OS7.2 Measuring change in health-related quality of life: the added value of analysis on the individual patient level in glioma patients in clinical decision making. (6th September 2019)

• Record Type: Journal Article
• Authors: Coomans, M; Taphoorn, M J B; Aaronson, N; Baumert, B G; van den Bent, M; Bottomley, A; Brandes, A A; Chinot, O; Coens, C; Gorlia, T; Herrlinger, U; Keime-Guibert, F; Malmström, A; Martinelli, F; Stupp, R; Talacchi, A; Weller, M; Wick, W; Reijneveld, J C; Dirven, L
• Is Part Of: Neuro-oncology. Volume 21(2019)Supplement 3
• Page Start: iii14
• Page End: iii14
• Publication Date: 2019-09-06
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noz126.045
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: BACKGROUND: Health-related quality of life (HRQoL) is often used as an outcome in glioma research, reflecting the impact of disease and treatment on a patient's functioning and wellbeing. Data on changes in HRQoL scores may provide important information for clinical decision-making, but different analytical methods may lead to different interpretations of the impact of treatment on HRQoL. This study aimed to examine three different methods to evaluate change in HRQoL, and to study whether these methods result in different interpretations. MATERIAL AND METHODS: HRQoL and sociodemographical/clinical data from 15 randomized clinical trials were combined. Change in HRQoL scores was analyzed in three ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms over time, (2) at the patient level per scale/item by calculating the percentage of patients that deteriorated, improved or remained stable on a scale/item per scale/item, and (3) at the individual patient level combining all scales/items. RESULTS: Baseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level (method 1), only the item 'hair loss' showed a significant and clinically relevant change (i.e. ≥10 points) over time, whereas change scores on the other scales/items showed a statistically significant change only (all p<.001, range in change score: 0.1–6.2). Analyses on the patient level per scale (method 2) indicated that, while a large proportion of patients had stable HRQoL over time (range 27–84%), many patients deteriorated (range: 6–43%) or improved (range: 8–32%) on a specific scale/item. At the individual patient level (method 3), the majority of patients (86%) showed both deterioration and improvement, while only 1% of the patients remained stable on all scales. Clustering on clinical characteristics (WHO performance status, sex, tumor type, type of resection, newly diagnosed versus recurrent tumor and age) did not identify subgroups of patients with a specific pattern of change in their HRQoL score. CONCLUSION: Different analytical methods of changes in HRQoL result in distinct interpretations of treatment effects, all of which may be relevant for clinical decision-making. Additional information about the joint impact of treatment on all outcomes, showing that most patients experience both deterioration and improvement, may help patients and physicians to make the best treatment decision.