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Background: The European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30) is a widely used quality-of-life measure in oncology. The ability to translate QLQ-C30 responses into utility scores would further expand its use in medical decision-making. The aims of this study were to: 1) map QLQ-C30 responses onto patient time trade-off utility scores; and 2) compare a multiattribute approach to a global evaluation approach to modeling utility scores. Methods: Two distinct approaches were applied to data from 1432 cancer patients. The multiattribute approach used psychometric analysis and expert input to select a subset of functioning and symptom scale items for modeling. The second approach focused on global health and quality-of-life items based on a conceptual model. Model selection criteria included parsimony, statistical significance and logical consistency of parameter estimates, predictive accuracy, number of states described, and scale range. Results: The optimal multiattribute model included nine variables for five items from different scales, described 144 unique states, predicted values ranging from 0.63 to 1.00, but it had poor predictive accuracy (cross-validation pseudo- R2 = 0.056). The best-fitting global approach-based model described 24 unique states using eight indicators for two items from one scale (plus a constant) and predicted values ranging from 0.17 to 1.00 (cross-validation pseudo- R2 = 0.127). Conclusions: Multiattribute models produced a greater number of unique predicted values, while global models exhibited more desirable statistical properties and a wider range of values. The recommended models will enable users to predict cancer patients’ utilities from existing and future QLQ-C30 data sets. [ABSTRACT FROM AUTHOR]

Several measures have been used or developed to capture the health and well-being of caregivers, including the EQ Health and Well-being (EQ-HWB) and its short form, EQ-HWB-S. This study aimed to evaluate the psychometric properties and construct validity of the EQ-HWB/EQ-HWB-S in a US caregiver population. A cross-sectional survey was conducted involving 504 caregivers. Eligible participants were 18+ years old, provided unpaid care to a relative/friend aged 18+ in the past 6 months, and spent on average of at least 1 hour per week caregiving. Survey included the following measures: EQ-HWB, Adult Social Care Outcomes Toolkit for Carers-Carer, CarerQol, and EQ-5D-5L. Psychometric properties were assessed using response distributions, floor/ceiling effects, Spearman's correlation for convergent validity, and effect sizes (ES) for known-group validity based on caregiving situations and intensity. The average age of caregivers was 49.2 (SD = 15.4), with 57.5% being female. More than half (54.4%) reported high caregiving intensity, and 68.3% lived with the care recipient. The EQ-HWB-S index showed a strong positive correlation with the EQ-5D-5L (r s = 0.72), Adult Social Care Outcomes Toolkit for Carers (r s = 0.54), and CarerQol (r s = 0.54) indices. Notably, the EQ-HWB-S index showed the largest ES among measures in differentiating caregiving scenarios with a large ES for caregiver's general health (d = 1.00) and small ES for caregiving intensity (d = 0.39). Results support construct validity of EQ-HWB and EQ-HWB-S as measures for assessing health and well-being of adult informal caregivers in comparison with other validated instruments. Differing levels of known-group validity across anchors emphasize the importance of selecting appropriate measures for caregivers, depending on research question and/or intervention aims. • Various preference-based measures, including Adult Social Care Outcomes Toolkit for Carers-Carer, CarerQol-7D, and EQ-5D-5L, can be used to assess the health and quality of life of informal caregivers. The EQ Health and Well-being (EQ-HWB) was developed as a broader measure of health and well-being, including for caregivers. However, its psychometric properties have yet to be examined in relation to other validated measures, specifically in caregivers. • This study evaluated the psychometric properties of EQ-HWB and its short form, EQ-HWB-S, in a heterogeneous US caregiver population, demonstrating construct validity with other preference-based measures. Notably, care recipients' self-perceived burden to caregivers proved to be a valid anchor-based criterion for distinguishing groups based on the influence of caregiving on their health and well-being. • The findings highlight the importance of selecting appropriate measures for assessing health and well-being of informal caregivers. This choice should depend on the specific aims of the intervention being evaluated and perspective of economic evaluation. Using the appropriate measures can lead to more accurate assessments of the effectiveness and cost-effectiveness of interventions with impacts on broader quality of life and well-being, which is essential for informed decision making in healthcare policy. [ABSTRACT FROM AUTHOR]