility score 59.4. Between 15% and 30% of patients reported moderate to severe problems in any given HRQoL domain. There were no differences in any EQ-5D-5L domain in patients who received hydrocortisone vs. placebo, nor in the mean VAS (p = 0.6161), or mean utility score (p = 0.7611). In all patients combined, males experienced lower pain levels compared to females [p = 0.0002). Neither higher severity of illness or shock impacted reported HRQoL. In post-randomisation subgroups, longer time to shock reversal was associated with increased problems with mobility (p = < 0.0001]; self-care (p = 0.0.0142), usual activities (p = <0.0001] and pain (p = 0.0384). Amongst those treated with RRT, more patients reported increased problems with mobility (p = 0.0307) and usual activities (p = 0.0048) compared to those not treated. Bacteraemia was not associated with worse HRQoL in any domains of the EQ-5D-5L.

CONCLUSIONS

Approximately one fifth of septic shock survivors report moderate to extreme problems in HRQoL domains at 6 months. Hydrocortisone treatment for septic shock was not associated with improved HRQoL at 6 months. Female gender was associated with worse pain at 6 months.

Blood pressure postpartum (BP2) RCT protocol: Follow-up and lifestyle behaviour change strategies in the first 12 months after hypertensive pregnancy

OBJECTIVES

Women who had hypertensive disorders of pregnancy (HDP) are twice as likely to experience maternal cardiovascular disease later in life. The primary aim of this study (BP²) is to compare outcomes of 3 different management strategies, including lifestyle behaviour change (LBC), in the first 12 months postpartum in women who had HDP in their preceding pregnancy. Secondary aims include assessing the effects on other cardiometabolic parameters.

STUDY DESIGN

Three-arm multicentre randomised trial in metropolitan Australian hospitals, (registration: ACTRN12618002004246) target sample size 480. Participants are randomised to one of three groups: 1) Optimised usual care: information package and family doctor follow-up 6 months postpartum 2) Brief intervention: information package as per group 1, plus assessment and brief LBC counselling at a specialised clinic with an obstetric physician and dietitian 6 months postpartum 3) Extended intervention: as per group 2 plus enrolment into a 6 month telephone-based LBC program from 6 to 12 months postpartum. All women have an outcome assessment at 12 months.

MAIN OUTCOME MEASURES

Primary outcomes: (a) BP change or (b) weight change and/or waist circumference change.

SECONDARY OUTCOMES

maternal health-related quality of life, engagement and retention in LBC program, biochemical markers, vascular function testing, infant weight trajectory, incremental cost-effectiveness ratios. The study is powered to detect a 4 mmHg difference in systolic BP between groups, or a 4 kg weight loss difference/2cm waist circumference change.

CONCLUSIONS

BP² will provide evidence regarding the feasibility and effectiveness of postpartum LBC interventions and structured clinical follow-up in improving cardiovascular health markers after HDP.

Transforming discrete choice experiment latent scale values for EQ-5D-3L using the visual analogue scale

BACKGROUND

Discrete choice experiments (DCEs) are widely used to elicit health state preferences. However, additional information is required to transform values to a scale with dead valued at 0 and full health valued at 1. This paper presents DCE-VAS, an understandable and easy anchoring method with low participant burden based on the visual analogue scale (VAS).

METHODS

Responses from 1450 members of the UK general public to a discrete choice experiment (DCE) were analysed using mixed logit models. Latent scale valuations were anchored to a full health = 1, dead = 0 scale using participants' VAS ratings of three states including the dead. The robustness of results was examined. This included a filtering procedure with the influence each individual respondent had on valuation being calculated, and those whose influence was more than two standard deviations away from the mean excluded.

RESULTS

Coefficients in all models were in the expected direction and statistically significant. Excluding respondents who self-reported not understanding the VAS task did not significantly influence valuation, but excluding a small number who valued 33333 extremely low did. However, after eight respondents were removed via the filtering procedure, valuations were robust to removing other participants.

CONCLUSION

DCE-VAS is a feasible way of anchoring DCE results to a 0-1 anchored scale with low additional respondent burden.

Peruvian Valuation of the EQ-5D-5L: A Direct Comparison of Time Trade-Off and Discrete Choice Experiments

OBJECTIVES

(1) To produce Peruvian general population EQ-5D-5L value sets on a quality-adjusted life-year scale, (2) to investigate the feasibility of a "Lite" protocol less reliant on the composite time trade-off (cTTO), and (3) to compare cTTO and discrete choice experiment (DCE) value sets.

METHODS

A random sample of adults (N = 1000) in Lima, Arequipa, and Iquitos did a home interview; 300 were randomly selected to complete 11 cTTOs first. All respondents completed a DCE, including 10 latent-scale pairs (A/B) with 5 EQ-5D-5L attributes, and 12 matched pairs (A/B and B/C) with 5 EQ-5D-5L and one lifespan attributes. We estimated a cTTO heteroscedastic tobit (N = 300) model and 3 DCE Zermelo-Bradley-Terry models (N = 300, 700, and 1000).

RESULTS

Each model produced a consistent value set (20 positive incremental parameters). Nevertheless, their lowest quality-adjusted life-year values differed greatly (cTTO: -1.076 [N = 300]; DCE: -0.984 [300], 0.048 [700], -0.213 [1000]). Compared with the cTTO, the DCE (N = 300) produced different parameters (Pearson's correlation = 0.541), fewer insignificant parameters (0 vs 8), and fewer values less than 0 (26% vs 44%). Compared with the DCE (N = 300), the DCE (N = 700) produced higher values but similar parameters (Pearson's correlation = 0.800).

CONCLUSIONS

Besides producing EQ-5D-5L value sets for Peru, the results casts doubt about the feasibility of a Lite protocol like the one in this study. Additionally, fundamental differences between cTTO and DCE-without the existence of a gold standard-need further clarification. The choice between the two rational value sets produced in the current study is a matter of judgment and may have substantial policy implications.

Prenusinersen economic and health-related quality of life burden of spinal muscular atrophy

Objective

To quantify the economic and health-related quality of life (HRQoL) burden incurred by households with a child affected by spinal muscular atrophy (SMA).

Methods

Hospital records, insurance claims, and detailed resource use questionnaires completed by caregivers were used to capture the direct and indirect costs to households of 40 children affected by SMA I, II, and III in Australia between 2016 and 2017. Prevalence costing methods were used and reported in 2017 US dollar (USD) purchasing power parity (PPP). The HRQoL for patients and primary caregivers was quantified with the youth version of the EQ-5D and CareQoL multiattribute utility instruments and Australian utility weights.

Results

The average total annual cost of SMA per household was $143,705 USD PPP for all SMA types (SMA I $229,346, SMA II $150,909, SMA III $94,948). Direct costs accounted for 56% of total costs. The average total indirect health care costs for all SMA types were $63,145 per annum and were highest in families affected by SMA II. Loss of income and unpaid informal care made up 24.2% and 19.8% respectively, of annual SMA costs. Three of 4 (78%) caregivers stated that they experienced financial problems because of care tasks. The loss in HRQoL of children affected by SMA and caregivers was substantial, with average caregiver and patient scores of 0.708 and 0.115, respectively (reference range 0 = death and 1 = full health).

Conclusion

Our results demonstrate the substantial and far-ranging economic and quality of life burden on households and society of SMA and are essential to fully understanding the health benefits and cost-effectiveness associated with emerging disease-modifying therapies for SMA.

Cost-Effectiveness of IncobotulinumtoxinA in the Treatment of Sialorrhea in Patients with Various Neurological Conditions

INTRODUCTION

Sialorrhea is a common and debilitating symptom associated with neurological conditions, which can result in considerable physical and psychosocial complications. In Australia, management options are limited and further impeded by the lack of approved treatments. Whilst there is emerging evidence for the efficacy and tolerability of botulinum toxin (BoNT) for the treatment of sialorrhea in patients with neurological conditions, the cost-effectiveness of the treatment is yet to be established.

OBJECTIVES

To evaluate the cost-effectiveness of incobotulinumtoxinA for the treatment of chronic troublesome sialorrhea caused by various neurological conditions from the Australian healthcare perspective.

METHODS

A Markov state transition model was developed to perform a cost-utility analysis comparing incobotulinumtoxinA with standard of care (SoC). The model consisted of a hypothetical cohort of patients transiting between three severity-based health states, defined according to the Drooling Severity and Frequency Scale (DSFS), in 16-weekly cycles over 5 years. All clinical and utility inputs were sourced from a single placebo-controlled randomised clinical trial. Only direct healthcare costs were considered, and potential indirect costs such as carer's time and lost productivity were ignored. The primary outcome measure was the incremental cost per quality-adjusted life-year (QALY). Univariate and probabilistic sensitivity analyses were conducted.

RESULTS

The model demonstrated that proportionally more patients spent time in less severe sialorrhea health states in the incobotulinumtoxinA arm. For example, over the 5-year period, patients receiving incobotulinumtoxinA were estimated to spend 1.6 years with minimal or no sialorrhea, while no patients achieved this level of improvement under SoC. IncobotulinumtoxinA was shown to have an incremental cost per QALY gained of A$23,445 when compared with SoC.

CONCLUSIONS

The quality of life (QoL) of patients with sialorrhea caused by neurological conditions was considerably compromised. IncobotulinumtoxinA was shown to successfully alleviate sialorrhea and it was demonstrated to be a cost-effective intervention when compared with SoC alone.

Using the Choice Sequence in Time Trade-Off as Discrete Choices: Do the Two Stories Match?

OBJECTIVES

The EQ-5D-5L valuation protocol recommends combining time trade-off (TTO) and discrete choice experiments (DCEs). DCEs that include a duration attribute (DCE_TTO) allow modeling on the quality-adjusted life-year scale. Because the choice sequence in a TTO can be construed as a series of DCE_TTO, we used data from a single TTO study to investigate the extent to which DCE values match TTO values when based on identical preferences.

METHODS

In a TTO design in which a fixed set of choices were administered without termination at preference indifference, 202 individuals each valued 10 EQ-5D health states. From identified indifference points, we estimated three sets of TTO values: (i) plotting means and (ii) applying censored regressions at -1 and 1. Using all strict preferences, we (iii) estimated DCE_TTO values with a logit model and a bootstrap procedure.

RESULTS

Estimated DCE_TTO and TTO values agreed well at the severe end of the quality-adjusted life-year scale, but with decreasing severity, DCE_TTO values were higher than TTO-values, with the difference peaking at 0.37 for the mildest health state. Left-censoring TTO values at -1 worsen the agreement for the worst health states and did not affect health states. Right censoring at 1 improved the agreement for mild states.

CONCLUSIONS

TTO and the DCE_TTO values estimated from the same preference data diverged, with increasing difference for milder health states. Although the values converged when applying censored regression at +1, we question the validity of this adjustment.

Constraint-induced or multi-modal personalized aphasia rehabilitation (COMPARE): A randomized controlled trial for stroke-related chronic aphasia

RATIONALE

The comparative efficacy and cost-effectiveness of constraint-induced and multi-modality aphasia therapy in chronic stroke are unknown.

AIMS AND HYPOTHESES

In the COMPARE trial, we aim to determine whether Multi-Modal Aphasia Treatment (M-MAT) and Constraint-Induced Aphasia Therapy Plus (CIAT-Plus) are superior to usual care (UC) for chronic post-stroke aphasia. Primary hypothesis: CIAT-Plus and M-MAT will reduce aphasia severity (Western Aphasia Battery-Revised Aphasia Quotient (WAB-R-AQ)) compared with UC: CIAT-Plus superior for moderate aphasia; M-MAT superior for mild and severe aphasia.

SAMPLE SIZE ESTIMATES

A total of 216 participants (72 per arm) will provide 90% power to detect a 5-point difference on the WAB-R-AQ between CIAT-Plus or M-MAT and UC at α = 0.05.

METHODS AND DESIGN

Prospective, randomized, parallel group, open-label, assessor blinded trial. Participants: Stroke >6 months; aphasia severity categorized using WAB-R-AQ. Computer-generated blocked and stratified randomization by aphasia severity (mild, moderate, and severe), to 3 arms: CIAT-Plus, M-MAT (both 30 h therapy over two weeks); UC (self-reported usual community care).

STUDY OUTCOMES

WAB-R-AQ immediately post-intervention. Secondary outcomes: WAB-R-AQ at 12-week follow-up; naming scores, discourse measures, Communicative Effectiveness Index, Scenario Test, and Stroke and Aphasia Quality of Life Scale-39 g immediately and at 12 weeks post-intervention; incremental cost-effectiveness ratios compared with UC at 12 weeks.

DISCUSSION

This trial will determine whether CIAT-Plus and M-MAT are superior and more cost-effective than UC in chronic aphasia. Participant subgroups with the greatest response to CIAT-Plus and M-MAT will be described.

U.K. utility weights for the EORTC QLU-C10D

The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely used cancer-specific quality of life questionnaire, EORTC QLQ-C30. It contains 10 dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems), each with four levels. The aim of this study was to provide U.K. general population utility weights for the QLU-C10D. A U.K. online panel was quota-sampled to align the sample to the general population proportions of sex and age (≥18 years). The online valuation survey included a discrete choice experiment (DCE). Each participant was asked to complete 16 choice-pairs, each comprising two QLU-C10D health states plus duration. DCE data were analysed using conditional logistic regression to generate utility weights. Data from 2,187 respondents who completed at least one choice set were included in the DCE analysis. The final U.K. QLU-C10D utility weights comprised decrements for each level of each health dimension. For nine of the 10 dimensions (all except appetite), the expected monotonic pattern was observed across levels: Utility decreased as severity increased. For the final model, consistent monotonicity was achieved by merging inconsistent adjacent levels for appetite. The largest utility decrements were associated with physical functioning and pain. The worst possible health state (the worst level of each dimension) is -0.083, which is considered slightly worse than being dead. The U.K.-specific utility weights will enable cost-utility analysis (CUA) for the economic evaluation of new oncology therapies and technologies in the United Kingdom, where CUA is commonly used to inform resource allocation.

A new tool for creating personal and social EQ-5D-5L value sets, including valuing 'dead'

The EuroQol Group's health descriptive systems, the EQ-5D-3L and its successor introduced in 2009, the EQ-5D-5L, are widely used worldwide for valuing health-related quality of life for cost-utility analysis and patient-reported health outcome measures. A new online tool for creating personal and social EQ-5D-5L value sets was recently developed and trialled in New Zealand (NZ). The tool, which includes extensive checks of the quality of participants' data, implements the PAPRIKA method - a novel type of adaptive discrete choice experiment in the present context - and a binary search algorithm to identify any health states worse than dead. After development and testing, the tool was distributed in an online survey in February and March 2018 to a representative sample of NZ adults (N = 5112), whose personal value sets were created. The tool's extensive data quality checks resulted in a 'high-quality' sub-sample of 2468 participants whose personal value sets were, in effect, averaged to create a social value set for NZ. These results overall as well as feedback from participants indicates that the new valuation tool is feasible and acceptable to participants, enabling valuation data to be relatively easily and cheaply collected. The tool could also be used in other countries, tested against other methods for creating EQ-5D-5L value sets, applied in personalised medicine and adapted to create value sets for other health descriptive systems.

Investigating the relative value of health and social care related quality of life using a discrete choice experiment

A key outcome in the evaluation of health technologies is the quality adjusted life year (QALY) which is often estimated using health measures such as the EuroQol instruments (EQ-5D-3L and EQ-5D-5L). The impacts of many interventions extend beyond a narrow definition of health to include non-health impacts such as social care related dimensions of quality of life (QoL). This means that there are circumstances where the QALY does not capture the full value of an intervention. In response to this, instruments with a wider measurement framework, such as the Adult Social Care Outcomes Toolkit (ASCOT), which measures social care related QoL, have been developed. Given the range of instruments available, it is important that decision-makers have tools to assess value for money comprehensively and consistently. To date, preference elicitation of different aspects of QoL combined within the same valuation procedure has not been tested. We investigate the relationship between health and social care aspects of QoL when assessed jointly by combining EQ-5D-5L and ASCOT in an online discrete choice experiment (DCE). In July 2016, 975 respondents recruited from internet panels completed 15 choice sets from an underlying design of 300. Conditional logit regression was used to estimate coefficient decrements for each attribute and examine their relative magnitude. Latent class and mixed logit modelling were used to understand preference heterogeneity. The results suggest trading across health and social care aspects indicated by coefficient estimates of differing magnitude. Dimensions with the largest disutility include four from EQ-5D-5L and one from ASCOT. There is evidence of preference heterogeneity at more severe dimension levels. We have used an established method to test the joint valuation of concepts measuring different aspects of QoL. The results have implications for the aspects of QoL that are included in QALY estimation and used in resource allocation decision-making.

The EORTC QLU-C10D: The Canadian Valuation Study and Algorithm to Derive Cancer-Specific Utilities From the EORTC QLQ-C30

Objective. The EORTC QLQ-C30 is widely used for assessing quality of life in cancer. However, QLQ-C30 responses cannot be incorporated in cost-utility analysis because they are not based on general population's preferences, or utilities. To overcome this limitation, the QLU-C10D, a cancer-specific utility algorithm, was derived from the QLQ-C30. The aim of this study was to obtain Canadian population utility weights for the QLU-C10D. Methods. Respondents from a Canadian research panel expressed their preferences for 16 choice sets in an online discrete choice experiment. Each choice set consisted of two health states described by the 10 QLU-C10D domains plus an attribute representing duration of survival. Using a conditional logit model, responses were converted into utility decrements by evaluating the marginal rate of substitution between each QLU-C10D domain level with respect to duration. Results. A total of 3,363 individuals were recruited. A total of 2,345 completed at least one choice set and 2,271 completed all choice sets. The largest utility decrements were associated with the worse levels of Physical Functioning (-0.24), Pain (-0.18), Role Functioning (-0.15), Emotional Functioning (-0.12), and Nausea (-0.12). The remaining domains and levels had decrements of -0.05 to -0.09. The utility of the worst possible health state was -0.15. Conclusion. Respondents from the general population were most concerned with generic health domains, but Nausea and Bowel Problems also had an impact on the individual's utility. It is unclear as to whether cancer-specific domains will affect cost-utility analysis when evaluating cancer treatments; this will be tested in the next phase of the study.

Cost Effectiveness of Long-Term Incobotulinumtoxin-A Treatment in the Management of Post-stroke Spasticity of the Upper Limb from the Australian Payer Perspective

BACKGROUND

In Australia, the reimbursement of botulinum neurotoxin-A (BoNT-A) on the Pharmaceutical Benefits Scheme for the treatment of moderate to severe spasticity of the upper limb following a stroke (PSS-UL) is restricted to four treatment cycles per upper limb per lifetime. This analysis examined the cost effectiveness of extending the treatment beyond four treatments among patients with an adequate response to previous treatment cycles.

METHODS

A Markov state transition model was developed to perform a cost-utility analysis of extending the use of incobotulinumtoxin-A beyond the current restriction of four treatment cycles among patients who have shown a successful response in previous treatment cycles ('known responders'). The Markov model followed patients in 12-weekly cycles for 5 years, estimating the proportion of patients with or without response over this period in each of the modelled treatment arms. Post hoc analysis of an open-label extension phase study informed the Markov model. The perspective of the analysis was the Australian healthcare system, meaning only direct healthcare costs were included. Utility values by response status were derived from EQ-5D data from a published double-blind, placebo-controlled study. The primary outcome measure was the incremental cost per quality-adjusted life-year (QALY). Univariate and probabilistic sensitivity analyses were conducted.

RESULTS

The open-label extension study data demonstrated the probability of treatment response after four injections was greater among 'known responders' than those without prior response. The incremental cost per QALY gained of continued use of incobotulinumtoxin-A beyond the current restriction of four treatments was A$59,911.

CONCLUSION

Limiting BoNT-A treatment to four cycles per patient per lifetime is likely to be suboptimal in many patients with PSS-UL. Treatment response beyond four cycles is highest among known responders, and allowing such patients to continue treatment beyond four cycles appears cost effective.

Link-me: Protocol for a randomised controlled trial of a systematic approach to stepped mental health care in primary care

Primary care in Australia is undergoing significant reform, with a particular focus on cost-effective tailoring of mental health care to individual needs. Link-me is testing whether a patient-completed Decision Support Tool (DST), which predicts future severity of depression and anxiety symptoms and triages individuals into care accordingly, is clinically effective and cost-effective relative to usual care. The trial is set in general practices, with English-speaking patients invited to complete eligibility screening in their general practitioner's waiting room. Eligible and consenting patients will then complete the DST assessment and are randomised and stratified according to predicted symptom severity. Participants allocated to the intervention arm will receive feedback on DST responses, select treatment priorities, assess motivation to change, and receive a severity-matched treatment recommendation (information about and links to low intensity services for those with mild symptoms, or assistance from a specially trained health professional (care navigator) for those with severe symptoms). All patients allocated to the comparison arm will receive usual GP care plus attention control. Primary (psychological distress) and secondary (depression, anxiety, quality of life, days out of role) outcomes will be assessed at 6 and 12 months. Differences in outcome means between trial arms both across and within symptom severity group will be examined using intention-to-treat analyses. Within trial and modelled economic evaluations will be conducted to determine the value for money of credentials of Link-me. Findings will be reported to the Federal Government to inform how mental health services across Australia are funded and delivered in the future.

Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments

A randomized controlled discrete choice experiment (DCE) with 3,320 participating respondents was used to investigate the individual and combined impact of level overlap and color coding on task complexity, choice consistency, survey satisfaction scores, and dropout rates. The systematic differences between the study arms allowed for a direct comparison of dropout rates and cognitive debriefing scores and accommodated the quantitative comparison of respondents' choice consistency using a heteroskedastic mixed logit model. Our results indicate that the introduction of level overlap made it significantly easier for respondents to identify the differences and choose between the choice options. As a stand-alone design strategy, attribute level overlap reduced the dropout rate by 30%, increased the level of choice consistency by 30%, and avoided learning effects in the initial choice tasks of the DCE. The combination of level overlap and color coding was even more effective: It reduced the dropout rate by 40% to 50% and increased the level of choice consistency by more than 60%. Hence, we can recommend attribute level overlap, with color coding to amplify its impact, as a standard design strategy in DCEs.

Discrete Choice Experiments in Health Economics: Past, Present and Future

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990-2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges.

METHODS

A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated.

RESULTS

Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels.

CONCLUSIONS

The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers' confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research.

One Method, Many Methodological Choices: A Structured Review of Discrete-Choice Experiments for Health State Valuation

BACKGROUND

Discrete-choice experiments (DCEs) are used in the development of preference-based measure (PBM) value sets. There is considerable variation in the methodological approaches used to elicit preferences.

OBJECTIVE

Our objective was to carry out a structured review of DCE methods used for health state valuation.

METHODS

PubMed was searched until 31 May 2018 for published literature using DCEs for health state valuation. Search terms to describe DCEs, the process of valuation and preference-based instruments were developed. English language papers with any study population were included if they used DCEs to develop or directly inform the production of value sets for generic or condition-specific PBMs. Assessment of paper quality was guided by the recently developed Checklist for Reporting Valuation Studies. Data were extracted under six categories: general study information, choice task and study design, type of designed experiment, modelling and analysis methods, results and discussion.

RESULTS

The literature search identified 1132 published papers, and 63 papers were included in the review. Paper quality was generally high. The study design and choice task formats varied considerably, and a wide range of modelling methods were employed to estimate value sets.

CONCLUSIONS

This review of DCE methods used for developing value sets suggests some recurring limitations, areas of consensus and areas where further research is required. Methodological diversity means that the values should be seen as experimental, and users should understand the features of the value sets produced before applying them in decision making.

Does Inclusion of Interactions Result in Higher Precision of Estimated Health State Values?

BACKGROUND

Most preference-based instruments producing overall values for health states are devised on the simplifying assumption that the overall effect of distinct health-related quality of life domains (attributes) of the instrument equals the sum of the attributes. Nevertheless, health attributes are often inter-related and depend on each other.

OBJECTIVES

To investigate whether inclusion of second-order interactions in the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L) value function would result in better fit and lead to different health state values than a model with main effects only.

METHODS

Using an efficient design, 400 pairs of EQ-5D-3L health states were generated in a pairwise choice format. We analyzed responses of 4000 people from the general population using a conditional logit model, and we tested goodness of fit using pseudo R², Akaike information criterion, differences in log-likelihood, and likelihood ratio. We compared accuracies of models' predictions based on root mean square error and mean absolute error.

RESULTS

The interaction-effects model showed systematically lower values than the main-effects model. Inclusion of interactions resulted only in a slightly better model fit. Interactions comprising mobility and self-care were the most salient.

CONCLUSIONS

For the EQ-5D-3L, a value function based on interactions produces systematically lower values than a main-effects model, meaning that the effect of two or more health problems combined is stronger than the sum of the individual main effects.

Assessing utility values for treatment-related health states of acute myeloid leukemia in the United States

Background

Preference valuations of health status are essential in health technology and economic appraisal. This study estimated utilities for treatment-related health states of acute myeloid leukemia (AML) and disutilities of severe adverse events (SAEs) using a representative sample of adults from the general population in the United States (US).

Methods

Treatment-related AML health states, defined based on literature and interviews with clinicians, included complete remission (CR), no CR, relapse, stem cell transplant (SCT), and post SCT short-term recovery. Six attributes with varying levels, including fever, lack of energy, problems with daily function, anxiety/depression, blood transfusions, and hospitalization, were used to define health states. An online survey using discrete choice experiment methodology was designed to capture preferences for health status scenarios including the identified attributes and key grade 3/4 chemotherapy-related SAEs. Health state utilities and SAE disutilities were generated from a conditional logistic regression with generalized estimating equations.

Results

Of the 300 survey participants, the demographic distributions were within a 3% margin of those in the 2010 US Census. CR had the highest utility value (0.875), followed by post-SCT short-term recovery (0.398), relapse (0.355), no CR (0.262), and SCT (0.158). Of the SAEs, serious infection had the highest decline in utility (0.218), followed by severe diarrhea (0.176), abnormally low blood cell counts (0.100), and severe redness/skin peeling (0.060).

Conclusions

AML and treatments can result in reduced quality of life and impaired ability to perform daily activities. Findings of this study underline the value that society places on treatment-related AML health states and SAEs.

Advocating a Paradigm Shift in Health-State Valuations: The Estimation of Time-Preference Corrected QALY Tariffs

BACKGROUND

Despite evidence of nonproportional trade-offs in time trade-off exercises and the explicit incorporation of exponential discounting in health technology assessment calculations, quality-adjusted life-year (QALY) tariffs are currently still established under the assumption of linear time preferences.

OBJECTIVES

The aim of this study was to introduce a general method of accommodating for nonlinear time preferences in discrete choice experiment (DCE) duration studies and to evaluate its impact on estimated QALY tariffs.

METHODS

A parsimonious utility function is proposed that accommodates any discounting function and preserves linear time preferences as a special case. Based on an efficient DCE design and 1775 respondents from a nationally representative scientific household panel, preferences and QALY tariffs for the Dutch SF-6D were estimated while accommodating for nonlinear time preferences via exponential and hyperbolic discounting functions.

RESULTS

When the discount rate was estimated directly, we found strong evidence of nonlinear time preferences (with an exponential and hyperbolic discount rate of 5.7% and 16.5%, respectively). When the discount rate was estimated as a function of health state severity, we found that years lived in better health states are discounted minus years lived in impaired health states. Finally, the best statistical fit was obtained when using a hyperbolic discount function, which resulted in smaller QALY decrements and fewer health states classified as worse than immediate death.

CONCLUSIONS

Our results highlight the relevance and even necessity of a paradigm shift in health valuation studies in favor of time-preference corrected QALY tariffs, with potentially important implications for health technology assessment calculations and regulatory decisions.

Head-to-Head Comparison of EQ-5D-3L and EQ-5D-5L Health Values

BACKGROUND

The EQ-5D is a widely used preference-based instrument to measure health-related quality of life. Some methodological drawbacks of its three-level version (EQ-5D-3L) prompted development of a new format (EQ-5D-5L). There is no clear evidence that the new format outperforms the standard version.

OBJECTIVE

The objective of this study was to make a head-to-head comparison of the EQ-5D-3L and EQ-5D-5L in a discrete choice model setting giving special attention to the consistency and logical ordering of coefficients for the attribute levels and to the differences in health-state values.

METHODS

Using efficient designs, 240 pairs of EQ-5D-3L health states and 240 pairs of EQ-5D-5L health states were generated in a pairwise choice format. The study included 3698 Dutch general population respondents, analyzed their responses using a conditional logit model, and compared the values elicited by EQ-5D-3L and EQ-5D-5L for different health states.

RESULTS

No inconsistencies or illogical ordering of level coefficients were observed in either version. The proportion of severe health states with low values was higher in the EQ-5D-5L than in the EQ-5D-3L, and the proportion of mild/moderate states was lower in the EQ-5D-5L than in the EQ-5D-3L. Moreover, differences were observed in the relative weights of the attributes.

CONCLUSION

Overall distribution of health-state values derived from a large representative sample using the same measurement framework for both versions showed differences between the EQ-5D-3L and EQ-5D-5L. However, even small differences in the phrasing (language) of the descriptive system or in the valuation protocol can produce differences in values between these two versions.

Australian Utility Weights for the EORTC QLU-C10D, a Multi-Attribute Utility Instrument Derived from the Cancer-Specific Quality of Life Questionnaire, EORTC QLQ-C30

BACKGROUND

The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely used cancer-specific quality-of-life (QOL) questionnaire, EORTC QLQ-C30. The QLU-C10D contains ten dimensions (Physical, Role, Social and Emotional Functioning; Pain, Fatigue, Sleep, Appetite, Nausea, Bowel Problems), each with four levels. To be used in cost-utility analysis, country-specific valuation sets are required.

OBJECTIVE

The aim of this study was to provide Australian utility weights for the QLU-C10D.

METHODS

An Australian online panel was quota-sampled to ensure population representativeness by sex and age (≥ 18 years). Participants completed a discrete choice experiment (DCE) consisting of 16 choice-pairs. Each pair comprised two QLU-C10D health states plus life expectancy. Data were analysed using conditional logistic regression, parameterised to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each QOL dimension-level coefficient to the coefficient on life expectancy.

RESULTS

A total of 1979 panel members opted in, 1904 (96%) completed at least one choice-pair, and 1846 (93%) completed all 16 choice-pairs. Dimension weights were generally monotonic: poorer levels within each dimension were generally associated with greater utility decrements. The dimensions that impacted most on choice were, in order, Physical Functioning, Pain, Role Functioning and Emotional Functioning. Oncology-relevant dimensions with moderate impact were Nausea and Bowel Problems. Fatigue, Trouble Sleeping and Appetite had relatively small impact. The value of the worst health state was -0.096, somewhat worse than death.

CONCLUSIONS

This study provides the first country-specific value set for the QLU-C10D, which can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30, prospectively and retrospectively.

A Computer-Assisted Personal Interview App in Research Electronic Data Capture for Administering Time Trade-off Surveys (REDCap): Development and Pretest

Background

The time trade-off (TTO) task is a method of eliciting health utility scores, which range from 0 (equivalent to death) to 1 (equivalent to perfect health). These scores numerically represent a person’s health-related quality of life. Software apps exist to administer the TTO task; however, most of these apps are poorly documented and unavailable to researchers.

Objective

To fill the void, we developed an online app to administer the TTO task for a research study that is examining general public proxy health-related quality of life estimates for persons with Alzheimer’s disease. This manuscript describes the development and pretest of the app.

Methods

We used Research Electronic Data Capture (REDCap) to build the TTO app. The app’s modular structure and REDCap’s object-oriented environment facilitated development. After the TTO app was built, we recruited a purposive sample of 11 members of the general public to pretest its functionality and ease of use.

Results

Feedback from the pretest group was positive. Minor modifications included clarity enhancements, such as rearranging some paragraph text into bullet points, labeling the app to delineate different question sections, and revising or deleting text. We also added a research question to enable the identification of respondents who know someone with Alzheimer’s disease.

Conclusions

We developed an online app to administer the TTO task. Other researchers may access and customize the app for their own research purposes.

Using a Discrete-Choice Experiment Involving Cost to Value a Classification System Measuring the Quality-of-Life Impact of Self-Management for Diabetes

OBJECTIVES

To describe the use of a novel approach in health valuation of a discrete-choice experiment (DCE) including a cost attribute to value a recently developed classification system for measuring the quality-of-life impact (both health and treatment experience) of self-management for diabetes.

METHODS

A large online survey was conducted using DCE with cost on UK respondents from the general population (n = 1497) and individuals with diabetes (n = 405). The data were modeled using a conditional logit model with robust standard errors. The marginal rate of substitution was used to generate willingness-to-pay (WTP) estimates for every state defined by the classification system. Robustness of results was assessed by including interaction effects for household income.

RESULTS

There were some logical inconsistencies and insignificant coefficients for the milder levels of some attributes. There were some differences in the rank ordering of different attributes for the general population and diabetic patients. The WTP to avoid the most severe state was £1118.53 per month for the general population and £2356.02 per month for the diabetic patient population. The results were largely robust.

CONCLUSIONS

Health and self-management can be valued in a single classification system using DCE with cost. The marginal rate of substitution for key attributes can be used to inform cost-benefit analysis of self-management interventions in diabetes using results from clinical studies in which this new classification system has been applied. The method shows promise, but found large WTP estimates exceeding the cost levels used in the survey.

Comparing and transforming PROMIS utility values to the EQ-5D

PURPOSE

Summarizing patient-reported outcomes (PROs) on a quality-adjusted life year (QALY) scale is an essential component to any economic evaluation comparing alternative medical treatments. While multiple studies have compared PRO items and instruments based on their psychometric properties, no study has compared the preference-based summary of the EQ-5D-3L and Patient Reported Outcomes Measurement Information System (PROMIS-29) instruments. As part of this comparison, a major aim of this manuscript is to transform PROMIS-29 utility values to an EQ-5D-3L scale.

METHODS

A nationally representative survey of 2623 US adults completed the 29-item PROMIS health profile instrument (PROMIS-29) and the 3-level version of the EQ-5D instrument (EQ-5D-3L). Their responses were summarized on a health utility scale using published estimates. Using regression analysis, PROMIS-29 and EQ-5D-3L utility weights were compared with each other as well as with self-reported general health.

RESULTS

PROMIS-29 utility weights were much lower than the EQ-5D-3L weights. However, a correlation coefficient of 0.769 between the utility values of the two instruments suggests that the main discordance is simply a difference in scale between the measures. It is also possible to map PROMIS-29 utility weights onto an EQ-5D-3L scale. EQ-5D-3L losses equal .1784 × (PROMIS-29 Losses)^.7286.

CONCLUSIONS

The published estimates of the PROMIS-29 produce lower utility values than many other health instruments. Mapping the PROMIS-29 estimates to an EQ-5D-3L scale alleviates this issue and allows for a more straightforward comparison between the PROMIS-29 and other common health instruments.

A Review of Generic Preference-Based Measures for Use in Cost-Effectiveness Models

Generic preference-based measures (GPBMs) of health are used to obtain the quality adjustment weight required to calculate the quality-adjusted life year in health economic models. GPBMs have been developed to use across different interventions and medical conditions and typically consist of a self-complete patient questionnaire, a health state classification system, and preference weights for all states defined by the classification system. Of the six main GPBMs, the three most frequently used are the Health Utilities Index version 3, the EuroQol 5 dimensions (3 and 5 levels), and the Short Form 6 dimensions. There are considerable differences in GPBMs in terms of the content and size of descriptive systems (i.e. the numbers of dimensions of health and levels of severity within these), the methods of valuation [e.g. time trade-off (TTO), standard gamble (SG)], and the populations (e.g. general population, patients) used to value the health states within the descriptive systems. Although GPBMs are anchored at 1 (full health) and 0 (dead), they produce different health state utility values when completed by the same patient. Considerations when selecting a measure for use in a clinical trial include practicality, reliability, validity and responsiveness. Requirements of reimbursement agencies may impose additional restrictions on suitable measures for use in economic evaluations, such as the valuation technique (TTO, SG) or the source of values (general public vs. patients).

Is Best-Worst Scaling Suitable for Health State Valuation? A Comparison with Discrete Choice Experiments

Health utility indices (HUIs) are widely used in economic evaluation. The best-worst scaling (BWS) method is being used to value dimensions of HUIs. However, little is known about the properties of this method. This paper investigates the validity of the BWS method to develop HUI, comparing it to another ordinal valuation method, the discrete choice experiment (DCE). Using a parametric approach, we find a low level of concordance between the two methods, with evidence of preference reversals. BWS responses are subject to decision biases, with significant effects on individuals' preferences. Non parametric tests indicate that BWS data has lower stability, monotonicity and continuity compared to DCE data, suggesting that the BWS provides lower quality data. As a consequence, for both theoretical and technical reasons, practitioners should be cautious both about using the BWS method to measure health-related preferences, and using HUI based on BWS data. Given existing evidence, it seems that the DCE method is a better method, at least because its limitations (and measurement properties) have been extensively researched. Copyright © 2016 John Wiley & Sons, Ltd.

How Should Discrete Choice Experiments with Duration Choice Sets Be Presented for the Valuation of Health States?

BACKGROUND

Discrete Choice Experiments including duration (DCE_TTO) can be used to generate utility values for health states from measures such as EQ-5D-5L. However, methodological issues concerning the optimum way to present choice sets remain. The aim of the present study was to test a range of task presentation approaches designed to support the DCE_TTO completion process.

METHODS

Four separate presentation approaches were developed to examine different task features including dimension level highlighting, and health state severity and duration level presentation. Choice sets included 2 EQ-5D-5L states paired with 1 of 4 duration levels, and a third "immediate death" option. The same design, including 120 choice sets (developed using optimal methods), was employed across all approaches. The online survey was administered to a sample of the Australian population who completed 20 choice sets across 2 approaches. Conditional logit regression was used to assess model consistency, and scale parameter testing investigated poolability.

RESULTS

Overall 1,565 respondents completed the survey. Three approaches, using different dimension level highlighting techniques, produced mainly monotonic coefficients that resulted in a larger disutility as the severity level increased (excepting usual activities levels 2/3). The fourth approach, using a level indicator to present the severity levels, has slightly more non-monotonicity and produced larger ordered differences for the more severe dimension levels. Scale parameter testing suggested that the data cannot be pooled.

CONCLUSIONS

The results provide information regarding how to present DCE tasks for health state valuation. The findings improve our understanding of the impact of different presentation approaches on valuation, and how DCE questions could be presented to be amenable to completion. However, it is unclear if the task presentation impacts online respondent engagement.

Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L

PURPOSE

It has been argued that generic health-related quality of life measures are not sensitive to certain disease-specific improvements; condition-specific preference-based measures may offer a better alternative. This paper assesses the validity, responsiveness and sensitivity of a cancer-specific preference-based measure, the EORTC-8D, relative to the EQ-5D-3L.

METHODS

A longitudinal prospective population-based cancer genomic cohort, Cancer 2015, was utilised in the analysis. EQ-5D-3L and the EORTC QLQ-C30 (which gives EORTC-8D values) were asked at baseline (diagnosis) and at various follow-up points (3 months, 6 months, 12 months). Baseline values were assessed for convergent validity, ceiling effects, agreement and sensitivity. Quality-adjusted life-years (QALYs) were estimated and similarly assessed. Multivariate regression analyses were employed to understand the determinants of the difference in QALYs.

RESULTS

Complete case analysis of 1678 patients found that the EQ-5D-3L values at baseline were significantly lower than the EORTC-8D values (0.748 vs 0.829, p < 0.001). While the correlation between the instruments was high, agreement between the instruments was poor. The baseline health state values using both instruments were found to be sensitive to a number of patient and disease characteristics, and discrimination between disease states was found to be similar. Mean generic QALYs (estimated using the EQ-5D-3L) were significantly lower than condition-specific QALYs (estimated using the EORTC-8D) (0.860 vs 0.909, p < 0.001). The discriminatory power of both QALYs was similar.

CONCLUSIONS

When comparing a generic and condition-specific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated QALYs over time for cancer patients. The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably.

Is Dimension Order Important when Valuing Health States Using Discrete Choice Experiments Including Duration?

BACKGROUND

Discrete choice experiments with duration (DCE_TTO) can be used to estimate utility values for preference-based measures, such as the EQ-5D-5L. For self-completion, the health dimensions are presented in a standard order. However, for valuation, this may result in order effects. Thus, it is important to understand whether health state dimension ordering affects values. The aim of this study was to examine the importance of dimension ordering on DCE values using EQ-5D-5L.

METHODS

A choice experiment presenting two health profiles and a third immediate death option was developed. A three-arm study was used, with the same 120 choice sets presented online across each arm (n = 360 per arm). Arm 1 presented the standard EQ-5D-5L dimension order, arm 2 randomised order between respondents, and arm 3 randomised within respondents. Conditional logit regression was used to assess model consistency, and scale parameter testing was used to assess model poolability.

RESULTS

There were minor inconsistencies across each arm, but the magnitudes of the coefficients produced were generally consistent. Arm 3 produced the largest range of utility values (1 to -0.980). Scale parameter testing suggested that the models did not differ, and the data could be pooled. Follow-up questions did not suggest variation in terms of difficulty.

CONCLUSIONS

The results suggest that the level of randomisation used in DCE health state valuation studies does not significantly impact values, and dimension order may not be as important as other study design issues. The results support past valuation studies that use the standard order of dimensions.

A Health-Related Quality-of-Life Measure for Use in Patients with HIV: A Validation Study

In the United States, HIV has evolved from an acute disease to a chronic illness making health-related quality of life a pre-eminent goal for many persons living with HIV (PLWH). There have been a number of HIV-specific quality-of-life instruments developed, but little attention has been paid to the validation of standardized nondisease-specific quality-of-life instruments tailored to PLWH. The goal of this research was to validate the Patient-Reported Outcomes Measurement Information System (PROMIS)-29, a questionnaire that measures health-related quality of life in PLWH. A sample of 1306 PLWH completed an online anonymous survey assessing their symptom experience and health-related quality of life. A subsample of 209 participants completed another questionnaire 30 days later. The subscales of the PROMIS-29 showed high internal consistency reliability (range = 0.87–0.97). The PROMIS-29 detected differences in health-related quality of life in those persons who reported an AIDS diagnosis compared to those who did not report an AIDS diagnosis. The PROMIS-29 has demonstrated reliability, validity, and reproducibility for use in measuring health-related quality of life in PLWH.

Order of Presentation of Dimensions Does Not Systematically Bias Utility Weights from a Discrete Choice Experiment

BACKGROUND

Discrete choice experiments (DCEs) are increasingly used to value aspects of health. An issue with their adoption is that results may be sensitive to the order in which dimensions of health are presented in the valuation task. Findings in the literature regarding order effects are discordant at present.

OBJECTIVES

To quantify the magnitude of order effect of quality-of-life (QOL) dimensions within the context of a DCE designed to produce country-specific value sets for the EORTC Quality of Life Utility Measure-Core 10 dimensions (QLU-C10D), a new utility instrument derived from the widely used cancer-specific QOL questionnaire, the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30.

METHODS

The DCE comprised 960 choice sets, divided into 60 versions of 16 choice sets, with each respondent assigned to a version. Within each version, the order of QLU-C10D QOL dimensions was randomized, followed by life duration in the last position. The DCE was completed online by 2053 individuals in France and Germany. We analyzed the data with a series of conditional logit models, adjusted for repeated choices within respondent. We used F tests to assess order effects, correcting for multiple hypothesis testing.

RESULTS

Each F test failed to reject the null hypothesis of no position effect: 1) all QOL order positions considered jointly; 2) last QOL position only; 3) first QOL position only. Furthermore, the order coefficients were small relative to those of the QLU-C10D QOL dimension levels.

CONCLUSIONS

The order of presentation of QOL dimensions within a DCE designed to provide utility weights for the QLU-C10D had little effect on level coefficients of those QOL dimensions.

Using Discrete Choice Experiments with Duration to Model EQ-5D-5L Health State Preferences

Background: Discrete choice experiments incorporating duration can be used to derive health state values for EQ-5D-5L. Yet, methodological issues relating to the duration attribute and the optimal way to select health states remain. The aims of this study were to: test increasing the number of duration levels and choice sets where duration varies (aim 1); compare designs with zero and non-zero prior values (aim 2); and investigate a novel, two-stage design to incorporate prior values (aim 3). Methods: Informed by zero and non-zero prior values, two efficient designs were developed, each consisting of 120 EQ-5D-5L health profile pairs with one of six duration levels (aims 1 and 2). Another 120 health state pairs were selected, with one of six duration levels allocated in a second stage based on existing estimated utility of the states (aim 3). An online sample of 2,002 members of the UK general population completed 10 choice sets each. Differences across the regression coefficients from the three designs were assessed. Results: The zero prior value design produced a model with coefficients that were generally logically ordered, but the non-zero prior value design resulted in a set of less ordered coefficients where some differed significantly. The two-stage design resulted in ordered and significant coefficients. The non-zero prior value design may include more “difficult” choice sets, based on the proportions choosing each profile. Conclusions: There is some indication of compromised “respondent efficiency”, suggesting that the use of non-zero prior values will not necessarily result in better overall precision. It is feasible to design discrete choice experiments in two stages by allocating duration values to EQ-5D-5L health state pairs based on estimates from prior studies.

The Impact of Different DCE-Based Approaches When Anchoring Utility Scores

BACKGROUND

Discrete choice experiments (DCEs) have been proposed as a method to estimate utility weights for health states within utility instruments. However, the most appropriate method to anchor the utility values on the full health to dead quality-adjusted life year (QALY) scale remains uncertain. We test four approaches to anchoring in which dead is valued at zero and full health at one.

METHODS

We use data from two DCEs valuing EQ-5D-3L and EQ-5D-5L health states, which presented pairs of health profiles with an associated duration, and a dead option. The approaches to anchoring the results on the required scale were (1) using only preferences between non-dead health profiles; (2) including the dead data, treating it as a health profile with zero duration; (3) explicitly modelling both duration and dead; and (4) using the preferences regarding the dead health state as an external anchor subsequent to the estimation of approach 1.

RESULTS

All approaches lead to differences in the scale of utility decrements, but not the ranking of EQ-5D health states. The models differ in their ability to predict preferences around dead health states, and the characteristics of the value sets in terms of their range and the proportion of states valued as worse than dead.

DISCUSSION

Appropriate anchoring of DCEs with or without complementary time trade-off (TTO) data remains unresolved, and the method chosen will impact on health resource allocation decision making employing the value sets.

Comparison of Value Set Based on DCE and/or TTO Data: Scoring for EQ-5D-5L Health States in Japan

BACKGROUND

The valuation study of the five-level version of the EuroQol five-dimensional questionnaire (EQ-5D-5L) involved composite time trade-off (cTTO) and a discrete choice experiment (DCE). The DCE scores must be anchored to the quality-of-life scale from 0 (death) to 1 (full health). Nevertheless, the characteristics of the statistical methods used for converting the EQ-5D-5L DCE results by using TTO information are not yet clearly known.

OBJECTIVES

To present the Japanese DCE value set of the EQ-5D-5L and compare three methods for converting latent DCE values.

METHODS

The survey sampled the general population at five locations in Japan. 1098 respondents were stratified by age and sex. To obtain and compare the value sets of the EQ-5D-5L, the cTTO and DCE data were analyzed by a linear mixed model and conditional logit, respectively. The DCE scores were converted to the quality-of-life scale by anchoring to the worst state using cTTO, mapping DCE onto cTTO, and a hybrid model.

RESULTS

The data from 1026 respondents were analyzed. All the coefficients in the cTTO and DCE value sets were consistent throughout all the analyses. Compared with the cTTO algorithm, the mapping and hybrid methods yielded very similar scoring coefficients. The hybrid model results, however, produced a lower root mean square error and fewer health states with errors exceeding 0.05 than did the other models. The DCE anchored to the worst state overestimated the cTTO scores of almost all the health states.

CONCLUSIONS

Japanese value sets based on DCE were demonstrated. On comparing the observed cTTO scores, we found that the hybrid model was slightly superior to the simpler methods, including the TTO model.

Better outcomes for hospitalized patients with TIA when in stroke units: An observational study

OBJECTIVES

To investigate differences in management and outcomes for patients admitted to the hospital with TIA according to care on a stroke unit (SU) or alternate ward setting up to 180 days post event.

METHODS

TIA admissions from 40 hospitals participating in the Australian Stroke Clinical Registry during 2010-2013 were assessed. Propensity score matching was used to assess outcomes by treatment group including Cox proportional hazards regression to compare survival differences and other appropriate multivariable regression models for outcomes including health-related quality of life and readmissions.

RESULTS

Among 3,007 patients with TIA (mean age 73 years, 54% male), 1,110 pairs could be matched. Compared to management elsewhere in hospitals, management in an SU was associated with improved cumulative survival at 180 days post event (hazard ratio 0.57, 95% confidence interval 0.35-0.94; p = 0.029), despite not being statistically significant at 90 days (hazard ratio 0.66, 95% confidence interval 0.33-1.31; p = 0.237). Overall, there were no differences for being discharged on antihypertensive medication or with a care plan, and the 90- to 180-day self-reported outcomes between these groups were similar. In subgroup analyses of 461 matched pairs treated in hospitals in one Australian state (Queensland), patients treated in an SU were more often prescribed aspirin within 48 hours (73% vs 62%, p < 0.001) and discharged on antithrombotic medications (84% vs 71%, p < 0.001) than those not treated in an SU.

CONCLUSIONS

Hospitalized patients with TIA managed in SUs had better survival at 180 days than those treated in alternate wards, potentially through better management, but further research is needed.

Response Patterns in Health State Valuation Using Endogenous Attribute Attendance and Latent Class Analysis

Not accounting for simplifying decision-making heuristics when modelling data from discrete choice experiments has been shown potentially to lead to biased inferences. This study considers two ways of exploring the presence of attribute non-attendance (that is, respondents considering only a subset of the attributes that define the choice options) in a health state valuation discrete choice experiment. The methods used include the latent class (LC) and endogenous attribute attendance (EAA) models, which both required adjustment to reflect the structure of the quality-adjusted life year (QALY) framework for valuing health outcomes. We find that explicit consideration of attendance patterns substantially improves model fit. The impact of allowing for non-attendance on the estimated QALY weights is dependent on the assumed source of non-attendance. If non-attendance is interpreted as a form of preference heterogeneity, then the inferences from the LC and EAA models are similar to those from standard models, while if respondents ignore attributes to simplify the choice task, the QALY weights differ from those using the standard approach. Because the cause of non-attendance is unknown in the absence of additional data, a policymaker may use the range of weights implied by the two approaches to conduct a sensitivity analysis.

Using blocked fractional factorial designs to construct discrete choice experiments for healthcare studies

Discrete choice experiments (DCEs) are increasingly used for studying and quantifying subjects preferences in a wide variety of healthcare applications. They provide a rich source of data to assess real-life decision-making processes, which involve trade-offs between desirable characteristics pertaining to health and healthcare and identification of key attributes affecting healthcare. The choice of the design for a DCE is critical because it determines which attributes' effects and their interactions are identifiable. We apply blocked fractional factorial designs to construct DCEs and address some identification issues by utilizing the known structure of blocked fractional factorial designs. Our design techniques can be applied to several situations including DCEs where attributes have different number of levels. We demonstrate our design methodology using two healthcare studies to evaluate (i) asthma patients' preferences for symptom-based outcome measures and (ii) patient preference for breast screening services. Copyright © 2016 John Wiley & Sons, Ltd.

QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30

PURPOSE

To derive a health state classification system (HSCS) from the cancer-specific quality of life questionnaire, the EORTC QLQ-C30, as the basis for a multi-attribute utility instrument.

METHODS

The conceptual model for the HSCS was based on the established domain structure of the QLQ-C30. Several criteria were considered to select a subset of dimensions and items for the HSCS. Expert opinion and patient input informed a priori selection of key dimensions. Psychometric criteria were assessed via secondary analysis of a pooled dataset comprising HRQOL and clinical data from 2616 patients from eight countries and a range of primary cancer sites, disease stages, and treatments. We used confirmatory factor analysis (CFA) to assess the conceptual model's robustness and generalisability. We assessed item floor effects (>75 % observations at lowest score), disordered item response thresholds, coverage of the latent variable and differential item function using Rasch analysis. We calculated effect sizes for known group comparisons based on disease stage and responsiveness to change. Seventy-nine cancer patients assessed the relative importance of items within dimensions.

RESULTS

CFA supported the conceptual model and its generalisability across primary cancer sites. After considering all criteria, 12 items were selected representing 10 dimensions: physical functioning (mobility), role functioning, social functioning, emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems.

CONCLUSIONS

The HSCS created from QLQ-C30 items is known as the EORTC Quality of Life Utility Measure-Core 10 dimensions (QLU-C10D). The next phase of the QLU-C10D's development involves valuation studies, currently planned or being conducted across the globe.