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

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 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.

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.

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.

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.

General population normative data from seven European countries for the K10 and K6 scales for psychological distress

The 10-item Kessler Psychological Distress scale (K10) and its 6-item short-form version (K6) measure psychological distress, particularly anxiety or depressive symptoms. While these questionnaire scales are widely used in various settings and populations, general population normative data are rarely available. To facilitate the interpretation of K10 and K6 scores, we provide normative general population data from seven European countries. We used an online survey to collect K10 data from general population samples in Austria, Italy, Germany, France, the Netherlands, Poland and Spain. We calculated the age- and sex-specific normative values separately for each country. For more specific estimates of K10 and K6 scores for individuals or groups, we also established a multivariable regression model based on socio-demographic and health data. In total, N = 7,087 adults participated in our study (51.6% women; mean age, 49.6 years). The mean K10 score in the total sample was 8.5 points (standard deviation, 7.3) on 0-40 points metric, with mean scores in individual countries ranging from 6.9 (the Netherlands) to 9.9 (Spain). Women showed higher scores than men and younger participants scored higher than older participants. Our study is the first to present normative K10 and K6 data from several European countries using a consistent sampling approach. These reference values will facilitate the interpretation of K10 and K6 scores in clinical research and practice and also highlight the variation in psychological distress levels across countries and groups according to their socio-demographic and health characteristics.

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.

A Value Set for the EQ-5D-Y-3L in the Netherlands

BACKGROUND AND OBJECTIVE

There is increasing interest in preference-accompanied measures of health for paediatric populations. The child-friendly EQ-5D version, EQ-5D-Y-3L, is one such instrument, but the lack of a Dutch value set prevents its use in economic evaluations of healthcare interventions in the Netherlands. This study aims at covering this gap by collecting preferences using a standardised protocol for deriving EQ-5D-Y-3L value sets.

METHODS

Composite time trade-off data were collected using videoconferencing interviews, with each respondent completing ten composite time trade-off tasks. Discrete choice experiment data were collected using an online survey, with respondents each completing 15 paired comparisons. Respondents completed these tasks considering what they prefer for a hypothetical 10-year-old child. Discrete choice experiment data were analysed using a ten-parameter mixed-logit model and anchored to the quality-adjusted life-year scale using the mean observed composite time trade-off values.

RESULTS

The study collected preferences for 197 respondents using composite time trade-off and for 959 respondents using a discrete choice experiment. The discrete choice experiment sample was representative for the Dutch population in terms of age and sex. The level 3 weight for pain/discomfort was the largest, followed by feeling worried, sad or unhappy, usual activities, mobility and self-care. Health state values ranged between -0.218 and 1.

CONCLUSIONS

This study generated a Dutch value set for the EQ-5D-Y-3L, which can be used for the computation of quality-adjusted life-years for economic evaluations of healthcare interventions in paediatric populations.

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.

Clinical Outcome Assessment in Cancer Rehabilitation and the Central Role of Patient-Reported Outcomes

The aim of cancer rehabilitation is to help patients regain functioning and social participation. In order to evaluate and optimize rehabilitation, it is important to measure its outcomes in a structured way. In this article, we review the different types of clinical outcome assessments (COAs), including Clinician-Reported Outcomes (ClinROs), Observer-Reported Outcomes (ObsROs), Performance Outcomes (PerfOs), and Patient-Reported Outcomes (PROs). A special focus is placed on PROs, which are commonly defined as any direct report from the patient about their health condition without any interpretation by a third party. We provide a narrative review of available PRO measures (PROMs) for relevant outcomes, discuss the current state of PRO implementation in cancer rehabilitation, and highlight trends that use PROs to benchmark value-based care. Furthermore, we provide examples of PRO usage, highlight the benefits of electronic PRO (ePRO) collection, and offer advice on how to select, implement, and integrate PROs into the cancer rehabilitation setting to maximize efficiency.

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.

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.

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.