Moderators of Exercise Effects on Cancer-related Fatigue: A Meta-analysis of Individual Patient Data.
AuthorVAN Vulpen, JK; Sweegers, MG; Peeters, PHM; Courneya, KS; Newton, RU; Aaronson, NK; Jacobsen, PB; Galvão, DA; Chinapaw, MJ; Steindorf, K; ...
Source TitleMedicine and Science in Sports and Exercise
PublisherOvid Technologies (Wolters Kluwer Health)
University of Melbourne Author/sShort, Camille
AffiliationMelbourne School of Psychological Sciences
Document TypeJournal Article
CitationsVAN Vulpen, J. K., Sweegers, M. G., Peeters, P. H. M., Courneya, K. S., Newton, R. U., Aaronson, N. K., Jacobsen, P. B., Galvão, D. A., Chinapaw, M. J., Steindorf, K., Irwin, M. L., Stuiver, M. M., Hayes, S., Griffith, K. A., Mesters, I., Knoop, H., Goedendorp, M. M., Mutrie, N., Daley, A. J. ,... Buffart, L. M. (2020). Moderators of Exercise Effects on Cancer-related Fatigue: A Meta-analysis of Individual Patient Data.. Med Sci Sports Exerc, 52 (2), pp.303-314. https://doi.org/10.1249/MSS.0000000000002154.
Access StatusAccess this item via the Open Access location
Open Access URLPublished version
Open Access at PMChttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC6962544
PURPOSE: Fatigue is a common and potentially disabling symptom in patients with cancer. It can often be effectively reduced by exercise. Yet, effects of exercise interventions might differ across subgroups. We conducted a meta-analysis using individual patient data of randomized controlled trials (RCT) to investigate moderators of exercise intervention effects on cancer-related fatigue. METHODS: We used individual patient data from 31 exercise RCT worldwide, representing 4366 patients, of whom 3846 had complete fatigue data. We performed a one-step individual patient data meta-analysis, using linear mixed-effect models to analyze the effects of exercise interventions on fatigue (z score) and to identify demographic, clinical, intervention- and exercise-related moderators. Models were adjusted for baseline fatigue and included a random intercept on study level to account for clustering of patients within studies. We identified potential moderators by testing their interaction with group allocation, using a likelihood ratio test. RESULTS: Exercise interventions had statistically significant beneficial effects on fatigue (β = -0.17; 95% confidence interval [CI], -0.22 to -0.12). There was no evidence of moderation by demographic or clinical characteristics. Supervised exercise interventions had significantly larger effects on fatigue than unsupervised exercise interventions (βdifference = -0.18; 95% CI -0.28 to -0.08). Supervised interventions with a duration ≤12 wk showed larger effects on fatigue (β = -0.29; 95% CI, -0.39 to -0.20) than supervised interventions with a longer duration. CONCLUSIONS: In this individual patient data meta-analysis, we found statistically significant beneficial effects of exercise interventions on fatigue, irrespective of demographic and clinical characteristics. These findings support a role for exercise, preferably supervised exercise interventions, in clinical practice. Reasons for differential effects in duration require further exploration.
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