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Minimal important differences in the EORTC QLQ-C15-PAL to determine meaningful change in palliative advanced cancer
Gillian Bedard1, Liang Zeng1, Liying Zhang1
1Rapid Response Radiotherapy Program, Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada.
Aims:
Quality of life (QOL) is important for advanced cancer patients. Brief questionnaires are advantageous to reduce patient burden. In large clinical trials, statistically significant small changes can be achieved; however, whether such change is clinically relevant is unknown. The purpose of this study was to determine the minimal important differences (MID) of the European Organisation for Research and Treatment of Cancer quality of life core 15 palliative questionnaire (EORTC QLQ-C15-PAL).
Methods:
Patients undergoing palliative radiotherapy completed the EORTC QLQ-C15-PAL at baseline and 1 month later. Anchor and distribution-based assessments were employed to determine the MID associated with this instrument. The anchor of overall QOL was used to determine meaningful change.
Results:
In all, 276 patients were included in MID calculation. Mean age was 65 years and primary lung, breast or prostate cancers were most common. Statistically significant MID for improvement was seen in emotional functioning and pain (20.9 and 15.6, respectively). MID for deterioration required a 20.4, 24.5, 17.1 and 23.0 change in physical functioning, fatigue, pain and appetite loss, respectively, to constitute meaningful change. Distribution-based estimates of MID were closest to the standard error of measurement. MID for brain and bone metastases patients yielded MID larger than previously determined in the incorporation of all patients.
Conclusion:
Meaningful change in the EORTC QLQ-C15-PAL is important for clinicians to determine the impact of treatment on the QOL of patients and can aid in determining the sample size required for clinical trials. Future studies should investigate MID in subgroups using symptom-specific modules.
