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

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An Erratum to this article was published on 08 April 2016

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.

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Acknowledgments

The MAUCa Consortium, in addition to those named as authors, consists of the following members, all of whom made some contribution to the research reported in this paper: Stuart Peacock, Helen McTaggart-Cowan, Julie Pallant and Deborah Street. We would also like to thank the following people for their generosity in contributing data for secondary analysis: U. Abacioğlu, J. Arraras, J. Blazeby, W.-C. Chie, S. Clarke, S. Kaasa, P. Klepstad, Millennium Pharmaceuticals, K. Mystakidou, S. Peacock, R. Schwarz, N. Scott, N. Tebbutt, G. Velikova and the Australian Gastro-Intestinal Trials Group. This research was supported by a National Health and Medical Research Council (Australia) Project Grant (632662). A/Professor Janda was supported by a NHMRC career development award 1045247. Professor King was supported by the Australian Government through Cancer Australia.

Funding

This research was supported by a National Health and Medical Research Council (Australia) Project Grant (632662). Professor King was supported by the Australian Government through Cancer Australia. Dr. Norman was supported by a NHMRC early career research fellowship (1069732).

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Authors and Affiliations

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

    M. T. King & D. S. J. Costa

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

    M. T. King

  3. Division of Psychosocial Research & Epidemiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    N. K. Aaronson

  4. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK

    J. E. Brazier, D. Rowen & T. A. Young

  5. Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    D. F. Cella

  6. Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK

    P. M. Fayers

  7. Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

    P. M. Fayers

  8. Chris O’Brien Lifehouse, Sydney Medical School, University of Sydney, Sydney, NSW, Australia

    P. Grimison

  9. School of Public Health, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia

    M. Janda

  10. Department of Psychiatry and Psychotherapy, Innsbruck Medical University, Innsbruck, Austria

    G. Kemmler

  11. School of Public Health, Curtin University, Perth, WA, Australia

    R. Norman

  12. Centre for Health Economics Research and Evaluation (CHERE), University of Technology Sydney (UTS), Sydney, NSW, Australia

    R. Norman & R. Viney

  13. Department of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, Chicago, IL, USA

    A. S. Pickard

  14. Leeds Institute of Cancer and Pathology, University of Leeds, St James’s University Hospital, Leeds, UK

    G. Velikova

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  1. M. T. King
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  2. D. S. J. Costa
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  9. G. Kemmler
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  10. R. Norman
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  13. G. Velikova
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  14. T. A. Young
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Correspondence to M. T. King.

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The authors declare they do not have conflicts of interest.

Ethical approval

The study was approved by the University of Sydney Human Research Ethics Committee, approval number 2012/2444. All study procedures involving human participants were in accordance with the ethical standards of institutional and national research committees and with the 1964 Helsinki Declaration and its later amendments and comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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King, M.T., Costa, D.S.J., Aaronson, N.K. et al. QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30. Qual Life Res 25, 625–636 (2016). https://doi.org/10.1007/s11136-015-1217-y

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