Australian Utility Weights for the EORTC QLU-C10D, a Multi-Attribute Utility Instrument Derived from the Cancer-Specific Quality of Life Questionnaire, EORTC QLQ-C30

Abstract

BackgroundThe EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely used cancer-specific quality-of-life (QOL) questionnaire, EORTC QLQ-C30. The QLU-C10D contains ten dimensions (Physical, Role, Social and Emotional Functioning; Pain, Fatigue, Sleep, Appetite, Nausea, Bowel Problems), each with four levels. To be used in cost-utility analysis, country-specific valuation sets are required.ObjectiveThe aim of this study was to provide Australian utility weights for the QLU-C10D.MethodsAn Australian online panel was quota-sampled to ensure population representativeness by sex and age (≥ 18 years). Participants completed a discrete choice experiment (DCE) consisting of 16 choice-pairs. Each pair comprised two QLU-C10D health states plus life expectancy. Data were analysed using conditional logistic regression, parameterised to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each QOL dimension-level coefficient to the coefficient on life expectancy.ResultsA total of 1979 panel members opted in, 1904 (96%) completed at least one choice-pair, and 1846 (93%) completed all 16 choice-pairs. Dimension weights were generally monotonic: poorer levels within each dimension were generally associated with greater utility decrements. The dimensions that impacted most on choice were, in order, Physical Functioning, Pain, Role Functioning and Emotional Functioning. Oncology-relevant dimensions with moderate impact were Nausea and Bowel Problems. Fatigue, Trouble Sleeping and Appetite had relatively small impact. The value of the worst health state was -0.096, somewhat worse than death.ConclusionsThis study provides the first country-specific value set for the QLU-C10D, which can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30, prospectively and retrospectively.Electronic supplementary materialThe online version of this article (doi:10.1007/s40273-017-0582-5) contains supplementary material, which is available to authorized users.

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

“…The unconstrained regression reported in Model 1 is largely monotonic with the exception of the higher levels of appetite. This effect was also seen in the Australian survey where Levels 3 and 4 were inconsistent in the unconstrained model (King et al, 2018). As yet, it is uncertain why this pattern occurs.…”

“…The study used the valuation protocol successfully developed for the Australian valuation of the QLU‐C10D (King et al, ), with modifications only to the participant demographic section. The DCE component of the valuation survey was informed by previous valuation studies for the EQ‐5D‐3L and SF‐6D instruments (Norman et al, ; Viney et al, ).…”

“…To avoid artefactual confounding across countries, the Multi‐Attribute Utility in Cancer Consortium derived a standard method for valuing the EORTC QLU‐C10D in the general population samples, described below. Using this method, we have estimated value sets in Australia (King et al, ), Europe (Kemmler et al, ), and Canada (McTaggart‐Cowan et al, ). The aim of this current paper is to apply this valuation method in a U.K. general population sample to produce U.K.‐specific utility weights for the QLU‐C10D.…”

“…The EORTC QLU-C10D descriptive system has been valued in an Australian general population sample (King et al, 2018;Norman et al, 2016). However, preferences for health may differ across countries (e.g., see Ferreira, Ferreira, Rowen, & Brazier, 2011;Norman et al, 2009).…”

New challenges in psycho‐oncology: Economic evaluation of psychosocial services in cancer: Challenges and best practice recommendations

“…The EORTC recommends the use of the new QLU‐C10D instrument over the EORTC‐8D, as it has broader dimensions and was developed using a broader cancer population; however, additional work is required to generate valuations (ie, weights) and to validate this instrument . Of note is that for the QLU‐C10D, an Australian utility scoring algorithm was published recently . Scoring algorithms for utility weights should be based on the population preferences of the country where the decision making will occur.…”