OBJECTIVE: The European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30) is one of the most commonly used measures in cancer care but in its current form cannot be used in economic evaluation because it does not incorporate preferences. We address this gap by estimating a preference-based measure for cancer from the EORTC QLQ-C30. METHODS: Factor analysis, Rasch analysis, and other psychometric analyses were undertaken on a clinical trial dataset of 655 patients with multiple myeloma to derive a health state classification system amenable to valuation. Second a valuation study was conducted of 350 members of the UK general population using time trade-off. Mean and individual-level multivariate regression models were fitted to derive preference weights for the classification system. RESULTS: The health state classification system has eight dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue and sleep disturbance, nausea, constipation, and diarrhea) with four or five levels each. Regression models have few inconsistencies (0 to 2) in estimated preference weights and small mean absolute error ranges (0.046 to 0.054). CONCLUSIONS: It is feasible to derive a preference-based measure from the EORTC QLQ-C30 for use in economic evaluation. Future research will extend this to other countries and replicate across other patient groups.
OBJECTIVE: The European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30) is one of the most commonly used measures in cancer care but in its current form cannot be used in economic evaluation because it does not incorporate preferences. We address this gap by estimating a preference-based measure for cancer from the EORTC QLQ-C30. METHODS: Factor analysis, Rasch analysis, and other psychometric analyses were undertaken on a clinical trial dataset of 655 patients with multiple myeloma to derive a health state classification system amenable to valuation. Second a valuation study was conducted of 350 members of the UK general population using time trade-off. Mean and individual-level multivariate regression models were fitted to derive preference weights for the classification system. RESULTS: The health state classification system has eight dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue and sleep disturbance, nausea, constipation, and diarrhea) with four or five levels each. Regression models have few inconsistencies (0 to 2) in estimated preference weights and small mean absolute error ranges (0.046 to 0.054). CONCLUSIONS: It is feasible to derive a preference-based measure from the EORTC QLQ-C30 for use in economic evaluation. Future research will extend this to other countries and replicate across other patient groups.
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