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QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30.

作者信息

King M T, Costa D S J, Aaronson N K, Brazier J E, Cella D F, Fayers P M, Grimison P, Janda M, Kemmler G, Norman R, Pickard A S, Rowen D, Velikova G, Young T A, Viney R

机构信息

Psycho-Oncology Cooperative Research Group (PoCoG), School of Psychology, Faculty of Science, University of Sydney, Sydney, NSW, Australia.

Central Clinical School, Sydney Medical School, Faculty of Medicine, University of Sydney, Sydney, NSW, Australia.

出版信息

Qual Life Res. 2016 Mar;25(3):625-36. doi: 10.1007/s11136-015-1217-y. Epub 2016 Jan 20.


DOI:10.1007/s11136-015-1217-y
PMID:26790428
Abstract

PURPOSE: To derive a health state classification system (HSCS) from the cancer-specific quality of life questionnaire, the EORTC QLQ-C30, as the basis for a multi-attribute utility instrument. METHODS: The conceptual model for the HSCS was based on the established domain structure of the QLQ-C30. Several criteria were considered to select a subset of dimensions and items for the HSCS. Expert opinion and patient input informed a priori selection of key dimensions. Psychometric criteria were assessed via secondary analysis of a pooled dataset comprising HRQOL and clinical data from 2616 patients from eight countries and a range of primary cancer sites, disease stages, and treatments. We used confirmatory factor analysis (CFA) to assess the conceptual model's robustness and generalisability. We assessed item floor effects (>75 % observations at lowest score), disordered item response thresholds, coverage of the latent variable and differential item function using Rasch analysis. We calculated effect sizes for known group comparisons based on disease stage and responsiveness to change. Seventy-nine cancer patients assessed the relative importance of items within dimensions. RESULTS: CFA supported the conceptual model and its generalisability across primary cancer sites. After considering all criteria, 12 items were selected representing 10 dimensions: physical functioning (mobility), role functioning, social functioning, emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems. CONCLUSIONS: The HSCS created from QLQ-C30 items is known as the EORTC Quality of Life Utility Measure-Core 10 dimensions (QLU-C10D). The next phase of the QLU-C10D's development involves valuation studies, currently planned or being conducted across the globe.

摘要

相似文献

[1]
QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30.

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[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
Dutch utility weights for the EORTC cancer-specific utility instrument: the Dutch EORTC QLU-C10D.

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[9]
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[10]
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引用本文的文献

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[2]
Comparing EQ-5D-5L and SF-6Dv2 utilities with QLU-C10D utilities in hematologic cancer patients.

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[3]
Validation of the cancer-specific utility measure EORTC QLU-C10D using evidence from four lung cancer trials covering six country value sets.

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[4]
Validation of the Cancer-Specific Preference-Based Measure EORTC QLU-C10D against the Generic Instruments EQ-5D-5L and SF-6Dv2 in a Prospectively Collected Sample of Patients with Cancer in Austria and France.

Pharmacoeconomics. 2025-4-27

[5]
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[6]
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[9]
Cancer-specific utility: clinical validation of the EORTC QLU-C10D in patients with glioblastoma.

Eur J Health Econ. 2024-11-20

[10]
Norwegian and Swedish value sets for the EORTC QLU-C10D utility instrument.

Qual Life Res. 2025-2

本文引用的文献

[1]
Using a discrete choice experiment to value the QLU-C10D: feasibility and sensitivity to presentation format.

Qual Life Res. 2016-3

[2]
Deriving a preference-based utility measure for cancer patients from the European Organisation for the Research and Treatment of Cancer's Quality of Life Questionnaire C30: a confirmatory versus exploratory approach.

Patient Relat Outcome Meas. 2014-11-6

[3]
Testing the measurement invariance of the EORTC QLQ-C30 across primary cancer sites using multi-group confirmatory factor analysis.

Qual Life Res. 2015-1

[4]
Should linking replace regression when mapping from profile-based measures to preference-based measures?

Value Health. 2014-3

[5]
Mapping utilities from cancer-specific health-related quality of life instruments: a review of the literature.

Expert Rev Pharmacoecon Outcomes Res. 2013-12

[6]
Valuing SF-6D Health States Using a Discrete Choice Experiment.

Med Decis Making. 2014-8

[7]
The prevalence and correlates of supportive care needs in testicular cancer survivors: a cross-sectional study.

Psychooncology. 2013-7-3

[8]
An Australian discrete choice experiment to value eq-5d health states.

Health Econ. 2013-6-13

[9]
Docetaxel plus cetuximab as second-line treatment for docetaxel-refractory oesophagogastric cancer: the AGITG ATTAX2 trial.

Br J Cancer. 2013-2-14

[10]
[A meta-analysis of chemotherapy related cognitive impairment in patients with breast cancer].

J Korean Acad Nurs. 2012-10

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