Eva-Maria Gamper

The Quality of Life (QoL) Utility measure, QLU-C10D, is derived of the European Organisation for Research and Treatment of Cancer (EORTC) QoL Questionnaire, QLQ-C30. Based on the cancer-specific nature, the QLU-C10D is expected to be sensitive and responsive in lung cancer patients.This retrospective analysis used data from four international lung cancer multi-center trials (NCT00656136, NCT00949650, NCT01085136, NCT01523587). Clinical validity was assessed in comparison to a generic standard utility instrument, the EuroQoL Group´s EQ-5D-3L. Utilities of six country value sets (Australia, Canada, Italy, the Netherlands, Poland, UK) were calculated at baseline and end of treatment for both measures. Country value set pairs of both measures (k) were compared in terms of Relative Efficiency (RE) and difference in Effect Sizes (dES) in 1) sensitivity to detect differences between performance status groups and 2) responsiveness to changes at each trial sample. Analysis of the four trials (N1 = 496, N2 = 290, N3 = 202, N4 = 770) with the six country value sets of each utility measure showed ad 1) Sensitivity indices favored the QLU-C10D (k = 18, p ≤ 0.019; RE > 1.10; dES > 0.03), and ad 2) Responsiveness indices of changes within clinically known groups (k = 78), largely favored QLU-C10D (k = 74, p ≤ .024; RE > 1.01; dES > 0.02), in comparison with the generic utility instrument. In summary, 96% of the comparative indices favored the QLU-C10D. In summary, this study confirms the clinical validity of the QLU-C10D in lung cancer patients. The QLU-C10D produced homogenous results across six country value sets and detected differences/changes in alignment with clinical expectations. In most comparisons the QLU-C10D was more sensitive or responsive compared to the EQ-5D-3L.

Background The Quality of Life Utility – Core 10 Dimensions (QLU-C10D) is a disease-specific preference-based measure (PBM) designed to obtain health state utility values from patients with cancer. Previously, satisfactory psychometric properties were established from retrospective trial analyses using clinical anchors. This study aimed to validate the QLU-C10D against two generic PBMs in a prospective sample of Austrian and French patients with cancer using patient-reported anchors. Methods Patients completed the European Organisation of Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire – Core 30 (QLQ-C30), EQ-5D-5L and Short Form 36 (SF-36) at study baseline (any time during anti-cancer treatment) plus a follow-up assessment 3–6 months later. Sociodemographic and clinical characteristics were assessed. QLU-C10D and SF-6Dv2 utilities were calculated from QLQ-C30 and SF-36 data, respectively. German, French and UK value sets were applied for all three PBMs. Floor and ceiling effects were assessed. Known-group validity (independent t-test) and responsiveness (paired t-tests) were assessed respectively by ability to detect health status differences and changes over time according to patient-rated overall quality of life/health perception assessed by the QLQ-C30 Global Health Status scale, the EQ-5D-5L VAS and the SF-36 General Health scale. Results A total of 465 patients were included in the analysis. QLU-C10D index scores (intra-class correlation) and domains (Pearson) were correlated with EQ-5D-5L and Short-Form Six Dimensions (SF-6Dv2) conceptual counterparts. Correlation coefficients for the index scores of QLU-C10D and the generic PBMs ranged from 0.63 to 0.81. The QLU-C10D detected statistically significant differences between groups at baseline in 100% of tests performed (n = 27). For changes over time, QLU-C10D detected expected effects in 68% of cases (n = 29). In comparison with the generic PBMs, QLU-C10D detected differences and changes with a higher statistical efficiency in 76% of cases (77 of 102). Conclusions The QLU-C10D is a fit-for-purpose ready-to-use PBM to estimate health state utilities of patients with cancer. This study adds to evidence that QLU-C10D has appropriate psychometric properties and appears to have higher statistical efficiency than generic PBMs in cancer.

Purpose Hypoparathyroidism (HypoPT) is one of the most common complications of surgical treatment for thyroid cancer and afflicated patients often report symptoms or impairments in quality of life (QoL). We aimed to investigate differences in various QoL domains between thyroid cancer survivors with and without permanent hypoparathyroidism. Methods Thyroid cancer survivors with a minimum of 1.5 years post-diagnosis completed the EORTC core questionnaire (EORTC QLQ-C30) and the EORTC thyroid module (QLQ-THY34). Sociodemographic and clinical information were obtained from the patients themselves and their medical charts. Analysis of covariance was used to compare QoL between survivors with and without hypoparathyroidism (adjusting for age, gender, time since diagnosis, and comorbidity). Results Of the 126 participants, 21 (17%) were diagnosed with permanent HypoPT. There was no evidence of differences regarding any QoL domain between survivors due to hypoparathyroidism. The symptoms with the highest burden for both groups were fatigue (hypoPT: 24.9; non-hypoPT: 32.8; p = 0.151) and insomnia (hypoPT: 22.2; non-hypoPT: 30.8; p = 0.213). Thyroid cancer specific impairments were observed for joint pain (hypoPT: 28.6; non-hypoPT: 34.0; p = 0.480), worry about important others (hypoPT: 25.8; non-hypoPT: 27.9; p = 0.765), exhaustion (hypoPT: 23.8; non-hypoPT: 27.9; p = 0.482), and lacking social support (hypoPT: 36.5; no-hypoPT: 23.0; p = 0.070). Conclusion The present study appears to show that QoL in thyroid cancer survivors may be unrelated to hypoparathyroidism, further suggesting a more complex relationship between these two aspects.

Introduction: Many health economic evaluations rely on the validity of the utility measurement for health-related quality of life (HRQoL). While generic utility measures perform well in HRQoL assessments of many diseases and patient populations, appropriateness for cancer-specific disease burdens needs attention and condition-specific measures could be a viable option. This study assessed the clinical validity of the cancer-specific EORTC QLU-C10D, a utility scoring algorithm for the EORTC QLQ-C30, in patients with glioblastoma. We expect the EORTC QLU-C10D to be sensitive and responsive in glioblastoma patients. Furthermore, we compared its statistical efficiency with the generic utility measure EQ-5D-3L. Methods: We used data from a multi-center randomized controlled trial (NCT00689221) with patients from 146 study sites in 25 countries. Both, the QLQ-C30 and the EQ-5D-3L, had been administered at seven assessment points together. Utilities of both measures were calculated for four country value set (Australia, Canada, UK, USA). Ceiling effects, agreement (Bland–Altman plots (BA), intra-class correlation (ICC)), were calculated to analyze construct validity. Sensitivity to known-groups (performance status; global health) and responsiveness to changes (progressive vs. non-progressive; stable vs. improved or deteriorated HRQoL) were investigated for clinical validity. Relative Efficiency (RE) was calculated to compare statistical efficiency of both utility measures. Results: 435 patients were included at baseline and six subsequent time points (median timeframe 497 days). QLU-C10D country value set showed negligible ceiling effects (< 6.7%) and high agreement with EQ-5D-3L (ICC > 0.750). BA indicated that differences between both utility measures increased with deteriorating health states. While the QLU-C10D was more sensitive to global health groups (RE > 1.2), the EQ-5D-3L was more sensitive to performance status groups (RE < 0.7) than the other utility measure. Statistical efficiency to detect differences between change groups and within HRQoL deterioration group (RE > 1.4) favored QLU-C10D in 18 of 24 (75%) and 20 of 24 (83%) comparisons with the EQ-5D-3L respectively. Responsiveness to overall HRQoL change (RE > 3.4) also favored the QLU-C10D. Conclusion: Our results indicate that the QLU-C10D is a valid utility measure to assess HRQoL in patients with glioblastoma. This facilitates the investigation of HRQoL profiles and utilities in this patient population by administering a single questionnaire, the EORTC QLQ-C30. Efficiency analyses point to higher statistical power of the QLU-C10D compared to the EQ-5D-3L.

Background Cost-utility analysis generally requires valid preference-based measures (PBMs) to assess the utility of patient health. While generic PBMs are widely used, disease-specific PBMs may capture additional aspects of health relevant for certain patient populations. This study investigates the construct and concurrent criterion validity of the cancer-specific European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility-Core 10 dimensions (QLU-C10D) in non-small-cell lung cancer patients. Methods We retrospectively analysed data from four multicentre LUX-Lung trials, all of which had administered the EORTC Quality of Life Questionnaire (QLQ-C30) and the EQ-5D-3L. We applied six country-specific value sets (Australia, Canada, Italy, the Netherlands, Poland, and the United Kingdom) to both instruments. Criterion validity was assessed via correlations between the instruments’ utility scores. Correlations of divergent and convergent domains and Bland-Altman plots investigated construct validity. Floor and ceiling effects were assessed. Results The comparison of the EORTC QLU-C10D and EQ-5D-3L produced homogenous results for five of the six country tariffs. High correlations of utilities (r > 0.7) were found for all country tariffs except for the Netherlands. Moderate to high correlations of converging domain pairs (r from 0.472 to 0.718) were found with few exceptions, such as the Social Functioning–Usual Activities domain pair (max. r = 0.376). For all but the Dutch tariff, the EORTC QLU-C10D produced consistently lower utility values compared to the EQ-5D-3L (x̄ difference from − 0.082 to 0.033). Floor and ceiling effects were consistently lower for the EORTC QLU-C10D (max. 4.67% for utilities). Conclusions The six country tariffs showed good psychometric properties for the EORTC QLU-C10D in lung cancer patients. Criterion and construct validity was established. The QLU-C10D showed superior measurement precision towards the upper and lower end of the scale compared to the EQ-5D-3L, which is important when cost-utility analysis seeks to measure health change across the severity spectrum.

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.