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Vaz-Luis, Ines; Di Meglio, Antonio; Havas, Julie; El-Mouhebb, Mayssam; Lapidari, Pietro; Presti, Daniele; Soldato, Davide; Pistilli, Barbara; Dumas, Agnes; Menvielle, Gwenn; Charles, Cecile; Everhard, Sibille; Martin, Anne-Laure; Cottu, Paul H.; Lerebours, Florence; Coutant, Charles; Dauchy, Sarah; Delaloge, Suzette; Lin, Nancy U.; Ganz, Patricia A.; Partridge, Ann H.; André, Fabrice; Michiels, Stefan

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

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  • Media type: E-Article
  • Title: Long-Term Longitudinal Patterns of Patient-Reported Fatigue After Breast Cancer: A Group-Based Trajectory Analysis
  • Contributor: Vaz-Luis, Ines; Di Meglio, Antonio; Havas, Julie; El-Mouhebb, Mayssam; Lapidari, Pietro; Presti, Daniele; Soldato, Davide; Pistilli, Barbara; Dumas, Agnes; Menvielle, Gwenn; Charles, Cecile; Everhard, Sibille; Martin, Anne-Laure; Cottu, Paul H.; Lerebours, Florence; Coutant, Charles; Dauchy, Sarah; Delaloge, Suzette; Lin, Nancy U.; Ganz, Patricia A.; Partridge, Ann H.; André, Fabrice; Michiels, Stefan
  • Published: American Society of Clinical Oncology (ASCO), 2022
  • Published in: Journal of Clinical Oncology, 40 (2022) 19, Seite 2148-2162
  • Language: English
  • DOI: 10.1200/jco.21.01958
  • ISSN: 0732-183X; 1527-7755
  • Origination:
  • Footnote:
  • Description: <jats:sec><jats:title>PURPOSE</jats:title><jats:p> 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. </jats:p></jats:sec><jats:sec><jats:title>METHODS</jats:title><jats:p> 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. </jats:p></jats:sec><jats:sec><jats:title>RESULTS</jats:title><jats:p> 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. </jats:p></jats:sec><jats:sec><jats:title>CONCLUSION</jats:title><jats:p> 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. </jats:p></jats:sec>
  • Access State: Open Access