Preliminary Validation of an Optimally Weighted Patient-Based Utility Index by Application to Randomized Trials in Breast Cancer |
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Authors: | Peter S. Grimison BSc MBBS MPH FRACP R. John Simes BSc MBBS MD SM FRACP H. Malcolm Hudson BSc PhD Martin R. Stockler MBBS MSc FRACP |
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Affiliation: | NHMRC Clinical Trials Centre, University of Sydney, Sydney, Australia;;Department of Statistics, Macquarie University, Sydney, Australia;;Sydney Cancer Centre, Royal Prince Alfred Hospital, Camperdown, Australia |
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Abstract: | ObjectivesTo optimize, apply, and validate a scoring algorithm that provides a utility index from a cancer-specific quality of life questionnaire called the Utility-Based Questionnaire-Cancer (UBQ-C) using data sets from randomized trials in breast cancer. The index is designed to reflect the perspective of cancer patients in a specific clinical context so as to best inform clinical decisions.MethodsWe applied the UBQ-C scoring algorithm to trials of chemotherapy for advanced (n = 325) and early (n = 126) breast cancer. The algorithm converts UBQ-C subscales into a subset index, and combines it with a global health status item into an overall HRQL index, which is then converted to a utility index using a power transformation. The optimal subscale weights were determined by their correlations with the global scale in the relevant data set. The validity of the utility index was tested against other patient characteristics.ResultsOptimal weights (range 0–1) for the subset index in advanced (early) breast cancer were: physical function 0.20 (0.09); social/usual activities 0.23 (0.25); self-care 0.04 (0.01); and distresses 0.53 (0.64). Weights for the overall HRQL index were health status 0.66 (0.63) and subset index 0.34 (0.37). The utility index discriminated between breast cancer that was advanced rather than early (means 0.88 vs. 0.94, P < 0.0001) and was responsive to the toxic effects of chemotherapy in early breast cancer (mean change 0.07, P < 0.0001).ConclusionsThe scoring algorithm for the UBQ-C utility index can be optimized in different clinical contexts to reflect the relative importance of different aspects of quality of life to the patients in a trial. It can be used to generate sensitive and responsive utility scores, and quality-adjusted life-years that can be used within a trial to compare the net benefit of treatments and inform clinical decision-making. |
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Keywords: | cancer health-state utility health-related quality of life patient-derived preferences |
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