Deriving a preference-based measure for cancer using the EORTC QLQ-C30

Abstract

Background: The EORTC QLQ-C30 is one of the most commonly used measures in cancer but in its current form cannot be used in economic evaluation as it does not incorporate preferences. Methods and results: We address this gap by estimating a preference-based single index for cancer from the EORTC QLQ-C30 for use in economic evaluation. 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 from the QLQ-C30 that is amenable to valuation. The resulting health state classification system has 8 dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue and sleep disturbance, nausea, and constipation and diarrhoea) with 4 or 5 levels each. A valuation study was conducted of 350 members of the UK general population using ranking and time trade-off. Mean and individual level additive multivariate regression models including the episodic random utility model were fitted to the valuation data to derive preference weights for the classification system. Mean absolute error ranges from 0.046 to 0.054 and models have few inconsistencies (0 to 2) in estimated preference weights. Conclusions: We conclude that it is feasible to derive a preference-based measure from the EORTC QLQ-C30 for use in economic evaluation, but this work needs to be extended to other countries and replicated across other patient groups

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    This paper was published in White Rose Research Online.

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