• Amar U Kishan, Pin-Chieh Wang, Jamal Sharif, Patrick A Kupelian, Michael L Steinberg, and Susan A McCloskey.
• Department of Radiation Oncology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.
• Int. J. Radiat. Oncol. Biol. Phys. 2016 Jul 1; 95 (3): 946-955.

PurposeTo assess the magnitude and predictors of patient-reported fatigue among breast cancer patients receiving radiation therapy (RT).Methods And MaterialsPatients receiving breast RT completed a survey querying fatigue at each weekly on-treatment visit. Patient-reported fatigue severity and interference was assessed on an ordinal scale of 0 to 4, using a validated scoring system. Baseline anxiety and depression scores were also obtained. The kinetics of mean fatigue scores per week and the maximum fatigue scores over the course of the entire treatment were assessed, and clinical predictors were identified by univariate and multivariate regression.ResultsThe average fatigue severity and interference scores were 0.6 and 0.46. The average fatigue scores increased to an equivalent extent from week to week, with expected increases of 0.99 in fatigue severity and 0.85 in interference over 7 weeks. Patients treated with hypofractionated RT (HF-RT) versus conventionally fractionated RT (CF-RT) had significantly fewer maximum fatigue severity or interference scores that were >2 (ie, severe or very severe; 29% vs 10% for severity, and 26% vs 8% for interference, P<.01). Age ≤45 years, presence of psychiatric/pain-related comorbidities, and baseline sadness and anxiety severity were predictive of average and maximum fatigue scores (P<.05), but variables related to treatment intensity (eg, mastectomy vs lumpectomy, chemotherapy use, radiation target volumes) and other host factors (working, children, marital status, proximity to RT facility) were not.ConclusionPatient-reported fatigue modestly increases over RT courses, with less maximum fatigue reported with HF-RT. Younger age and baseline sadness, anxiety, and psychiatric/pain-related comorbidities are powerful predictors of fatigue, whereas other factors, such as treatment intensity, are not. Future studies will investigate interventions for patients at high risk for fatigue.Copyright © 2016 Elsevier Inc. All rights reserved.

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