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

Jansen, Femke; Leeuw, Irma M. Verdonck‐de; Gamper, Eva‐Maria; Norman, Richard; Holzner, Bernhard; King, Madeleine; Kemmler, Georg

doi:10.1007/s11136-021-02767-8

Cited by 22 publications

(12 citation statements)

References 26 publications

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“…For this study, we followed the methods for the generation of utility weights established by King et al [ 24 ] which were also used in the valuation surveys for other countries [ 14 , 15 , 18 , 20 , 30 ]. In this cross-sectional valuation survey, participants from the Danish general population were recruited via a third-party provider online panel ( https://surveyengine.com/ ).…”

Section: Methodsmentioning

confidence: 99%

“…As different countries and healthcare systems have different approaches to health economic evaluations and CUA [ 11 ] and health state preferences are known to differ between countries [ 15 ], country-specific utility weights should be used where available and required by agencies. For the QLU-C10D, utility weights have already been established for a number of European countries [ 14 , 15 , 18 , 20 , 30 ], Australia [ 24 ], the United States [ 36 ], Canada [ 29 ], and first Asian countries [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

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Danish value sets for the EORTC QLU-C10D utility instrument

Lehmann,

Rojas-Concha,

Petersen

et al. 2024

Qual Life Res

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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.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Danish value sets for the EORTC QLU-C10D utility instrument

Lehmann,

Rojas-Concha,

Petersen

et al. 2024

Qual Life Res

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“…We expected that differences or changes should be found more pronounced with the cancer-speci c measure, than with the generic comparative instrument, the EQ-5D-3L. For this analysis we used six corresponding country tariffs of the QLU-C10D and the EQ-5D-3L: Australia (AUS) ( 31 ), Canada (CAN) ( 32 ), Italy (ITA) ( 33 ), the Netherlands (NLD) ( 34 ), Poland (POL) (34), and the United Kingdom (UK) ( 35 ) 2 Methods…”

Section: Aim Of This Studymentioning

confidence: 99%

Clinical Validity of the Cancer-Specific Utility Measure EORTC QLU-C10D: Retrospective Analyses of Four Lung Cancer Trials Using Six Country Tariffs.

Seyringer,

Pilz,

Al-Naesan

et al. 2024

Preprint

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Objectives The Quality of Life (QoL) Utility measure, QLU-C10D, is derived of the European Organisation for Research and Treatment of Cancer (EORTC) QoL Questionnaire, QLQ-C30. Based on the cancer-specific nature, the QLU-C10D is expected to be sensitive and responsive in lung cancer patients.Methods This retrospective analysis used data from four lung cancer multi-center trials. Clinical validity was assessed in comparison to a generic standard utility instrument, the EuroQoL Group´s EQ-5D-3L. Utilities for six country tariffs (Australia, Canada, Italy, the Netherlands, Poland, UK) were calculated at baseline and end of treatment. Country tariff pairs of both measures (k) were compared in terms of Relative Efficiency (RE) and difference in Effect Sizes (dES) of significant t-tests (Bonferroni-Holm correction) in 1) sensitivity to detect differences between performance status groups and 2) responsiveness to changes.Results ad 1) Sensitivity indices favored the QLU-C10D (k = 18, p ≤ 0.019; RE > 1.10; dES > 0.03). ad 2) Responsiveness indices of differences between adverse events groups favored the QLU-C10D (k = 6, p ≤ .006; RE > 1.0, dES > 0.02). Responsiveness indices of changes within clinically known groups (k = 78), largely favored QLU-C10D (k = 74, p ≤ .024; RE > 1.01; dES > 0.02). In summary, 96% of the comparative indices favored the QLU-C10D.Conclusions Our study confirms the clinical validity of the QLU-C10D in lung cancer patients. The QLU-C10D produced homogenous results across six country tariffs and detected differences/changes in alignment with clinical expectations. In most comparisons the QLU-C10D was more sensitive and responsive compared to the EQ-5D-3L.

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“…The modelling approach followed that used in the valuation studies conducted in Australia and the United States [14]. The DCE responses were analyzed using a conditional logit model (Model 1).…”

Section: Utility Estimationmentioning

confidence: 99%

“…The Multi-Attribute Utility in Cancer (MAUCa) Consortium has derived a MAUI to generate utilities from data collected from the QLQ-C30 to produce the European Organization of Research and Treatment in Cancer (EORTC) QLU-C10D [11]. Since its development, a number of country-specific utility weights for the QLU-C10D have followed, including Canada [12][13][14][15][16][17][18][19]. Recently, the MAUCa Consortium derived the health state classification system from items of the FACT-G and the Australian value set for the new FACT-8D has now been produced [20].…”

Section: Introductionmentioning

confidence: 99%

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

McTaggart-Cowan

King²,

Norman³

et al. 2022

Health Qual Life Outcomes

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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.

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

Cited by 22 publications

References 26 publications

Danish value sets for the EORTC QLU-C10D utility instrument

Danish value sets for the EORTC QLU-C10D utility instrument

Clinical Validity of the Cancer-Specific Utility Measure EORTC QLU-C10D: Retrospective Analyses of Four Lung Cancer Trials Using Six Country Tariffs.

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

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