Journal Article

DKFZ-2019-02256

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Moderators of Exercise Effects on Cancer-related Fatigue: A Meta-analysis of Individual Patient Data.

van 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.DKFZ* ; Irwin, M. L. ; Stuiver, M. M. ; Hayes, S. ; Griffith, K. A. ; Mesters, I. ; Knoop, H. ; Goedendorp, M. M. ; Mutrie, N. ; Daley, A. J. ; McConnachie, A. ; Bohus, M. ; Thorsen, L. ; Schulz, K.-H. ; Short, C. E. ; James, E. L. ; Plotnikoff, R. C. ; Schmidt, M. E.DKFZ* ; Ulrich, C. M. ; van Beurden, M. ; Oldenburg, H. S. ; Sonke, G. S. ; van Harten, W. H. ; Schmitz, K. H. ; Winters-Stone, K. M. ; Velthuis, M. J. ; Taaffe, D. R. ; van Mechelen, W. ; Kersten, M. J. ; Nollet, F. ; Wenzel, J. ; Wiskemann, J. ; Verdonck-de Leeuw, I. M. ; Brug, J. ; May, A. M. ; Buffart, L. M.

2020
Ovid [s.l.]

This record in other databases:  

Please use a persistent id in citations: doi:10.1249/MSS.0000000000002154

Abstract: 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 (RCTs) to investigate moderators of exercise intervention effects on cancer-related fatigue.We used individual patient data from 31 exercise RCTs worldwide, representing 4,366 patients, of whom 3,846 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.Exercise interventions had statistically significant beneficial effects on fatigue (β= -0.17 [95% confidence interval (CI) -0.22;-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;-0.08]). Supervised interventions with a duration ≤12 weeks showed larger effects on fatigue (β= -0.29 [95% CI -0.39;-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.PROSPERO, CRD42013003805.

Note: 2020 Feb;52(2):303-314

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Contributing Institute(s):

1. Bewegung, Präventionsforschung und Krebs (C110)

Research Program(s):

1. 313 - Cancer risk factors and prevention (POF3-313) (POF3-313)

Appears in the scientific report 2020

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Database coverage:
; Allianz-Lizenz ; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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