U.K. utility weights for the EORTC QLU‐C10D

Richard Norman, Rebecca Mercieca‐Bebber, Donna Rowen, John E. Brazier, David Cella, A. Simon Pickard, Deborah J. Street, Rosalie Viney (), Dennis Revicki, Madeleine T. King and On behalf of the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Group and the MAUCa Consortium

Health Economics, 2019, vol. 28, issue 12, 1385-1401

Abstract: The EORTC QLU‐C10D is a new multi‐attribute utility instrument derived from the widely used cancer‐specific quality of life questionnaire, EORTC QLQ‐C30. It contains 10 dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems), each with four levels. The aim of this study was to provide U.K. general population utility weights for the QLU‐C10D. A U.K. online panel was quota‐sampled to align the sample to the general population proportions of sex and age (≥18 years). The online valuation survey included a discrete choice experiment (DCE). Each participant was asked to complete 16 choice‐pairs, each comprising two QLU‐C10D health states plus duration. DCE data were analysed using conditional logistic regression to generate utility weights. Data from 2,187 respondents who completed at least one choice set were included in the DCE analysis. The final U.K. QLU‐C10D utility weights comprised decrements for each level of each health dimension. For nine of the 10 dimensions (all except appetite), the expected monotonic pattern was observed across levels: Utility decreased as severity increased. For the final model, consistent monotonicity was achieved by merging inconsistent adjacent levels for appetite. The largest utility decrements were associated with physical functioning and pain. The worst possible health state (the worst level of each dimension) is −0.083, which is considered slightly worse than being dead. The U.K.‐specific utility weights will enable cost–utility analysis (CUA) for the economic evaluation of new oncology therapies and technologies in the United Kingdom, where CUA is commonly used to inform resource allocation.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:wly:hlthec:v:28:y:2019:i:12:p:1385-1401

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