TY - JOUR
T1 - Moderators of the effect of psychosocial interventions on fatigue in women with breast cancer and men with prostate cancer
T2 - Individual patient data meta-analyses
AU - Abrahams, Harriët J.G.
AU - Knoop, Hans
AU - Schreurs, Maartje
AU - Aaronson, Neil K.
AU - Jacobsen, Paul B.
AU - Newton, Robert U.
AU - Courneya, Kerry S.
AU - Aitken, Joanne F.
AU - Arving, Cecilia
AU - Brandberg, Yvonne
AU - Chambers, Suzanne K.
AU - Gielissen, Marieke F.M.
AU - Glimelius, Bengt
AU - Goedendorp, Martine M.
AU - Graves, Kristi D.
AU - Heiney, Sue P.
AU - Horne, Rob
AU - Hunter, Myra S.
AU - Johansson, Birgitta
AU - Northouse, Laurel L.
AU - Oldenburg, Hester S.A.
AU - Prins, Judith B.
AU - Savard, Josée
AU - van Beurden, Marc
AU - van den Berg, Sanne W.
AU - Verdonck-de Leeuw, Irma M.
AU - Buffart, Laurien M.
PY - 2020/11
Y1 - 2020/11
N2 - Objective: Psychosocial interventions can reduce cancer-related fatigue effectively. However, it is still unclear if intervention effects differ across subgroups of patients. These meta-analyses aimed at evaluating moderator effects of (a) sociodemographic characteristics, (b) clinical characteristics, (c) baseline levels of fatigue and other symptoms, and (d) intervention-related characteristics on the effect of psychosocial interventions on cancer-related fatigue in patients with non-metastatic breast and prostate cancer. Methods: Data were retrieved from the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) consortium. Potential moderators were studied with meta-analyses of pooled individual patient data from 14 randomized controlled trials through linear mixed-effects models with interaction tests. The analyses were conducted separately in patients with breast (n = 1091) and prostate cancer (n = 1008). Results: Statistically significant, small overall effects of psychosocial interventions on fatigue were found (breast cancer: β = −0.19 [95% confidence interval (95%CI) = −0.30; −0.08]; prostate cancer: β = −0.11 [95%CI = −0.21; −0.00]). In both patient groups, intervention effects did not differ significantly by sociodemographic or clinical characteristics, nor by baseline levels of fatigue or pain. For intervention-related moderators (only tested among women with breast cancer), statistically significant larger effects were found for cognitive behavioral therapy as intervention strategy (β = −0.27 [95%CI = −0.40; −0.15]), fatigue-specific interventions (β = −0.48 [95%CI = −0.79; −0.18]), and interventions that only targeted patients with clinically relevant fatigue (β = −0.85 [95%CI = −1.40; −0.30]). Conclusions: Our findings did not provide evidence that any selected demographic or clinical characteristic, or baseline levels of fatigue or pain, moderated effects of psychosocial interventions on fatigue. A specific focus on decreasing fatigue seems beneficial for patients with breast cancer with clinically relevant fatigue.
AB - Objective: Psychosocial interventions can reduce cancer-related fatigue effectively. However, it is still unclear if intervention effects differ across subgroups of patients. These meta-analyses aimed at evaluating moderator effects of (a) sociodemographic characteristics, (b) clinical characteristics, (c) baseline levels of fatigue and other symptoms, and (d) intervention-related characteristics on the effect of psychosocial interventions on cancer-related fatigue in patients with non-metastatic breast and prostate cancer. Methods: Data were retrieved from the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) consortium. Potential moderators were studied with meta-analyses of pooled individual patient data from 14 randomized controlled trials through linear mixed-effects models with interaction tests. The analyses were conducted separately in patients with breast (n = 1091) and prostate cancer (n = 1008). Results: Statistically significant, small overall effects of psychosocial interventions on fatigue were found (breast cancer: β = −0.19 [95% confidence interval (95%CI) = −0.30; −0.08]; prostate cancer: β = −0.11 [95%CI = −0.21; −0.00]). In both patient groups, intervention effects did not differ significantly by sociodemographic or clinical characteristics, nor by baseline levels of fatigue or pain. For intervention-related moderators (only tested among women with breast cancer), statistically significant larger effects were found for cognitive behavioral therapy as intervention strategy (β = −0.27 [95%CI = −0.40; −0.15]), fatigue-specific interventions (β = −0.48 [95%CI = −0.79; −0.18]), and interventions that only targeted patients with clinically relevant fatigue (β = −0.85 [95%CI = −1.40; −0.30]). Conclusions: Our findings did not provide evidence that any selected demographic or clinical characteristic, or baseline levels of fatigue or pain, moderated effects of psychosocial interventions on fatigue. A specific focus on decreasing fatigue seems beneficial for patients with breast cancer with clinically relevant fatigue.
KW - breast cancer
KW - cancer
KW - fatigue
KW - individual patient data meta-analysis
KW - moderators
KW - oncology
KW - prostate cancer
KW - psycho-oncology
KW - psychosocial interventions
UR - http://www.scopus.com/inward/record.url?scp=85090114877&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090114877&partnerID=8YFLogxK
U2 - https://doi.org/10.1002/pon.5522
DO - https://doi.org/10.1002/pon.5522
M3 - Review article
C2 - 33448521
SN - 1057-9249
VL - 29
SP - 1772
EP - 1785
JO - Psycho-Oncology
JF - Psycho-Oncology
IS - 11
ER -