QLU-C10D: a health state classification system for a multiattribute utility measure based on the EORTC QLQ-C30
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. Se...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Journal Article |
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Springer International Publishing
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/38395 |
| _version_ | 1848755309184548864 |
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| author | King, M. Costa, D. Aaronson, N. Brazier, J. Cella, D. Fayers, P. Grimison, P. Janda, M. Kemmler, G. Norman, Richard Pickard, A. Rowen, D. Velikova, G. Young, T. Viney, R. |
| author_facet | King, M. Costa, D. Aaronson, N. Brazier, J. Cella, D. Fayers, P. Grimison, P. Janda, M. Kemmler, G. Norman, Richard Pickard, A. Rowen, D. Velikova, G. Young, T. Viney, R. |
| author_sort | King, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T08:54:15Z |
| format | Journal Article |
| id | curtin-20.500.11937-38395 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:54:15Z |
| publishDate | 2016 |
| publisher | Springer International Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-383952018-03-29T09:07:10Z QLU-C10D: a health state classification system for a multiattribute utility measure based on the EORTC QLQ-C30 King, M. Costa, D. Aaronson, N. Brazier, J. Cella, D. Fayers, P. Grimison, P. Janda, M. Kemmler, G. Norman, Richard Pickard, A. Rowen, D. Velikova, G. Young, T. Viney, R. 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. 2016 Journal Article http://hdl.handle.net/20.500.11937/38395 10.1007/s11136-015-1217-y Springer International Publishing restricted |
| spellingShingle | King, M. Costa, D. Aaronson, N. Brazier, J. Cella, D. Fayers, P. Grimison, P. Janda, M. Kemmler, G. Norman, Richard Pickard, A. Rowen, D. Velikova, G. Young, T. Viney, R. QLU-C10D: a health state classification system for a multiattribute utility measure based on the EORTC QLQ-C30 |
| title | QLU-C10D: a health state classification system for a multiattribute utility measure based on the EORTC QLQ-C30 |
| title_full | QLU-C10D: a health state classification system for a multiattribute utility measure based on the EORTC QLQ-C30 |
| title_fullStr | QLU-C10D: a health state classification system for a multiattribute utility measure based on the EORTC QLQ-C30 |
| title_full_unstemmed | QLU-C10D: a health state classification system for a multiattribute utility measure based on the EORTC QLQ-C30 |
| title_short | QLU-C10D: a health state classification system for a multiattribute utility measure based on the EORTC QLQ-C30 |
| title_sort | qlu-c10d: a health state classification system for a multiattribute utility measure based on the eortc qlq-c30 |
| url | http://hdl.handle.net/20.500.11937/38395 |