The EORTC QLU-C10D distinguished better between cancer patients and the general population than PROPr and EQ-5D-5L in a cross-sectional study
The assessment of dimensions of health-related quality of life (HRQoL), such as physical functioning or depression, is important to cancer patients and physicians for treatment and side effect monitoring. Descriptive HRQoL is measured by patient-reported outcomes measures (PROM). The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 questionnaire and the Patient-Reported Outcome Measurement Information System (PROMIS) are the most common PROM in the clinical HRQoL assessment. In recent years, multidimensional preference-based HRQoL measures were developed using these PROM as dimensions. These preference-based measures, also referred to as health state utility (HSU) scores, are needed for economic evaluations of treatments. The QLQ-C30's corresponding HSU score is the Quality of Life Utility measure-Core 10 Dimensions (QLU-C10D), and PROMIS' HSU score is the PROMIS preference score (PROPr). Both new HSU scores are frequently compared to the well-established EuroQoL-5-dimensions-5-levels (EQ-5D-5L). They all conceptualize HSU differently, as they assess different dimensions of HRQoL und use different models. Both the QLU-C10D and the PROPr have thus shown systematic differences to the EQ-5D-5L but these were largely consistent across the subgroups. Convergent and known groups validity can therefore be considered established. However, as HSU is a multidimensional construct, it remains unclear how differences in its dimensions, for example, its descriptive scales, contribute to differences in HSU scores. This is of importance as it is the descriptive scales that measure clinical HRQoL. We investigated this question by assessing each dimension's ability to distinguish between a sample of 484 cancer patients and the German general population. We could show that the ability to distinguish depended on the domain: for example, for depression, the QLU-C10D and EQ-5D-5L distinguished clearer, while for physical function, PROMIS did. Overall, the QLU-C10D and its dimensions distinguish best between cancer patients and general population.
Authors
- Sandra Nolte (ORCID: https://orcid.org/0000-0001-6185-9423)
- Alexander Obbarius (ORCID: https://orcid.org/0000-0003-2348-1348)
- José M Valderas (ORCID: https://orcid.org/0000-0002-9299-1555)
- Christoph Paul Klapproth (ORCID: https://orcid.org/0000-0001-6057-5920)
- Matthias Rose (ORCID: https://orcid.org/0000-0001-5233-3139)
- Annika Döhmen (ORCID: https://orcid.org/0000-0002-9836-2557)
- Chris Sidey‐Gibbons (ORCID: https://orcid.org/0000-0002-4732-7305)
- Milan Kock (ORCID: https://orcid.org/0000-0002-8319-8379)
- Felix Fischer (ORCID: https://orcid.org/0000-0002-9693-6676)
- Ulrich Keilholz (ORCID: https://orcid.org/0000-0001-6773-9406)
- Kathrin Rieger
- Jens Rohde (ORCID: https://orcid.org/0000-0002-2834-066X)
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- National University of Singapore (SG)
- Eastern Health (AU)
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- National University Health System (SG)
- Franklin University (US)
- Charité - Universitätsmedizin Berlin (DE)
Publication Details
- Journal
- Journal of Clinical Epidemiology
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1016/j.jclinepi.2024.111592
- Citations
- 1
- Primary Topic
- Health Systems, Economic Evaluations, Quality of Life
- Type
- article
- Field-Weighted Citation Impact
- 1.13
Funders
- European Organisation for Research and Treatment of Cancer