German value sets for the EORTC QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30

Cancer-specific utility instrument for health economic evaluations: A synopsis of the EORTC QLU-C10D user manual and current validity evidence

The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility - Core 10 Dimensions (QLU-C10D) adds a preference-based scoring algorithm to the EORTC measurement portfolio. It is built on the most widely used health-related quality of life (HRQoL) measure in oncology, the EORTC Quality of Life Questionnaire - Core 30 (QLQ-C30), allowing for the calculation of both HRQoL profiles and health utilities. This is an important advancement for integrating cancer-specific values into health economic evaluations and decision making, offering greater content validity and statistical power than some generic measures. This article presents an outline of the EORTC QLU-C10D User Manual to inform health-technology bodies, academic researchers, and industry, on the why and how of using this instrument for utility measurement. It covers basic concepts, proper use of the tool, including administration and scoring. Further, we summarise the presently published valuation studies, country-specific value sets, and body of evidence about psychometric properties. Current methodological questions are discussed, including mapping between utility measures and adaptions of generic measures for use in cancer populations. Taking into account empirical studies on psychometric properties, like content and construct validity, and comparisons with generic measures, we argue that the QLU-C10D is a reliable and valid instrument for cancer populations. Without imposing additional patient and administrative burden it has the potential to support health economic decisions in cancer by providing high-quality cancer-specific utility scores, to complement the more detailed HRQoL information from the QLQ-C30.

Norwegian and Swedish value sets for the EORTC QLU-C10D utility instrument

PURPOSE

This study aimed to develop utility weights for the European Organization for Research and Treatment of Cancer (EORTC) QLU-C10D, a cancer-specific utility instrument, tailored to the Norwegian and Swedish populations. The utility weights are intended for use in the specific welfare contexts of Norway and Sweden to support more precise healthcare decision-making in cancer treatment and care.

METHODS

This cross-sectional study included 1019 Norwegian and 1048 Swedish participants representative in age and gender of the two general populations. Participants completed a discrete choice experiment involving 960 choice sets, each consisting of two EORTC QLU-C10D health states described by the instrument's domains and the duration of each state. Utility weights were calculated using generalized estimation equation models, and non-monotonic levels were merged to ensure consistent valuation.

RESULTS

In the Norwegian participants, the largest utility decrements were seen for the domain of physical functioning (decrement of - 0.263 for highest level "very much"), followed by pain (decrement - 0.205 for level "very much") and role functioning (- 0.139). Among the cancer-specific domains, nausea had the largest utility decrement (- 0.124). In the Swedish participants, the largest utility decrements were also observed for physical functioning (- 0.207 for the response "very much"), followed by pain (- 0.139), role functioning (- 0.133), and nausea (- 0.119). Emotional functioning also exhibited a sizable utility decrement (- 0.115).

CONCLUSION

This study provides the first set of utility weights for the EORTC QLU-C10D specific to Norway and Sweden, reflecting the unique health preferences of these populations. The generated utility decrements can inform cost-utility analyses and optimize resource allocation in cancer care within the Norwegian and Swedish healthcare systems.

The EORTC QLU-C10D distinguished better between cancer patients and the general population than PROPr and EQ-5D-5L in a cross-sectional study

OBJECTIVES

Health state utility (HSU) instruments for calculating quality-adjusted life years, such as the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility - Core 10 Dimensions (QLU-C10D), derived from the EORTC QLQ-30 questionnaire, the Patient-Reported Outcome Measurement Information System (PROMIS) preference score (PROPr), and the EuroQoL-5-Dimensions-5-Levels (EQ-5D-5L), yield different HSU values due to different modeling and different underlying descriptive scales. For example the QLU-C10D includes cancer-relevant dimensions such as nausea. This study aimed to investigate how these differences in descriptive scales contribute to differences in HSU scores by comparing scores of cancer patients receiving chemotherapy to those of the general population.

STUDY DESIGN AND SETTING

EORTC QLU-C10D, PROPr, and EQ-5D-5L scores were obtained for a convenience sample of 484 outpatients of the Department of Oncology, Charité - Universitätsmedizin Berlin, Germany. Convergent and known group's validity were assessed using Pearson's correlation and intraclass correlation coefficients (ICC). We assessed each descriptive dimension score's discriminatory power and compared them to those of the general population (n > 1000) using effect size (ES; Cohen's d) and area under the curve (AUC).

RESULTS

The mean scores of QLU-C10D (0.64; 95% CI 0.62-0.67), PROPr (0.38; 95% CI 0.36-0.40), and EQ-5D-5L (0.72; 95% CI 0.70-0.75) differed significantly, irrespective of sociodemographic factors, condition, or treatment. Conceptually similar descriptive scores as obtained from the HSU instruments showed varying degrees of discrimination in terms of ES and AUC between patients and the general population. The QLU-C10D and its dimensions showed the largest ES and AUC.

CONCLUSION

The QLU-C10D and its domains distinguished best between health states of the two populations, compared to the PROPr and EQ-5D-5L. As the EORTC Core Quality of Life Questionnaire (QLQ-C30) is widely used in clinical practice, its data are available for economic evaluation.

PLAIN LANGUAGE SUMMARY

The assessment of dimensions of health-related quality of life (HRQoL), such as physical functioning or depression, is important to cancer patients and physicians for treatment and side effect monitoring. Descriptive HRQoL is measured by patient-reported outcomes measures (PROM). The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 questionnaire and the Patient-Reported Outcome Measurement Information System (PROMIS) are the most common PROM in the clinical HRQoL assessment. In recent years, multidimensional preference-based HRQoL measures were developed using these PROM as dimensions. These preference-based measures, also referred to as health state utility (HSU) scores, are needed for economic evaluations of treatments. The QLQ-C30's corresponding HSU score is the Quality of Life Utility measure-Core 10 Dimensions (QLU-C10D), and PROMIS' HSU score is the PROMIS preference score (PROPr). Both new HSU scores are frequently compared to the well-established EuroQoL-5-dimensions-5-levels (EQ-5D-5L). They all conceptualize HSU differently, as they assess different dimensions of HRQoL und use different models. Both the QLU-C10D and the PROPr have thus shown systematic differences to the EQ-5D-5L but these were largely consistent across the subgroups. Convergent and known groups validity can therefore be considered established. However, as HSU is a multidimensional construct, it remains unclear how differences in its dimensions, for example, its descriptive scales, contribute to differences in HSU scores. This is of importance as it is the descriptive scales that measure clinical HRQoL. We investigated this question by assessing each dimension's ability to distinguish between a sample of 484 cancer patients and the German general population. We could show that the ability to distinguish depended on the domain: for example, for depression, the QLU-C10D and EQ-5D-5L distinguished clearer, while for physical function, PROMIS did. Overall, the QLU-C10D and its dimensions distinguish best between cancer patients and general population.

Valuation of the EORTC Quality of Life Utility Core 10 Dimensions (QLU-C10D) in a Multi-ethnic Asian Setting: How Does Having Cancer Matter?

OBJECTIVES

The aim of the study was to develop and compare utility value sets for the EORTC QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30, using the preferences of the general public and cancer patients in Singapore, and to assess their measurement properties.

METHODS

A total of 600 individuals from the general public were recruited using a multi-stage random sampling, along with 626 cancer patients with clinically confirmed diagnoses from outpatient clinics of the largest tertiary cancer hospital. Each participant valued 16 pairs of EORTC QLU-C10D health states using a discrete choice experiment (DCE). Conditional logit models were used to analyze the DCE responses of the general public and cancer patients separately. Utility values were assessed for known-group validity and responsiveness in the cancer patients by comparing mean values across subgroups of patients and calculating standardized response means using longitudinal EORTC QLQ-C30 data, respectively.

RESULTS

Physical functioning and pain had the most impact on utility for both cancer patients and general public groups. Worst health state utility values were -0.821 and -0.463 for the general public and cancer patients, respectively. Cancer patients' values were lower for mild-to-moderate health states but higher for moderately-to-highly impaired states compared with the general public's values. Both value sets discriminated between patients with differing characteristics and responded equally well to improved health status, but the cancer patients' value set was slightly more responsive to deteriorated health.

CONCLUSIONS

EORTC QLU-C10D value sets based on the preferences of the Singaporean general public and cancer patients exhibited differences in values but similar psychometric properties.

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.

Chinese utility weights for the EORTC cancer-specific utility instrument QLU-C10D

OBJECTIVE

The aim of this study is to provide Chinese utility weights for the European Organization for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions (EORTC QLU-C10D) which is a preference-based cancer-specific utility instrument derived from the EORTC QLQ-C30.

METHODS

We conducted an online survey of the general population in China, with quota sampling for age and gender. Each respondent was asked to complete a discrete choice experimental survey consisting of 16 randomly selected choice sets. The conditional logit model and mixed logit model were used to analyze respondents' preferences, and the goodness of fit of the model was tested.

RESULTS

A total of 2003 respondents were included in the analysis. Utility decrements within dimensions were typically monotonic. Monotonic inconsistency issues in the Fatigue, Sleep, and Nausea dimensions were normalized by monotonicity correction. Physical functioning, Pain, and Role functioning were associated with the greatest utility weights, with the smallest decrements being in Bowel problems and Emotional functioning. The utility value for the worst health state was 0.083, i.e. slightly higher than being dead.

CONCLUSIONS

This study provides the first China-specific set of value for the QLU-C10D based on societal preferences of the Chinese adult general population. The value set can be used as a cancer-specific scoring system for economic evaluations of new oncology therapies and technologies in China.

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.

A comparison of measurement properties between EORTC QLU-C10D and FACT-8D in patients with hematological malignances

OBJECTIVE

To perform a comparison of the measurement properties of two cancer-specific Multi-Attribute Utility Instruments (MAUIs), EORTC QLU-C10D and FACT-8D, in Chinese patients with hematologic malignancies (HM).

METHODS

We conducted a longitudinal study on patients with HM in China, using QLU-C10D and FACT-8D at baseline and follow-up (3-4 months from baseline). We assessed: (i) convergent validity using Spearman's rank correlation test (r) with EQ-5D-5L; (ii) clinical-groups validity by differentiating cancer stages, overall health assessment (OHA), Eastern Cancer Oncology Group (ECOG) performance status, and mental health status. We also examined clinical validity with effect size (ES) and relative efficiency (RE); (iii) responsiveness to changes in patient self-perception using receiver operating characteristics (ROC) curves and area under the curves (AUC); and (iv) agreement using intraclass correlation coefficients (ICC) and visualized with Bland-Altman plot.

RESULTS

Among the 308 patients with HM at baseline, 131 completed the follow-up survey. Agreement between the two measures was high (ICC = 0.76). Both measures were highly correlated with EQ-5D-5 L and significantly differentiated (p < 0.001) among groups categorized by cancer stage, OHA performance status, and mental health. ESs for QLU-C10D were numerically higher for cancer stage, OHA, and performance status (ES = 0.53-1.49), whereas ES was higher for FACT-8D and mental health status (ES = 1.35). Responsiveness was higher for QLU-C10D (AUC = 0.84) compared to FACT-8D (AUC = 0.78).

CONCLUSION

Both QLU-C10D and FACT-8D are valid cancer-specific MAUIs for evaluating patients with HM. However, scholars should consider their slight differences in focus when choosing between the two measures.

Cost-effectiveness of proton beam therapy vs. conventional radiotherapy for patients with brain tumors in Sweden: results from a non-randomized prospective multicenter study

BACKGROUND

This study assessed the cost-effectiveness of proton beam therapy (PBT) compared to conventional radiotherapy (CRT) for treating patients with brain tumors in Sweden.

METHODS

Data from a longitudinal non-randomized study performed between 2015 and 2020 was used, and included adult patients with brain tumors, followed during treatment and through a one-year follow-up. Clinical and demographic data were sourced from the longitudinal study and linked to Swedish national registers to get information on healthcare resource use. A cost-utility framework was used to evaluate the cost-effectiveness of PBT vs. CRT. Patients in PBT group (n = 310) were matched with patients in CRT group (n = 40) on relevant observables using propensity score matching with replacement. Costs were estimated from a healthcare perspective and included costs related to inpatient and specialized outpatient care, and prescribed medications. The health outcome was quality-adjusted life-years (QALYs), derived from the EORTC-QLQ-C30. Generalized linear models (GLM) and two-part models were used to estimate differences in costs and QALYs.

RESULTS

PBT yielded higher total costs, 14,639 US$, than CRT, 13,308 US$, with a difference of 1,372 US$ (95% CI, -4,914-7,659) over a 58 weeks' time horizon. Further, PBT resulted in non-significantly lower QALYs, 0.746 compared to CRT, 0.774, with a difference of -0.049 (95% CI, -0.195-0.097). The probability of PBT being cost-effective was < 30% at any willingness to pay.

CONCLUSIONS

These results suggest that PBT cannot be considered a cost-effective treatment for brain tumours, compared to CRT.

TRIAL REGISTRATION

Not applicable.

The EORTC QLU-C10D: the Hong Kong valuation study

OBJECTIVE

The EORTC QLU-C10D is a new preference-based measure derived from the EORTC QLQ-C30. Country-specific value sets are required to support the cost-utility analysis of cancer-related interventions. This study aimed to generate an EORTC QLU-C10 value set for Hong Kong (HK).

METHODS

A HK online panel was quota-sampled to achieve an adult general population sample representative by sex and age. Participants were invited to complete an online discrete choice experiment survey. Each participant was asked to complete 16 choice-pairs, randomly assigned from a total of 960 choice-pairs, each comprising two QLU-C10D health states and a duration attribute. Conditional and mixed logistic regression analyses were used to analyse the data.

RESULTS

The analysis included data from 1041 respondents who had successfully completed the online survey. The distribution of sex did not differ from that of the general population, but a significant difference was found among age groups. A weighting analysis for non-representative variable (age) was used. Utility decrements were generally monotonic, with the largest decrements for physical functioning (- 0.308), role functioning (- 0.165), and pain (- 0.161). The mean QLU-C10D utility score of the participants was 0.804 (median = 0.838, worst to best = - 0.169 to 1). The value of the worst health state was - 0.223, which was sufficiently lower than 0 (being dead).

CONCLUSIONS

This study established HK utility weights for the QLU-C10D, which can facilitate cost-utility analyses across cancer-related health programmes and technologies.

Japanese value set for the EORTC QLU-C10D: A multi-attribute utility instrument based on the EORTC QLQ-C30 cancer-specific quality-of-life questionnaire

PURPOSE

This study aimed to develop a Japanese value set for the EORTC QLU-C10D, a multi-attribute utility measure derived from the cancer-specific health-related quality-of-life (HRQL) questionnaire, the EORTC QLQ-C30. The QLU-C10D contains ten HRQL dimensions: physical, role, social and emotional functioning, pain, fatigue, sleep, appetite, nausea, and bowel problems.

METHODS

Quota sampling of a Japanese online panel was used to achieve representativeness of the Japanese general population by sex and age (≥ 18 years). The valuation method was an online discrete choice experiment. Each participant considered 16 choice pairs, randomly assigned from 960 choice pairs. Each pair included two QLU-C10D health states and life expectancy. Data were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life-year framework. Preference weights were calculated as the ratio of each dimension-level coefficient to the coefficient for life expectancy.

RESULTS

A total of 2809 eligible panel members consented, 2662/2809 (95%) completed at least one choice pair, and 2435/2662 (91%) completed all choice pairs. Within dimensions, preference weights were generally monotonic. Physical functioning, role functioning, and pain were associated with the largest utility weights. Intermediate utility weights were associated with social functioning and nausea; the remaining symptoms and emotional functioning were associated with smaller utility decrements. The value of the worst health state was - 0.221, lower than that seen in most other existing QLU-C10D country-specific value sets.

CONCLUSIONS

The Japan-specific QLU-C10D value set is suitable for evaluating the cost and utility of oncology treatments for Japanese health technology assessment and decision-making.

Cancer-Specific Health Utilities: Evaluation of Core Measurement Properties of the EORTC QLU-C10D in Lung Cancer Patients-Data from Four Multicentre LUX-Lung Trials, Applying Six Country Tariffs

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.

A scoping review to create a framework for the steps in developing condition-specific preference-based instruments de novo or from an existing non-preference-based instrument: use of item response theory or Rasch analysis

BACKGROUND

There is no widely accepted framework to guide the development of condition-specific preference-based instruments (CSPBIs) that includes both de novo and from existing non-preference-based instruments. The purpose of this study was to address this gap by reviewing the published literature on CSPBIs, with particular attention to the application of item response theory (IRT) and Rasch analysis in their development.

METHODS

A scoping review of the literature covering the concepts of all phases of CSPBI development and evaluation was performed from MEDLINE, Embase, PsychInfo, CINAHL, and the Cochrane Library, from inception to December 30, 2022.

RESULTS

The titles and abstracts of 1,967 unique references were reviewed. After retrieving and reviewing 154 full-text articles, data were extracted from 109 articles, representing 41 CSPBIs covering 21 diseases or conditions. The development of CSPBIs was conceptualized as a 15-step framework, covering four phases: 1) develop initial questionnaire items (when no suitable non-preference-based instrument exists), 2) establish the dimensional structure, 3) reduce items per dimension, 4) value and model health state utilities. Thirty-nine instruments used a type of Rasch model and two instruments used IRT models in phase 3.

CONCLUSION

We present an expanded framework that outlines the development of CSPBIs, both from existing non-preference-based instruments and de novo when no suitable non-preference-based instrument exists, using IRT and Rasch analysis. For items that fit the Rasch model, developers selected one item per dimension and explored item response level reduction. This framework will guide researchers who are developing or assessing CSPBIs.

Danish value sets for the EORTC QLU-C10D utility instrument

PURPOSE

In this study, we developed Danish utility weights for the European Organisation for Research and Treatment of Cancer (EORTC) QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30.

METHODS

Following a standardized methodology, 1001 adult participants from the Danish general population were quota-sampled and completed a cross-sectional web-based survey and discrete choice experiment (DCE). In the DCE, participants considered 16 choice sets constructed from the key 10 dimensions of the QLU-C10D and chose their preferred health state for each one. Utility weights were calculated using conditional logistic regression with correction for non-monotonicity.

RESULTS

The sample (n = 1001) was representative of the Danish general population with regard to age and gender. The domains with the largest utility decrements, i.e., the domains with the biggest impact on health utility, were physical functioning (- 0.224), pain (- 0.160), and role functioning (- 0.136). The smallest utility decrements were observed for the domains lack of appetite (- 0.024), sleep disorders (- 0.057), and fatigue (- 0.064). Non-monotonicity of severity levels was observed for the domains sleep disturbances, lack of appetite, and bowel problems. Deviations from monotonicity were not statistically significant.

CONCLUSION

The EORTC QLU-C10D is a relatively new multi-attribute utility instrument and is a promising cancer-specific health technology assessment candidate measure. The country-specific Danish utility weights from this study can be used for cost-utility analyses in Danish patients and for comparison with other country-specific utility data.

Health-related quality of life and quality-adjusted progression free survival for carfilzomib and dexamethasone maintenance following salvage autologous stem-cell transplantation in patients with multiple myeloma: a randomized phase 2 trial by the Nordic Myeloma Study Group

BACKGROUND

Decisions regarding maintenance therapy in patients with multiple myeloma should be based on both treatment efficacy and health-related quality of life (HRQL) consequences. In the CARFI trial, patients with first relapse of multiple myeloma underwent salvage autologous stem cell transplantation (salvage ASCT) before randomization to carfilzomib-dexamethasone maintenance therapy (Kd) or observation. The primary clinical endpoint was time to progression, which was extended by 8 months by Kd. The aim of this paper is to present the all HRQL endpoints of the CARFI trial including the HRQL effect of Kd maintenance therapy relative to observation. The primary HRQL endpoint was assessed by EORTC QLQ-C30 Summary score (QLQ-C30-sum) at 8 months follow-up. A key secondary HRQL endpoint was quality-adjusted progression-free-survival (QAPFS).

METHODS

HRQL was assessed with EORTC QLQ-C30, EORTC QLQ-MY20 and FACT/GOG-Ntx at randomization and every second month during follow-up. HRQL data were analyzed with linear mixed effect models until 8 months follow-up. QAPFS per individual was calculated by multiplying progression-free survival (PFS) by two quality-adjustment metrics, the QLQ-C30-sum and EORTC Quality of Life Utility Measure-Core 10 dimensions (QLU-C10D). The QAPFS per treatment group was estimated with the Kaplan-Meier method. P < 0.05 was used for statistical significance, and a between-group minimal important difference of 10 points was interpreted as clinically relevant for the QLQ-C30-sum.

RESULTS

168 patients were randomized. HRQL questionnaire compliance was 93%. For the QLQ-C30-sum, the difference of 4.62 points (95% confidence interval (CI) -8.9: -0.4, p = 0.032) was not clinically relevant. PFS was 19.3 months for the Kd maintenance group and 16.8 months for the observation group; difference = 2.5 months (95% CI 0.5; 4.5). QAPFS based on the QLQ-C30-sum for the Kd maintenance group was 18.0 months (95% CI 16.4; 19.6) and for the observation group 15.0 months (95% CI 13.5; 16.5); difference = 3.0 months (95% CI 0.8-5.3). QAPFS based on the QLU-C10D for the Kd maintenance group was 17.5 months (95% CI 15.9; 19.2) and 14.0 months (95% CI 12.4; 15.5) for the observation group; difference = 3.5 months (95% CI 1.1-5.9).

CONCLUSIONS

Kd maintenance therapy after salvage ASCT did not adversely affect overall HRQL, but adjustment for HRQL reduced the PFS compared to unadjusted PFS. PFS of maintenance therapy should be quality-adjusted to balance the benefits and HRQL impact.

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.

[Patient-reported outcomes in head and neck cancer treatment: relevance, challenges, and benefit]

Next to overall survival, quality of life is becoming more and more pivotal for cancer patients. The various domains of quality of life are complex and have different value to each patient. However, not only patients but also health care professionals, the pharmaceutical industry, and regulatory bodies ask: How can quality of life be reliably ascertained in clinical trials? For this purpose, carefully developed and validated specific questionnaires are needed: the patient-reported outcome measures (PROMs). A key challenge is to define how results based on PROMs can be used for shared decision-making. Next to clinical factors such as health and nutritional status, quality of life acts as a prognostic factor for overall survival in cancer. Thus, it is crucial to take quality of life into account in daily clinical practice.

Discrete Choice Experiments in Health State Valuation: A Systematic Review of Progress and New Trends

BACKGROUND

Discrete choice experiments (DCEs) are increasingly used in health state valuation studies.

OBJECTIVE

This systematic review updates the progress and new findings of DCE studies in the health state valuation, covering the period since the review of June 2018 to November 2022. The review reports the methods that are currently being used in DCE studies to value health and study design characteristics, and, for the first time, reviews DCE health state valuation studies published in the Chinese language.

METHODS

English language databases PubMed and Cochrane, and Chinese language databases Wanfang and CNKI were searched using the self-developed search terms. Health state valuation or methodology study papers were included if the study used DCE data to generate a value set for a preference-based measure. Key information extracted included DCE study design strategies applied, methods for anchoring the latent coefficient on to a 0-1 QALY scale and data analysis methods.

RESULTS

Sixty-five studies were included; one Chinese language publication and 64 English language publications. The number of health state valuation studies using DCE has rapidly increased in recent years and these have been conducted in more countries than prior to 2018. Wide usage of DCE with duration attributes, D-efficient design and models accounting for heterogeneity has continued in recent years. Although more methodological consensus has been found than in studies conducted prior to 2018, this consensus may be driven by valuation studies for common measures with an international protocol (the 'model' valuation research). Valuing long measures with well-being attributes attracted attention and more realistic design strategies (e.g., inconstant time preference, efficient design and implausible states design) were identified. However, more qualitative and quantitative methodology study is still necessary to evaluate the effect of those new methods.

CONCLUSIONS

The use of DCEs in health state valuation continues to grow dramatically and the methodology progress makes the method more reliable and pragmatic. However, study design is driven by international protocols and method selection is not always justified. There is no gold standard for DCE design, presentation format or anchoring method. More qualitative and quantitative methodology study is recommended to evaluate the effect of new methods before researchers make methodology decisions.

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.

Patient-reported outcome measures for physical function in cancer patients: content comparison of the EORTC CAT Core, EORTC QLQ-C30, SF-36, FACT-G, and PROMIS measures using the International Classification of Functioning, Disability and Health

BACKGROUND

Patient-reported physical function (PF) is a key endpoint in cancer clinical trials. Using complex statistical methods, common metrics have been developed to compare scores from different patient-reported outcome (PRO) measures, but such methods do not account for possible differences in questionnaire content. Therefore, the aim of our study was a content comparison of frequently used PRO measures for PF in cancer patients.

METHODS

Relying on the framework of the International Classification of Functioning, Disability and Health (ICF) we categorized the item content of the physical domains of the following measures: EORTC CAT Core, EORTC QLQ-C30, SF-36, PROMIS Cancer Item Bank for Physical Function, PROMIS Short Form for Physical Function 20a, and the FACT-G. Item content was linked to ICF categories by two independent reviewers.

RESULTS

The 118 items investigated were assigned to 3 components ('d - Activities and Participation', 'b - Body Functions', and 'e - Environmental Factors') and 11 first-level ICF categories. All PF items of the EORTC measures but one were assigned to the first-level ICF categories 'd4 - Mobility' and 'd5 - Self-care', all within the component 'd - Activities and Participation'. The SF-36 additionally included item content related to 'd9 - Community, social and civic life' and the PROMIS Short Form for Physical Function 20a also included content related to 'd6 - domestic life'. The PROMIS Cancer Item Bank (v1.1) covered, in addition, two first-level categories within the component 'b - Body Functions'. The FACT-G Physical Well-being scale was found to be the most diverse scale with item content partly not covered by the ICF framework.

DISCUSSION

Our results provide information about conceptual differences between common PRO measures for the assessment of PF in cancer patients. Our results complement quantitative information on psychometric characteristics of these measures and provide a better understanding of the possibilities of establishing common metrics.

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 FACT-8D, a new cancer-specific utility algorithm based on the Functional Assessment of Cancer Therapies-General (FACT-G): a Canadian valuation study

Introduction

Utility instruments are used to assess patients’ health-related quality of life for cost-utility analysis (CUA). However, for cancer patients, the dimensions of generic utility instruments may not capture all the information relevant to the impact of cancer. Cancer-specific utilities provide a useful alternative. Under the auspices of the Multi-Attribute Utility in Cancer Consortium, a cancer-specific utility algorithm was derived from the FACT-G. The new FACT-8D contains eight dimensions: pain, fatigue, nausea, sleep, work, support from family/friends, sadness, and worry health will get worse. The aim of the study was to obtain a Canadian value set for the FACT-8D.

Methods

A discrete choice experiment was administered to a Canadian general population online panel, quota sampled by age, sex, and province/territory of residence. Respondents provided responses to 16 choice sets. Each choice set consisted of two health states described by the FACT-8D dimensions plus an attribute representing survival duration. Sample weights were applied and the responses were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life year framework. The results were converted into utility weights by evaluating the marginal rate of substitution between each level of each FACT-8D dimension with respect to duration.

Results

2228 individuals were recruited. The analysis dataset included n = 1582 individuals, who completed at least one choice set; of which, n = 1501 completed all choice sets. After constraining to ensure monotonicity in the utility function, the largest decrements were for the highest levels of pain (− 0.38), nausea (− 0.30), and problems doing work (− 0.23). The decrements of the remaining dimensions ranged from − 0.08 to − 0.18 for their highest levels. The utility of the worst possible health state was defined as − 0.65, considerably worse than dead.

Conclusions

The largest impacts on utility included three generic dimensions (i.e., pain, support, and work) and nausea, a symptom caused by cancer (e.g., brain tumours, gastrointestinal tumours, malignant bowel obstruction) and by common treatments (e.g., chemotherapy, radiotherapy, opioid analgesics). This may make the FACT-8D more informative for CUA evaluating in many cancer contexts, an assertion that must now be tested empirically in head-to-head comparisons with generic utility measures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12955-022-02002-z.

The EORTC QLU-C10D discrete choice experiment for cancer patients: a first step towards patient utility weights

Background

The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility-Core 10 Dimensions (QLU-C10D) is a novel cancer-specific preference-based measure (PBM) for which value sets are being developed for an increasing number of countries. This is done by obtaining health preferences from the respective general population. There is an ongoing discussion if instead patients suffering from the disease in question should be asked for their preferences. We used the QLU-C10D valuation survey, originally designed for use in the general population, in a sample of cancer patients in Austria to assess the methodology’s acceptability and applicability in this target group before obtaining QLU-C10D patient preferences.

Methods

The core of the QLU-C10D valuation survey is a discrete choice experiment in which respondents are asked to give preferences for certain health states (described by a relatively large number of 10 quality of life domains) and an associated survival time. They therewith are asked to trade off quality of life against life time. As this might be a very burdensome task for cancer patients undergoing treatment, a cognitive interview was conducted in a pilot sample to assess burden and potential additional needs for explanation in order to be able to use the DCE for the development of QLU-C10D patient preferences. In addition, responses to general feedback questions on the survey were compared against responses from a matched control group from the already completed Austrian general population valuation survey.

Results

We included 48 patients (mean age 59.9 years; 46% female). In the cognitive interview, the majority indicated that their experience with the survey was positive (85%) and overall clarity as good (90%). In response to the general feedback questions, patients rated the presentation of the health states less clear than matched controls (p = 0.008). There was no difference between patients and the general population concerning the difficulty in choosing between the health states (p = 0.344).

Conclusion

Despite the relatively large number of DCE domains the survey was manageable for patients and allows going on with the QLU-C10D patient valuation study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41687-022-00430-5.

Adapting preference-based utility measures to capture the impact of cancer treatment-related symptoms

It is important that patient-reported outcome (PRO) measures used to assess cancer therapies adequately capture the benefits and risks experienced by patients, particularly when adverse event profiles differ across therapies. This study explores the case for augmenting preference-based utility measures to capture the impact of cancer treatment-related symptoms. Additional cancer treatment-related items could be specific (e.g., rash) or global. While specific items are easier to describe and understand, their use may miss rarer symptoms and those that are currently unknown but will arise from future medical advancements. The appropriate number of additional items, the independence of those items, and their impact on the psychometric properties of the core instrument require consideration. Alternatively, a global item could encompass all potential treatment-related symptoms, of any treatments for any disease. However, such an item may not be well understood by general public respondents in valuation exercises. Further challenges include the decision about whether to generate de novo value sets for the modified instrument or to map to existing tariffs. The fluctuating and transient nature of treatment-related symptoms may be inconsistent with the methods used in conventional valuation exercises. Fluctuating symptoms could be missed by sub-optimal measure administration timing. The addition of items also poses double-counting risks. In summary, the addition of treatment-related symptom items could increase the sensitivity of existing utility measures to capture known and unknown treatment effects in oncology, while retaining the core domains. However, more research is needed to investigate the challenges, particularly regarding valuation.

A Comparison of Generic and Condition-Specific Preference-Based Measures Using Data From Nivolumab Trials: EQ-5D-3L, Mapping to the EQ-5D-5L, and European Organisation for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions

OBJECTIVES

There is growing interest in condition-specific preference measures, including the European Organisation for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions (QLU-C10D). This research assessed the implications of using utility indices on the basis of the EQ-5D-3L, a mapping of EQ-5D-3L to the EQ-5D-5L, and the QLU-C10D, and compared their psychometric properties.

METHODS

Data were taken from 8 phase 3 randomized controlled trials of nivolumab with or without ipilimumab for the treatment of solid tumors. Utilities for progression-related states were calculated using the UK and English value sets and incremental quality-adjusted life-years (QALYs) derived from established UK cost-effectiveness models. The psychometric properties of the utility indices were assessed using pooled trial data.

RESULTS

Compared with the EQ-5D-3L index, the mapped EQ-5D-5L index yielded an average of 6% more and the QLU-C10D index an average of 2% fewer incremental QALYs for nivolumab versus comparators. All indices could differentiate between groups defined by performance status, cancer stage, or self-reported health status at baseline and detect meaningful changes in performance status, tumor response, health status, and quality of life over approximately 12 weeks of treatment.

CONCLUSIONS

The lower QALY yield of the QLU-C10D was balanced by evidence of greater validity and responsiveness. Benefits gained from using the QLU-C10D may be apparent when treatments affect targeted symptoms and functional aspects, including sleep, bowel function, appetite, nausea, and fatigue. The observed differences in QALYs may not be sufficiently large to affect health technology assessment decisions.

Estimation of an EORTC QLU-C10 Value Set for Spain Using a Discrete Choice Experiment

BACKGROUND

The EORTC QLU-C10D is a preference-based measure derived from the EORTC QLQ-C30. For use in economic evaluations, country-specific value sets are needed. This study aimed to generate an EORTC QLU-C10 value set for Spain.

METHODS

A sample of the Spanish general population completed an online discrete choice experiment. An attribute-balanced incomplete block design was used to select 960 choice tasks, with a total of 1920 health states. Each participant was randomly assigned 16 choice sets without replacement. Data were modelled using generalized estimating equations and mixed logistic regressions.

RESULTS

A total of 1625 panel members were invited to participate, 1010 of whom were included in the study. Dimension decrements were generally monotonic with larger disutilities at increased severity levels. Dimensions associated with larger decrements were physical functioning and pain, while the dimension with the smallest decrement was sleep disturbances. The PITS state (i.e. worst attainable health) for the Spanish population is - 0.043.

CONCLUSIONS

This study generated the first Spanish value set for the QLU-C10D. This can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30.

The Functional Assessment of Cancer Therapy Eight Dimension (FACT-8D), a Multi-Attribute Utility Instrument Derived From the Cancer-Specific FACT-General (FACT-G) Quality of Life Questionnaire: Development and Australian Value Set

OBJECTIVES

To develop a cancer-specific multi-attribute utility instrument derived from the Functional Assessment of Cancer Therapy - General (FACT-G) health-related quality of life (HRQL) questionnaire.

METHODS

We derived a descriptive system based on a subset of the 27-item FACT-G. Item selection was informed by psychometric analyses of existing FACT-G data (n = 6912) and by patient input (n = 82). We then conducted an online valuation survey, with participants recruited via an Australian general population online panel. A discrete choice experiment (DCE) was used, with attributes being the HRQL dimensions of the descriptive system and survival duration, and 16 choice-pairs per participant. Utility decrements were estimated with conditional logit and mixed logit modeling.

RESULTS

Eight HRQL dimensions were included in the descriptive system: pain, fatigue, nausea, sleep, work, social support, sadness, and future health worry; each with 5 levels. Of 1737 panel members who accessed the valuation survey, 1644 (95%) completed 1 or more DCE choice-pairs and were included in analyses. Utility decrements were generally monotonic; within each dimension, poorer HRQL levels generally had larger utility decrements. The largest utility decrements were for the highest levels of pain (-0.40) and nausea (-0.28). The worst health state had a utility of -0.54, considerably worse than dead.

CONCLUSIONS

A descriptive system and preference-based scoring approach were developed for the FACT-8D, a new cancer-specific multi-attribute utility instrument derived from the FACT-G. The Australian value set is the first of a series of country-specific value sets planned that can facilitate cost-utility analyses based on items from the FACT-G and related FACIT questionnaires containing FACT-G items.

Functional health and symptoms in Spain before and during the COVID-19 pandemic

BACKGROUND

The impact of the coronavirus disease (COVID-19) pandemic on wellbeing and health has so far been studied using mostly cross-sectional designs. To place recent findings into context, we compared symptoms and functional health status in two independent samples assessed before and during the COVID-19 pandemic.

METHODS

Participants were recruited via an online panel using quota sampling. We assessed symptoms, functional health, and global quality of life with the EORTC QLQ-C30 in two general population samples in Spain (collected in July 2019 and April 2020). We also assessed several COVID-19 related variables, such as adherence to social distancing.

RESULTS

Data from N = 1010 participants before the pandemic (mean age 47.1 years, 50.5% female) were compared with data from N = 504 participants during the pandemic (mean age 47.1 years, 50.8% female). Participants during the pandemic (vs. before the pandemic) reported lower role functioning and emotional functioning, as well as less symptom burden. A lower degree of social distancing was associated with better functional health and lower symptom burden.

CONCLUSION

Our findings indicate an impact of the COVID-19 pandemic on functional health and symptom burden in the Spanish general population. The comparison of before and during the pandemic can be used to benchmark results raised only during the pandemic.

French Value-Set of the QLU-C10D, a Cancer-Specific Utility Measure Derived from the QLQ-C30

BACKGROUND AND OBJECTIVE

The EORTC Quality of Life Utility Measure-Core 10 Dimensions (QLU-C10D) is a new multi-attribute utility instrument derived from the EORTC Quality of Life Questionnaire-Core 30 (QLQ-C30), a widely used cancer-specific quality-of-life questionnaire. It covers ten dimensions: physical, role functioning, social, emotional functioning, pain, fatigue, sleep, appetite, nausea and bowel problems. To allow national health preferences to be reflected, country-specific valuations are being performed through collaboration between the Multi-Attribute Utility Cancer (MAUCa) Consortium and the EORTC. The aim of this study was to determine the utility weights for health states in the French version of the QLU-C10D.

METHODS

Valuations were run in a web-based setting in a general population sample of 1033 adults. Utilities were elicited using a discrete-choice experiment (DCE). Data were analyzed by conditional logistic regression and mixed logits.

RESULTS

The sample was representative of the general French population in terms of gender and age. Dimensions with the largest impact on utility weights were, in this order: physical functioning, pain and emotional functioning. The impact on utilities was lower for role functioning, nausea, bowel problems and social functioning. The dimensions of sleep, fatigue and lacking appetite were associated with the smallest utility decrement.

CONCLUSION

The results of the present study provide utility weights for the QLU-C10D and offer interesting prospects, as some cancer-specific dimensions also received sizeable utility weights (nausea and bowel problems). In fact, the EQ-5D and the HUI 3 are recommended in France and commonly used for cancer-related CUA; however, both these instruments are generic. The availability of a new cancer-specific utility instrument, such as the QLU-C10D, could improve the quality and the pertinence of future CUA in oncology.

Dutch utility weights for the EORTC cancer-specific utility instrument: the Dutch EORTC QLU-C10D

Purpose

To measure utilities among cancer patients, a cancer-specific utility instrument called the European Organization for Research and Treatment of Cancer (EORTC) QLU-C10D has been developed based on EORTC quality of life core module (QLQ-C30). This study aimed to provide Dutch utility weights for the QLU-C10D.

Methods

A cross-sectional valuation study was performed in 1017 participants representative in age and gender of the Dutch general population. The valuation method was a discrete choice experiment containing 960 choice sets, i.e. pairs of QLU-C10D health states, each health state described in terms of the 10 QLU-C10D domains and the duration of that health state. Each participant considered 16 choice sets, choosing their preferred health state from each pair. Utility scores were derived using generalized estimation equation models. Non-monotonic levels were combined.

Results

Utility decrements were generated for all 10 QLU-C10D domains, with largest decrements for pain (− 0.242), physical functioning (− 0.228), and role functioning (− 0.149). Non-monotonic levels of emotional functioning, pain, fatigue, sleep problems, and appetite loss were combined. No decrement in utility was seen in case of a little or quite a bit impairment in emotional functioning or a little pain. The mean QLU-C10D utility score of the participants was 0.85 (median = 0.91, interquartile range = 0.82 to 0.96).

Conclusion

Dutch utility decrements were generated for the QLU-C10D. These are important for evaluating the cost-utility of new cancer treatments and supportive care interventions. Further insight is warranted into the added value of the QLU-C10D alongside other utility instruments.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11136-021-02767-8.

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.

Electronic supplementary material

The online version of this article (10.1007/s11136-020-02536-z) contains supplementary material, which is available to authorized users.