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.

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.

The European Organisation for Research and Treatment of Cancer Quality of Life Utility-Core 10 Dimensions: Development and Investigation of General Population Utility Norms for Canada, France, Germany, Italy, Poland, and the United Kingdom.

OBJECTIVES: The European Organisation for Research and Treatment of Cancer Quality of Life Utility-Core 10 Dimensions (EORTC QLU-C10D) is a cancer-specific preference-based measure, providing health utilities for use in economic evaluations derived from the widely used health-related quality of life measure, EORTC QLQ-C30. Several EORTC QLU-C10D country-specific value sets are available. This article aimed to provide EORTC QLU-C10D general population utility norms for Canada, France, Germany, Italy, Poland, and the United Kingdom, to aid interpretability of obtained utilities in these countries. METHODS: Data were collected in aforementioned countries via a quota-sampled, cross-sectional online survey (n = 100/age-sex group; N = approximately 1000/country). Participants were asked to complete the EORTC QLQ-C30 and provide sociodemographic data. Country-specific utility norms were calculated using the respective country tariff on the country's EORTC QLQ-C30 data after weighting to achieve population representativeness for age and sex. Norm values are provided as means (SDs) by country, age, and sex groups. Tukey's multiple comparison test investigated mean differences among countries. The impact of country, age, and sex on utility values was investigated with a multiple linear regression model. RESULTS: Country-specific mean utilities range from 0.724 (United Kingdom) to 0.843 (Italy). Country-, sex-, and age-specific mean utilities range from 0.664 for 30- to 39-year-old male Canadians to 0.899 for > 70-year-old male Italians. Utilities were lower in females in 4 of 6 countries, and the impact of age differed among countries. Independent of the impact of age and sex, between-country differences were found (P ≤ .05). CONCLUSION: Results showed a varying impact of age and sex on EORTC QLU-C10D utilities and significant between-country differences. Using national utility norms and utility decrements is recommended.

Health state utility differed systematically in breast cancer patients between the EORTC QLU-C10D and the PROMIS Preference Score.

BACKGROUND AND OBJECTIVES: The EORTC Quality of Life Utility Core 10 Dimensions (QLU-C10D) and the Patient-Reported Outcome Measurement Information System Preference Score (PROPr) are new health state utility (HSU) scores for quality-adjusted life years in cost-effectiveness analyses. Both are expected to measure HSU more comprehensively than existing measures in cancer patients by including cancer-related health domains such as fatigue. The aim of this study is to compare both scores in a sample of breast cancer patients. METHODS: We collected QLU-C10D and PROPr from 291 patients 90 days after treatment in the outpatient clinic of the breast cancer center at Charité - University Medicine Berlin between June 2018 and April 2021. We assessed both scores' convergent and known-groups validity, agreement, and ceiling and floor effects. RESULTS: The mean QLU-C10D score [0.71, 95% confidence interval (CI) 0.69-0.74] and the mean PROPr score (0.43, 95% CI 0.41-0.46) differed systematically (0.28, 95% CI 0.27-0.30) and showed fair agreement (intraclass correlation coefficient 0.46, 95% CI 0.32-0.57). The Pearson correlation coefficient was 0.83 (95% CI 0.79-0.86). Both scores showed similar discrimination across known groups of age, treatment, cancer stage, marital status, and education. The QLU-C10D showed relevant ceiling effects. CONCLUSION: QLU-C10D and PROPr measure HSU differently as a result of different utility models. The choice between QLU-C10D and PROPr should be informed by context, population, disease, and treatment.

The EORTC QLU-C10D was more efficient in detecting clinical known group differences in myelodysplastic syndromes than the EQ-5D-3L.

BACKGROUND: The aim was to investigate the relative validity of the preference-based measure EORTC QLU-C10D in comparison with the EQ-5D-3L in myelodysplastic syndromes (MDS) patients. METHODS: We used data from an international multicentre, observational cohort study of MDS patients. Baseline EORTC QLU-C10D and EQ-5D-3L scores were used and index scores calculated for Italy, Australia, and the UK. Criterion validity was established by Spearman and intraclass correlations (ICC) and Bland-Altman plots. Construct validity was established by the instruments' ability to discriminate known groups, i.e. groups whose health status is expected to differ. RESULTS: We analyzed data from 619 MDS patients (61.1% male; median age 73.8 years). Correlations between theoretically corresponding domains were largely higher than between unrelated domains. ICCs and Bland-Altman plots indicated moderate to good criterion validity. Ceiling effects were lower for the QLU-C10D (4.7%) than for the EQ-5D-3L (22.6%). The EQ-5D-3L failed to discriminate known-groups in two and the QLU-C10D in one of the comparisons; the QLU-C10D's efficiency in doing so was higher in clinical known-groups. Results were comparable between the countries. CONCLUSIONS: The QLU-C10D may be suitable to generate health utilities for economic research in MDS. Responsiveness and minimal important differences need yet to be established.

EORTC QLU-C10D value sets for Austria, Italy, and Poland.

OBJECTIVE: To develop Austrian, Italian, and Polish general population value sets for the EORTC QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30, and to descriptively compare their index scores for distinct health states. METHODS: The QLU-C10D descriptive system comprises 10 health attributes and each can take on 4 levels. A standardised and pre-tested methodology has been applied for valuations including a web-based discrete choice experiment (DCE). It was administered in 1000 general population respondents per country recruited via online panels, aiming at representativeness for core socio-demographic variables. RESULTS: In all three countries, the attributes with the largest impact on utility were physical functioning, pain, and role functioning. Cancer-specific dimensions with the largest impact were nausea and fatigue or bowel problems. Utility values of the worst health state (i.e. severe problems on all 10 dimension) were -0.111 (Austria), 0.025 (Italy), and 0.048 (Poland). Country-specific utilities differed for a selection of health states across the continuum. Austrian utilities were systematically lower for moderately and severely impaired health states. CONCLUSION: QLU-C10D cancer-specific utilities can now be calculated in three more countries. Differences between countries indicate that careful consideration is required when using non-country-specific value sets in economic evaluations.

Assessing health-related quality of life in cancer survivors: factors impacting on EORTC QLU-C10D-derived utility values.

PURPOSE: To investigate the factors influencing EORTC QLQ-C30-derived EORTC QLU-C10D utility values across five cancer types (non-Hodgkin lymphoma, multiple myeloma, colorectal, thyroid, and prostate cancer) and a general population sample. METHODS: Data from the Dutch population-based patient-reported outcomes following initial treatment and long-term evaluation of survivorship (PROFILES) registry collected between 2009 and 2012 were used. EORTC QLQ-C30 data were used to estimate utility values by applying the EORTC QLU-C10D instrument using Australian utility weights. Regression analyses were conducted, within and across cancer type, to examine the factors influencing utility values, including patient- and cancer-specific factors, as well as the EORTC QLQ-C30 scale/item scores. RESULTS: The mean utility value for the total cancer sample was 0.791 (SD 0.201), significantly lower than that from the general population (0.865, SD 0.165). Multiple myeloma patients had the lowest utility value at 0.663 (SD 0.244). Physical functioning, pain and nausea and vomiting were the health-related quality of life (HRQoL) domains with the greatest impact on utility values; cognitive functioning and dyspnea had the lowest impact. Of the demographic and clinical factors, unemployment for reasons other than retirement, age older than 75 years, number of comorbidities, and experience of symptoms all had a statistically significant negative impact on utility values. CONCLUSIONS: This study is one of the first to apply the EORTC QLU-C10D to a heterogeneous group of cancer patients. Results can be used to more efficiently target care towards factors influencing HRQoL. Furthermore, it enhances our understanding of how the EORTC QLU-C10D performs across cancer types, supporting its use in cost-utility analyses.