4.7 Article

Long-Term Longitudinal Patterns of Patient-Reported Fatigue After Breast Cancer: A Group-Based Trajectory Analysis

Journal

JOURNAL OF CLINICAL ONCOLOGY
Volume 40, Issue 19, Pages 2148-+

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1200/JCO.21.01958

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Funding

  1. Career Catalyst Research grant from Susan G. Komen [CCR17483507]
  2. Odyssea
  3. French Foundation for Cancer Research (ARC)
  4. Foundation Gustave Roussy
  5. Conquer Cancer
  6. ASCO Foundation
  7. Rising Tide Foundation for Clinical Cancer Research
  8. CANTO under the Investment for the Future program [ANR-10-COHO-0004]
  9. PRISM project - Agence Nationale de la Recherche [ANR-18-IBHU-0002]
  10. Susan G. Komen
  11. Conquer Cancer Foundation of ASCO
  12. French Government (Agence Nationale de la recherche [ANR])
  13. French Foundation for Cancer Research
  14. Agence Nationale de la Recherche (ANR) [ANR-18-IBHU-0002] Funding Source: Agence Nationale de la Recherche (ANR)

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This study aimed to characterize long-term fatigue trajectories among breast cancer survivors. Three trajectory groups were identified for severe global fatigue, and it was found that different dimensions of fatigue were influenced by different factors. This helps identify patients at increased risk of severe fatigue and inform personalized interventions.
PURPOSE Fatigue is recognized as one of the most burdensome and long-lasting adverse effects of cancer and cancer treatment. We aimed to characterize long-term fatigue trajectories among breast cancer survivors. METHODS We performed a detailed longitudinal analysis of fatigue using a large ongoing national prospective clinical study (CANcer TOxicity, ClinicalTrials.gov identifier: NCT01993498) of patients with stage I-III breast cancer treated from 2012 to 2015. Fatigue was assessed at diagnosis and year 1, 2, and 4 postdiagnosis. Baseline clinical, sociodemographic, behavioral, tumor-related, and treatment-related characteristics were available. Trajectories of fatigue and risk factors of trajectory-group membership were identified by iterative estimates of group-based trajectory models. RESULTS Three trajectory groups were identified for severe global fatigue (n = 4,173). Twenty-one percent of patients were in the high-risk group, having risk estimates of severe global fatigue of 94.8% (95% CI, 86.6 to 100.0) at diagnosis and 64.6% (95% CI, 59.2 to 70.1) at year 4; 19% of patients clustered in the deteriorating group with risk estimates of severe global fatigue of 13.8% (95% CI, 6.7 to 20.9) at diagnosis and 64.5% (95% CI, 57.3 to 71.8) at year 4; 60% were in the low-risk group with risk estimates of 3.6% (95% CI, 2.5 to 4.7) at diagnosis and 9.6%(95% CI, 7.5 to 11.7) at year 4. The distinct dimensions of fatigue clustered in different trajectory groups than those identified by severe global fatigue, being differentially affected by sociodemographic, clinical, and treatment-related factors. CONCLUSION Our findings highlight the multidimensional nature of cancer-related fatigue and the complexity of its risk factors. This study helps to identify patients with increased risk of severe fatigue and to inform personalized interventions to ameliorate this problem. (C) 2022 by American Society of Clinical Oncology

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