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

  • J.K. Van Vulpen
  • , M.G. Sweegers
  • , P.H.M. Peeters
  • , K.S. Courneya
  • , R.U. Newton
  • , N.K. Aaronson
  • , P.B. Jacobsen
  • , D.A. Galvao
  • , M.J. Chinapaw
  • , K. Steindorf
  • , M.L. Irwin
  • , M.M. Stuiver
  • , S. Hayes
  • , K.A. Griffith
  • , I. Mesters
  • , H. Knoop
  • , M.M. Goedendorp
  • , N. Mutrie
  • , A.J. Daley
  • , A. McConnachie
  • M. Bohus, L. Thorsen, K.H. Schulz, C.E. Short, E.L. James, R.C. Plotnikoff, M.E. Schmidt, C.M. Ulrich, M. Van Beurden, H.S. Oldenburg, G.S. Sonke, W.H. Van Harten, K.H. Schmitz, K.M. Winters-Stone, M.J. Velthuis, D.R. Taaffe, W. Van Mechelen, M.J. Kersten, F. Nollet, J. Wenzel, J. Wiskemann, I.M. Verdonck-de Leeuw, J. Brug, A.M. May, L.M. Buffart*
*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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 (beta = -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 (beta (difference) = -0.18; 95% CI -0.28 to -0.08). Supervised interventions with a duration <= 12 wk showed larger effects on fatigue (beta = -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 - 1 Feb 2020

Keywords

  • adjuvant chemotherapy
  • aerobic exercise
  • androgen deprivation therapy
  • breast-cancer
  • cancer
  • cardiorespiratory fitness
  • cognitive-behavioral therapy
  • exercise
  • fatigue
  • individual patient data meta-analysis
  • physical-exercise
  • prostate-cancer
  • quality-of-life
  • randomized controlled-trial
  • FATIGUE
  • PHYSICAL-EXERCISE
  • RANDOMIZED CONTROLLED-TRIAL
  • CANCER
  • BREAST-CANCER
  • CARDIORESPIRATORY FITNESS
  • COGNITIVE-BEHAVIORAL THERAPY
  • PROSTATE-CANCER
  • AEROBIC EXERCISE
  • QUALITY-OF-LIFE
  • ADJUVANT CHEMOTHERAPY
  • EXERCISE
  • INDIVIDUAL PATIENT DATA META-ANALYSIS
  • ANDROGEN DEPRIVATION THERAPY

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