Comparison of EQ-5D-3L with QLU-C10D in Metastatic Melanoma Using Cost-Utility Analysis

The EORTC QLU-C10D is a valid cancer-specific preference-based measure for cost-utility and health technology assessment in the Netherlands

BACKGROUND

Cost-utility analysis typically relies on preference-based measures (PBMs). While generic PBMs are widely used, disease-specific PBMs can capture aspects relevant for certain patient populations. Here the EORTC QLU-C10D, a cancer-specific PBM based on the QLQ-C30, is validated using Dutch trial data with the EQ-5D-3L as a generic comparator measure.

METHODS

We retrospectively analysed data from four Dutch randomised controlled trials (RCTs) comprising the EORTC QLQ-C30 and the EQ-5D-3L. Respective Dutch value sets were applied. Correlations between the instruments were calculated for domains and index scores. Bland-Altman plots and intra-class correlations (ICC) displayed agreement between the measures. Independent and paired t-tests, effect sizes and relative validity indices were used to determine the instruments' performance in detecting clinically known-group differences and health changes over time.

RESULTS

We analysed data from 602 cancer patients from four different trials. In overall, the EORTC QLU-C10D showed good relative validity with the EQ-5D-3L as a comparator (correlations of index scores r = 0.53-0.75, ICCs 0.686-0.808, conceptually similar domains showed higher correlations than dissimilar domains). Most importantly, it detected 63% of expected clinical group differences and 50% of changes over time in patients undergoing treatment. Both instruments showed poor performance in survivors. Detection rate and measurement efficiency were clearly higher for the QLU-C10D than for the EQ-5D-3L.

CONCLUSIONS

The Dutch EORTC QLU-C10D showed good comparative validity in patients undergoing treatment. Our results underline the benefit that can be achieved by using a cancer-specific PBM for generating health utilities for cancer patients from a measurement perspective.

Valuing quality of life for economic evaluations in cancer: navigating multiple methods

INTRODUCTION

Utility values offer a quantitative means to evaluate the impact of novel cancer treatments on patients' quality of life (QoL). However, the multiple methods available for valuing QoL present challenges in selecting the most appropriate method across different contexts.

AREAS COVERED

This review provides cancer clinicians and researchers with an overview of methods to value QoL for economic evaluations, including standalone and derived preference-based measures (PBMs) and direct preference elicitation methods. Recent developments are described, including the comparative performance of cancer-specific PBMs versus generic PBMs, measurement of outcomes beyond health-related QoL, and increased use of discrete choice experiments to elicit preferences. Recommendations and considerations are provided to guide the choice of method for cancer research.

EXPERT OPINION

We foresee continued adoption of the QLU-C10D and FACT-8D in cancer clinical trials given the extensive use of the EORTC QLQ-C30 and FACT-G in cancer research. While these cancer-specific PBMs offer the convenience of eliciting utility values without needing a standalone PBM, researchers should consider potential limitations if they intend to substitute them for generic PBMs. As the field advances, there is a greater need for consensus on the approach to selection and integration of various methods in cancer clinical trials.

The Cancer-Specific Health Economic Measure QLU-C10D is Valid and Responsive for Assessing Health Utility in Patients with Thyroid Cancer

Background: Health economic appraisals often rely on the assessment of health utilities using preference-based measures (PBM). The cancer-specific PBM, European Organisation for Research and Treatment of Cancer Quality of Life Utility - Core 10 Dimensions (EORTC QLU-C10D), was developed recently, and now needs to be validated in various clinical populations. Methods: In a multicenter, multinational prospective cohort study, we longitudinally collected EORTC QLQ-C30 and EQ-5D-5L data from patients with thyroid cancer. We applied seven country-specific value sets to the QLQ-C30 data to derive country-specific utility values and used the EQ-5D-5L as a comparator PBM. Criterion validity was assessed by correlating index scores and Bland-Altman plots. Construct validity was investigated by correlating domain scores. Known-group comparisons and responsiveness were assessed using external clinical criteria. Results: A total of 181 patients with thyroid cancer from nine countries (three continents) provided analyzable data. Patients were included if they had differentiated, medullary, or anaplastic thyroid cancer. Mean utility values of both instruments were generally lower compared to general population norms. No floor or ceiling effects were present for the QLU-C10D. The intra-class correlation for EQ-5D-5L and QLU-C10D index values ranged from 0.761 to 0.901 across the measurement timepoints, supporting criterion validity. Spearman's correlation coefficients ranged from 0.289 to 0.716 for theoretically corresponding domain pairs. The QLU-C10D detected differences in 9 of 15 known-group comparisons, supporting sensitivity. Clinically important changes were detected by all QLU-C10D country specific value sets, supporting responsiveness. Further, the QLU-C10D had higher statistical efficiency than the EQ-5D-5L in 74.7% of comparisons. Conclusions: The QLU-C10D is a valid PBM for health economic evaluations in thyroid cancer studies. We recommend its use to estimate health utilities in economic evaluations of thyroid cancer therapies.

Calculating ex-ante Utilities From the Neck Disability Index Score: Quantifying the Value of Care For Cervical Spine Pathology

STUDY DESIGN

General population utility valuation study.

OBJECTIVE

To develop a technique for calculating utilities from the Neck Disability Index (NDI) score.

METHODS

We recruited a sample of 1200 adults from a market research panel. Using an online discrete choice experiment (DCE), participants rated 10 choice sets based on NDI health states. A multi-attribute utility function was estimated using a mixed multinomial-logit regression model (MIXL). The sample was partitioned into a training set used for model fitting and validation set used for model evaluation.

RESULTS

The regression model demonstrated good predictive performance on the validation set with an AUC of .77 (95% CI: .76-.78). The regression model was used to develop a utility scoring rubric for the NDI. Regression results also revealed that participants did not regard all NDI items as equally important. The rank order of importance was (in decreasing order): pain intensity = work; personal care = headache; concentration = sleeping; driving; recreation; lifting; and lastly reading.

CONCLUSIONS

This study provides a simple technique for converting the NDI score to utilities and quantify the relative importance of individual NDI items. The ability to evaluate quality-adjusted life-years using these utilities for cervical spine pain and disability could facilitate economic analysis and aid in allocation of healthcare resources.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Comparison of EQ-5D-5L and EORTC QLU-C10D utilities in gastric cancer patients

BACKGROUND

To compare measurement properties of the utility scores derived from various country-specific value sets of EQ-5D-5L (5L) and EORTC QLU-C10D (10D) in gastric cancer patient.

METHODS

The study used cross-sectional data of 243 Chinese gastric cancer patients who completed both 5L and EORTC QLQ-C30. Utility score of QLU-C10D is generated from all the available QLU-C10D value sets currently; the score of 5L is derived from the corresponding 5L value sets for the countries with both the 5L and QLU-C10D value sets and the Chinese 5L value set. Convergent validity was evaluated by testing their correlations with the VAS score. Known-group validity was assessed by comparing the utility scores the patients with different severities. Their relative efficiency (RE) was also compared.

RESULTS

Correlation coefficient of 5L and QLU-C10D utility scores with VAS ranged from 0.54 to 0.59, and 0.55 to 0.63, respectively. Both the utility scores were in general able to discriminate the patients with different severities; and 5L utility score had higher RE in the majority of known-groups.

CONCLUSION

EQ-5D-5L and QLU-C10D utility scores were different and, thus, non-swappable. They possess similar convergent validity and known-group validity; while EQ-5D-5L scores may have better discriminative power.

Calculating Ex-ante Utilities From the Modified Japanese Orthopedic Association Score: A Prerequisite for Quantifying the Value of Care for Cervical Myelopathy

STUDY DESIGN

General population utility valuation study.

OBJECTIVE

The aim of this study was to develop a technique for calculating utilities from the modified Japanese Orthopedic Association (mJOA) Score.

SUMMARY OF BACKGROUND DATA

The ability to calculate quality-adjusted life-years (QALYs) for degenerative cervical myelopathy (DCM) would enhance treatment decision making and facilitate economic analysis. QALYs are calculated using utilities.

METHODS

We recruited a sample of 760 adults from a market research panel. Using an online discrete choice experiment, participants rated eight choice sets based on mJOA health states. A multiattribute utility function was estimated using a mixed multinomial-logit regression model. The sample was partitioned into a training set used for model fitting and validation set used for model evaluation.

RESULTS

The regression model demonstrated good predictive performance on the validation set with an area under the curve of 0.81 (95% confidence interval: 0.80-0.82)). The regression model was used to develop a utility scoring rubric for the mJOA. Regression results revealed that participants did not regard all mJOA domains as equally important. The rank order of importance was (in decreasing order): lower extremity motor function, upper extremity motor function, sphincter dysfunction, upper extremity sensation.

CONCLUSION

This study provides a simple technique for converting the mJOA score to utilities and quantify the importance of mJOA domains. The ability to evaluate QALYs for DCM will facilitate economic analysis and patient counseling. Clinicians should heed these findings and offer treatments that maximize function in the attributes viewed most important by patients.Level of Evidence: 3.