Abstract
BackgroundThe minimal important difference (MID) is a useful tool to interpret changes in patients’ health-related quality of life. This study aims to estimate MIDs for interpreting within-patient change for both components of the EQ-5D-5L questionnaire [EQ-Visual Analogue Scale (EQ-VAS) and utility index] and domains of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) for cancer patients.MethodsData were obtained from the Cancer 2015 dataset, a longitudinal cohort of Australian cancer patients. Anchor-based approaches were used to estimate MIDs for the EQ-5D-5L index-based utility index [Australia and the United States (US) tariff sets], EQ-VAS scores, and the EORTC QLQ-C30. Clinical [Eastern Cooperative Oncology Group (ECOG) performance status] and patient-reported (items 29 and 30 of the EORTC QLQ-C30 and the EQ-VAS) anchors were assessed for appropriateness by their correlation strength. Clinical change groups (CCGs) were defined a priori for improvement and deterioration based on estimates used in previous literature. MIDs were estimated via linear regression and distribution-based methods.ResultsFor the index-based utility scores in Australia, the anchor-defined MID estimates were 0.01 to 0.06 for improvement and − 0.04 to -0.03 for deterioration, with a weighted value of 0.03 for improvement and deterioration. The EQ-VAS MID estimate was 5 points for both improvement and deterioration. For the EORTC QLQ-C30, changes of at least 3.64 (improvement) and − 4.28 (deterioration) units on the physical functioning scale, 6.31 (improvement) and − 7.11 (deterioration) units on the role functioning scale, 4.65 (improvement) and − 3.41 (deterioration) units on the emotional functioning scale, and 5.41 (improvement) and − 5.56 (deterioration) units on the social functioning scale were estimated to be meaningful.ConclusionThis study identified lower MIDs for the EQ-5D-5L utility index, EQ-VAS, and EORTC QLQ-C30 domain scores, than those reported previously. The use of a real-world cancer-specific panel dataset may reflect smaller MID estimates that are more applicable to cancer patients in the clinical practice, rather than using MIDs that have been estimated from clinical trials.
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