Abstract
PurposeIt has been argued that generic health-related quality of life measures are not sensitive to certain disease-specific improvements; condition-specific preference-based measures may offer a better alternative. This paper assesses the validity, responsiveness and sensitivity of a cancer-specific preference-based measure, the EORTC-8D, relative to the EQ-5D-3L.MethodsA longitudinal prospective population-based cancer genomic cohort, Cancer 2015, was utilised in the analysis. EQ-5D-3L and the EORTC QLQ-C30 (which gives EORTC-8D values) were asked at baseline (diagnosis) and at various follow-up points (3 months, 6 months, 12 months). Baseline values were assessed for convergent validity, ceiling effects, agreement and sensitivity. Quality-adjusted life-years (QALYs) were estimated and similarly assessed. Multivariate regression analyses were employed to understand the determinants of the difference in QALYs.ResultsComplete case analysis of 1678 patients found that the EQ-5D-3L values at baseline were significantly lower than the EORTC-8D values (0.748 vs 0.829, p < 0.001). While the correlation between the instruments was high, agreement between the instruments was poor. The baseline health state values using both instruments were found to be sensitive to a number of patient and disease characteristics, and discrimination between disease states was found to be similar. Mean generic QALYs (estimated using the EQ-5D-3L) were significantly lower than condition-specific QALYs (estimated using the EORTC-8D) (0.860 vs 0.909, p < 0.001). The discriminatory power of both QALYs was similar.ConclusionsWhen comparing a generic and condition-specific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated QALYs over time for cancer patients. The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably.
Highlights
Cost-utility analyses (CUA) require preference-based measures (PBMs) of outcome
When comparing a generic and conditionspecific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated Qualityadjusted life-years (QALYs) over time for cancer patients
The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably
Summary
Cost-utility analyses (CUA) require preference-based measures (PBMs) of outcome. Traditionally PBMs, socalled multi-attribute utility instruments (MAUIs), have been generic. While the use of the same measure across a range of diseases and conditions increases comparability (what NICE refers to as a need for consistency) when informing decisions, there have been criticisms that these generic measures are not sensitive to certain diseasespecific characteristics [3,4,5]. While using PBMs in some diseases may mean that important clinical and patient quality of life changes are missed entirely, in other disease areas it may be that effects are found, but the magnitude of these is underestimated. That is, it is not a simple question of whether PBMs are sensitive, but whether they are sensitive enough?
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
