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Background: Cancer-related fatigue is one of the most common and distressing symptoms in pediatric oncology, yet its assessment and management remain insufficient. This study aimed to characterize trajectories of cancer-related fatigue in children and adolescents undergoing cancer treatment and to identify diagnosis- and therapy-specific fatigue predictors for personalized supportive care. Methods: In this prospective single-center cohort study, 104 pediatric cancer patients receiving chemotherapy (0-18 years) were enrolled at the Medical University of Innsbruck between May 1, 2020 and December 31, 2024. Daily symptom reports (patient or observer-reported) were collected via the ePROtect app and fatigue was scored 0-100, with lower values indicating greater burden. Patients were followed from diagnosis through the end of intensive therapy, and trajectories of cancer-related fatigue were analyzed across diagnostic groups and treatment phases using Locally Estimated Scatterplot Smoothing and linear mixed-effects models. Findings: In total, 11,602 daily cancer-related fatigue assessments were completed, with a median completion rate of 56·1%. Worst fatigue at diagnosis was seen in non-Hodgkin lymphoma (median: 54·2; interquartile range (IQR): 25·0, 75·0) and acute myeloid leukemia patients (median: 56·2; IQR: 33·3, 66·7); least in central nervous system tumor patients (median: 91·7; IQR: 75·0, 100). Glucocorticoid exposure was strongly associated with fatigue, especially in patients with acute lymphoblastic leukemia during steroid-intensive phases. Cancer-related fatigue was minimal during outpatient care but worsened during unplanned hospital admissions. Immunotherapy phases were associated with significant cancer-related fatigue improvement. Distinct fatigue patterns were observed across diagnoses and treatment protocols. Interpretation: Daily symptom monitoring reveals dynamic, diagnosis- and therapy-specific patterns of cancer-related fatigue in pediatric oncology patients. Glucocorticoid intensity and acute clinical events tend to be key drivers of fatigue burden. Integrating real-time symptom monitoring into clinical workflows helps identify high-risk periods for cancer-related fatigue and supports personalized supportive care to improve overall well-being in children and adolescents with cancer. Funding: Kinderkrebshilfe Tirol und Vorarlberg and Kinderhilfe Südtirol-Regenbogen supported this study.
Tilg et al. (Thu,) studied this question.