TY - JOUR
T1 - Moderators of Exercise Effects on Cancer-related Fatigue
T2 - A Meta-analysis of Individual Patient Data
AU - Van Vulpen, Jonna K.
AU - Sweegers, Maike G.
AU - Peeters, Petra H.M.
AU - Courneya, Kerry S.
AU - Newton, Robert U.
AU - Aaronson, Neil K.
AU - Jacobsen, Paul B.
AU - Galvaõ, Daniel A.
AU - Chinapaw, Mai J.
AU - Steindorf, Karen
AU - Irwin, Melinda L.
AU - Stuiver, Martijn M.
AU - Hayes, Sandi
AU - Griffith, Kathleen A.
AU - Mesters, Ilse
AU - Knoop, Hans
AU - Goedendorp, Martine M.
AU - Mutrie, Nanette
AU - Daley, Amanda J.
AU - McConnachie, Alex
AU - Bohus, Martin
AU - Thorsen, Lene
AU - Schulz, Karl Heinz
AU - Short, Camille E.
AU - James, Erica L.
AU - Plotnikoff, Ronald C.
AU - Schmidt, Martina E.
AU - Ulrich, Cornelia M.
AU - Van Beurden, Marc
AU - Oldenburg, Hester S.
AU - Sonke, Gabe S.
AU - Van Harten, Wim H.
AU - Schmitz, Kathryn H.
AU - Winters-Stone, Kerri M.
AU - Velthuis, Miranda J.
AU - Taaffe, Dennis R.
AU - Van Mechelen, Willem
AU - Kersten, Marie José
AU - Nollet, Frans
AU - Wenzel, Jennifer
AU - Wiskemann, Joachim
AU - Verdonck-De Leeuw, Irma M.
AU - Brug, Johannes
AU - May, Anne M.
AU - Buffart, Laurien M.
N1 - Publisher Copyright:
© Lippincott Williams & Wilkins.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - 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- A nd 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.
AB - 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- A nd 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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U2 - 10.1249/MSS.0000000000002154
DO - 10.1249/MSS.0000000000002154
M3 - Article
C2 - 31524827
AN - SCOPUS:85074763027
SN - 0195-9131
VL - 52
SP - 303
EP - 314
JO - Medicine and science in sports and exercise
JF - Medicine and science in sports and exercise
IS - 2
ER -