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

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.

An empirical comparison of the OPQoL-Brief, EQ-5D-3 L and ASCOT in a community dwelling population of older people

Background

This study examined the relationships between a newly developed older person-specific non-preference-based quality of life (QoL) instrument (Older People’s Quality of Life brief questionnaire (OPQoL-brief)) and two generic preference-based instruments (the EQ-5D-3L Level (EQ-5D-3 L) and the Adult Social Care Outcomes Toolkit (ASCOT) in a community-dwelling population of Australian older people receiving aged care services.

Methods

We formulated hypotheses about the convergent validity between the instruments (examined by Wilcoxon-Mann Whitney, Kruskal Wallis and Spearman’s correlation tests) and levels of agreement (assessed using intra class correlation (ICC) and modified Bland-Altman plots based on normalized Z EQ-5D-3 L and ASCOT utilities and OPQoL-Brief summary scores).

Results

The utilities/summary scores for 87 participants (aged 65–93 years) were moderately but positively correlated. Moderate convergent validity was evident for a number of instrument dimensions with the strongest relationship (r = 0.57) between ‘enjoy life’ (OPQoL-Brief) and ‘social contact’ (ASCOT). The overall ICC was 0.54 and Bland-Altman scatter plots showed 3–6 % of normalized Z-scores were outside the 95 % limits of agreement suggesting moderate agreement between all three instruments (agreement highest between the OPQoL-Brief and the ASCOT).

Conclusions

Our results suggest that the OPQoL-Brief, the ASCOT and the EQ-5D_3L are suitable for measuring quality of life outcomes in community-dwelling populations of older people. Given the different constructs underpinning these instruments, we recommend that choice of instrument should be guided by the context in which the instruments are being applied. Currently, the OPQoL-Brief is not suitable for use in cost-utility analyses as it is not preference-based. Given their different perspectives, we recommend that both the ASCOT and the EQ-5D are applied simultaneously to capture broader aspects of quality of life and health status within cost-utility analyses within the aged care sector. Future research directed towards the development of a new single preference-based instrument that incorporates both health status and broader aspects of quality of life within quality adjusted life year calculations for older people would be beneficial.

Using a discrete choice experiment to value the QLU-C10D: feasibility and sensitivity to presentation format

PURPOSE

To assess the feasibility of using a discrete choice experiment (DCE) to value health states within the QLU-C10D, a utility instrument derived from the QLQ-C30, and to assess clarity, difficulty, and respondent preference between two presentation formats.

METHODS

We ran a DCE valuation task in an online panel (N = 430). Respondents answered 16 choice pairs; in half of these, differences between dimensions were highlighted, and in the remainder, common dimensions were described in text and differing attributes were tabulated. To simplify the cognitive task, only four of the QLU-C10D's ten dimensions differed per choice set. We assessed difficulty and clarity of the valuation task with Likert-type scales, and respondents were asked which format they preferred. We analysed the DCE data by format with a conditional logit model and used Chi-squared tests to compare other responses by format. Semi-structured telephone interviews (N = 8) explored respondents' cognitive approaches to the valuation task.

RESULTS

Four hundred and forty-nine individuals were recruited, 430 completed at least one choice set, and 422/449 (94 %) completed all 16 choice sets. Interviews revealed that respondents found ten domains difficult but manageable, many adopting simplifying heuristics. Results for clarity and difficulty were identical between formats, but the "highlight" format was preferred by 68 % of respondents. Conditional logit parameter estimates were monotonic within domains, suggesting respondents were able to complete the DCE sensibly, yielding valid results.

CONCLUSION

A DCE valuation task in which only four of the QLU-C10D's ten dimensions differed in any choice set is feasible for deriving utility weights for the QLU-C10D.

US valuation of health outcomes measured using the PROMIS-29

OBJECTIVES

Health valuation studies enhance economic evaluations of treatments by estimating the value of health-related quality of life (HRQOL). The Patient-Reported Outcomes Measurement Information System (PROMIS) includes a 29-item short-form HRQOL measure, the PROMIS-29.

METHODS

To value PROMIS-29 responses on a quality-adjusted life-year scale, we conducted a national survey (N = 7557) using quota sampling based on the US 2010 Census. Based on 541 paired comparisons with over 350 responses each, pair-specific probabilities were incorporated into a weighted least-squared estimator.

RESULTS

All losses in HRQOL influenced choice; however, respondents valued losses in physical function, anxiety, depression, sleep, and pain more than those in fatigue and social functioning.

CONCLUSIONS

This article introduces a novel approach to valuing HRQOL for economic evaluations using paired comparisons and provides a tool to translate PROMIS-29 responses into quality-adjusted life-years.

Development of an EORTC-8D utility algorithm for Sri Lanka

BACKGROUND

Currently there are no reported cancer-specific health state valuations in low- and middle-income countries using a validated preference-based measure. The EORTC-8D, a cancer-specific preference-based measure, has 81,920 health states and is useful for economic evaluations in cancer care. The aim of this study was to develop a utility algorithm to value EORTC-8D health states using preferences derived from a representative population sample in Sri Lanka.

METHODS

The time-tradeoff method was used to elicit preferences from a general population sample of 780 in Sri Lanka. A block design of 85 health states, with a time horizon of 10 years, was used for the direct valuation. Data were analyzed using generalized least squares with random effects. All respondents with at least one logical inconsistency were excluded from the analysis.

RESULTS

After logical inconsistencies were excluded, 4520 observations were available from 717 respondents for the analysis. The preferred model specified main effects with an interaction term for any level 4 or worse descriptor within a health state. Worsening of physical functioning had a substantially greater utility decrement than any other dimension in this population. Limitations are that the data collection could not include the whole country and that females formed a large part of the sample.

CONCLUSIONS

Preference weights for EORTC-8D health states for Sri Lanka have been derived: These will be very useful in economic evaluations of cancer-related interventions in a range of low- and middle-income countries.

Estimating health state utility values from discrete choice experiments--a QALY space model approach

Using discrete choice experiments (DCEs) to estimate health state utility values has become an important alternative to the conventional methods of Time Trade-Off and Standard Gamble. Studies using DCEs have typically used the conditional logit to estimate the underlying utility function. The conditional logit is known for several limitations. In this paper, we propose two types of models based on the mixed logit: one using preference space and the other using quality-adjusted life year (QALY) space, a concept adapted from the willingness-to-pay literature. These methods are applied to a dataset collected using the EQ-5D. The results showcase the advantages of using QALY space and demonstrate that the preferred QALY space model provides lower estimates of the utility values than the conditional logit, with the divergence increasing with worsening health states.

The better than dead method: feasibility and interpretation of a valuation study

BACKGROUND

Traditionally, the valuation of health states worse than being dead suffers from two problems: [1] the use of different elicitation methods for positive and negative values, necessitating arbitrary transformations to map negative to positive values; and [2] the inability to quantify that values are time dependent. The Better than Dead (BTD) method is a health-state valuation method where states with a certain duration are compared with being dead. It has the potential to overcome these problems.

OBJECTIVES

To test the feasibility of the BTD method to estimate values for the EQ-5D system.

METHODS

A representative sample of 291 Dutch respondents (aged 18-45 years) was recruited. In a web-based questionnaire, preferences were elicited for a selection of 50 different health states with six durations between 1 and 40 years. Random-effects models were used to estimate the effects of socio-demographic and experimental variables, and to estimate values for the EQ-5D. Test-retest reliability was assessed in 41 respondents.

RESULTS

Important determinants for BTD were a religious life stance [odds ratio 4.09 (2.00-8.36)] and the educational level. The fastest respondents more often preferred health-state scenarios to being dead and had lower test-retest reliability (0.45 versus 0.77 and 0.84 for fast, medium and slow response times, respectively). The results showed a small number of so-called maximal endurable time states.

CONCLUSION

Valuating health states using the BTD method is feasible and reliable. Further research should explore how the experimental setting modifies how values depend on time.

Testing a discrete choice experiment including duration to value health states for large descriptive systems: addressing design and sampling issues

There is interest in the use of discrete choice experiments that include a duration attribute (DCETTO) to generate health utility values, but questions remain on its feasibility in large health state descriptive systems. This study examines the stability of DCETTO to estimate health utility values from the five-level EQ-5D, an instrument with depicts 3125 different health states. Between January and March 2011, we administered 120 DCETTO tasks based on the five-level EQ-5D to a total of 1799 respondents in the UK (each completed 15 DCETTO tasks on-line). We compared models across different sample sizes and different total numbers of observations. We found the DCETTO coefficients were generally consistent, with high agreement between individual ordinal preferences and aggregate cardinal values. Keeping the DCE design and the total number of observations fixed, subsamples consisting of 10 tasks per respondent with an intermediate sized sample, and 15 tasks with a smaller sample provide similar results in comparison to the whole sample model. In conclusion, we find that the DCETTO is a feasible method for developing values for larger descriptive systems such as EQ-5D-5L, and find evidence supporting important design features for future valuation studies that use the DCETTO.

Study protocol for valuing EQ-5D-3L and EORTC-8D health states in a representative population sample in Sri Lanka

BACKGROUND

Economic evaluations to inform decisions about allocation of health resources are scarce in Low and Middle Income Countries, including in Sri Lanka. This is in part due to a lack of country-specific utility weights, which are necessary to derive appropriate Quality Adjusted Life Years. The EQ-5D-3 L, a generic multi-attribute instrument (MAUI), is most widely used to measure and value health states in high income countries; nevertheless, the sensitivity of generic MAUIs has been criticised in some conditions such as cancer. This article describes a protocol to produce both a generic EQ-5D-3 L and cancer specific EORTC-8D utility index in Sri Lanka.

METHOD

EQ-5D-3 L and EORTC-8D health states will be valued using the Time Trade-Off technique, by a representative population sample (n = 780 invited) identified using stratified multi-stage cluster sampling with probability proportionate to size method. Households will be randomly selected within 30 clusters across four districts; one adult (≥ 18 years) within each household will be selected using the Kish grid method.Data will be collected via face-to-face interview, with a Time Trade-Off board employed as a visual aid. Of the 243 EQ-5D-3 L and 81,290 EORTC-8D health states, 196 and 84 respectively will be directly valued. In EQ-5D-3 L, all health states that combine level 3 on mobility with either level 1 on usual activities or self-care were excluded. Each participant will first complete the EQ-5D-3 L, rank and value 14 EQ-5D-3 L states (plus the worst health state and "immediate death"), and then rank and value seven EORTC-8D states (plus "immediate death"). Participant demographic and health characteristics will be also collected.Regression models will be fitted to estimate utility indices for EQ-5D-3 L and EORTC-8D health states for Sri Lanka. The dependent variable will be the utility value. Different specifications of independent variables will be derived from the ordinal EQ-5D-3 L to test for the best-fitting model.

DISCUSSION

In Sri Lanka, a LMIC health state valuation will have to be carried out using face to face interview instead of online methods. The proposed study will provide the first country-specific health state valuations for Sri Lanka, and one of the first valuations to be completed in a South Asian Country.