Moderators of Exercise Effects on Cancer-related Fatigue: A Meta-analysis of Individual Patient Data

Jonna K VAN Vulpen, Maike G Sweegers, Petra H M Peeters, Kerry S Courneya, Robert U Newton, Neil K Aaronson, Paul B Jacobsen, Daniel A Galvão, Mai J Chinapaw, Karen Steindorf, Melinda L Irwin, Martijn M Stuiver, Sandi Hayes, Kathleen A Griffith, Ilse Mesters, Hans Knoop, Martine M Goedendorp, Nanette Mutrie, Amanda J Daley, Alex McConnachieMartin Bohus, Lene Thorsen, Karl-Heinz Schulz, Camille E Short, Erica L James, Ronald C Plotnikoff, Martina E Schmidt, Cornelia M Ulrich, Marc VAN Beurden, Hester S Oldenburg, Gabe S Sonke, Wim H VAN Harten, Kathryn H Schmitz, Kerri M Winters-Stone, Miranda J Velthuis, Dennis R Taaffe, Willem VAN Mechelen, Marie José Kersten, Frans Nollet, Jennifer Wenzel, Joachim Wiskemann, Irma M Verdonck-DE Leeuw, Johannes Brug, Anne M May, Laurien M Buffart*

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    60 Citations (Scopus)
    85 Downloads (Pure)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)303-314
    Number of pages12
    JournalMedicine and Science in Sports and Exercise
    Volume52
    Issue number2
    DOIs
    Publication statusPublished - Feb-2020

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