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

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.

United States Utility Algorithm for the EORTC QLU-C10D, a Multiattribute Utility Instrument Based on a Cancer-Specific Quality-of-Life Instrument

“…Estimates for model 1 (i.e., unconstrained conditional logit regression) were mostly monotonic; however, the appetite, fatigue, and sleep dimensions showed misordering of the level 3 and 4 estimates. This finding was similar to results of the Australian and UK QLU-C10D valuation studies, 16,21 in which appetite at the highest levels was nonmonotonic, but in which monotonicity was observed for the fatigue and sleep problems dimensions. The monotonicity constraint applied in model 2 did not substantially reduce model fit or the utility decrements for other health dimensions.…”

“…Country-specific value sets for the QLU-C10D are needed to align with national health technology assessment guidelines that recommend value sets reflect local/ national preferences for different aspects of HRQL. 4,12 We focused on general population utility estimates given the more widely used preference for national allocation of health care resources in most countries, 17 despite recent work exploring patient valuations, such as that by Poder et al 18 Value sets for the QLU-C10D are now available for Australia, 16 Germany, 19 Canada, 20 and the United Kingdom, 21 with more forthcoming. These international value sets can be used to assist decision making both in oncology and in a broader context by generating QALYs, which can be used to inform resource allocation across the health care sector.…”

EORTC QLU-C10D value sets for Austria, Italy, and Poland

“…An indication for the potential relevance of cancer-specific symptoms are the decrements found for nausea, bowel problems and fatigue which are consistent with the Australian QLU-C10D valuation [9] as well as those in Germany, the UK [12], and Canada [10].…”

“…QLU-C10D valuations are currently being performed for a range of countries and tariffs have already been published for Australia [9], Canada [10], Germany [11], and the UK [12]. In the present study, we aim to determine the utility weights for health states of the Austrian, Italian, and Polish version of the QLU-C10D.…”

Estimating a Preference-Based Index for Mental Health From the Recovering Quality of Life Measure: Valuation of Recovering Quality of Life Utility Index

“…19 There is a possibility that this may be in part either due to a framing effect or due to the number of MH items in the classification system proportional to the number of PH items. However, previous research has shown that all aspects of health in a classification system do not always receive a sizable utility decrement (see for example 'appetite' in EORTC QLU-C10D UK weights 29 or 'worried' in CHU9D UK weights), 30 meaning that the presence of an item alone does not guarantee a utility decrement, nor does it follow that the larger the number of dimensions the lower the utility values for the health state. Nonetheless, the PH item has a large utility decrement of 0.29 for the most severe level.…”