Julienne E Bower1,2,3,4, Arash Asher5, Deborah Garet3, Laura Petersen4, Patricia A Ganz4,6,7, Michael R Irwin2,3, Steve W Cole2,3,8, Sara A Hurvitz8, Catherine M Crespi4,9. 1. Department of Psychology, University of California at Los Angeles, Los Angeles, California. 2. Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, California. 3. Norman Cousins Center for Psychoneuroimmunology, University of California at Los Angeles, Los Angeles, California. 4. Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, California. 5. Cedars-Sinai Medical Center, Samuel Oschin Comprehensive Cancer Institute, Los Angeles, California. 6. School of Medicine, University of California at Los Angeles, Los Angeles, California. 7. School of Public Health, University of California at Los Angeles, Los Angeles, California. 8. Department of Medicine, University of California at Los Angeles, Los Angeles, California. 9. Department of Biostatistics, University of California at Los Angeles, Los Angeles, California.
Abstract
BACKGROUND: Fatigue is one of the most common and disabling side effects of cancer and its treatment. Although research typically has focused on fatigue that occurs during and after treatment, patients may experience fatigue even before treatment onset. The current study was designed to identify biobehavioral risk factors associated with fatigue before adjuvant therapy in women with early-stage breast cancer. METHODS: Patients with stage 0 to stage IIIA breast cancer (270 women) were recruited before the onset of adjuvant or neoadjuvant therapy with radiotherapy, chemotherapy, and/or endocrine therapy. Host factors that may influence fatigue were identified from an empirically based, biobehavioral model and assessed using self-report questionnaires, medical record review, and blood collection (for genetic data). Fatigue was assessed by questionnaire. Linear regression analyses were used to evaluate the association between host factors and dimensions of fatigue, with general fatigue as the primary dimension of interest. RESULTS: Fatigue was elevated at the pretreatment assessment compared with published controls. Bivariate analyses identified demographic, cancer-related, and biobehavioral correlates of fatigue. In the multivariable model, predictors of general fatigue included younger age, lower educational level, lower cancer stage, and history of childhood maltreatment (all P values <.05), with the full model accounting for approximately 18.4% of the variance in fatigue. Secondary analyses identified common and specific predictors of emotional, mental, and physical dimensions of fatigue. CONCLUSIONS: Among women who have not yet initiated treatment of breast cancer, demographic and psychosocial factors are associated with elevated fatigue and could be used to identify at-risk patients for early intervention.
BACKGROUND:Fatigue is one of the most common and disabling side effects of cancer and its treatment. Although research typically has focused on fatigue that occurs during and after treatment, patients may experience fatigue even before treatment onset. The current study was designed to identify biobehavioral risk factors associated with fatigue before adjuvant therapy in women with early-stage breast cancer. METHODS:Patients with stage 0 to stage IIIA breast cancer (270 women) were recruited before the onset of adjuvant or neoadjuvant therapy with radiotherapy, chemotherapy, and/or endocrine therapy. Host factors that may influence fatigue were identified from an empirically based, biobehavioral model and assessed using self-report questionnaires, medical record review, and blood collection (for genetic data). Fatigue was assessed by questionnaire. Linear regression analyses were used to evaluate the association between host factors and dimensions of fatigue, with general fatigue as the primary dimension of interest. RESULTS:Fatigue was elevated at the pretreatment assessment compared with published controls. Bivariate analyses identified demographic, cancer-related, and biobehavioral correlates of fatigue. In the multivariable model, predictors of general fatigue included younger age, lower educational level, lower cancer stage, and history of childhood maltreatment (all P values <.05), with the full model accounting for approximately 18.4% of the variance in fatigue. Secondary analyses identified common and specific predictors of emotional, mental, and physical dimensions of fatigue. CONCLUSIONS: Among women who have not yet initiated treatment of breast cancer, demographic and psychosocial factors are associated with elevated fatigue and could be used to identify at-risk patients for early intervention.
Authors: Tracy D Vannorsdall; Ermiece Straub; Christina Saba; Mallory Blackwood; Jingyi Zhang; Keren Stearns; Karen Lisa Smith Journal: Support Care Cancer Date: 2020-10-21 Impact factor: 3.603
Authors: Julienne E Bower; Patricia A Ganz; Michael R Irwin; Steve W Cole; Deborah Garet; Laura Petersen; Arash Asher; Sara A Hurvitz; Catherine M Crespi Journal: Cancer Date: 2021-02-19 Impact factor: 6.860
Authors: AnnaLynn M Williams; Carly Paterson Khan; Charles E Heckler; Debra L Barton; Mary Ontko; Jodi Geer; Amber S Kleckner; Shaker Dakhil; Jerry Mitchell; Karen M Mustian; Luke J Peppone; Victor Kipnis; Charles S Kamen; Ann M O'Mara; Michelle C Janelsins Journal: Breast Cancer Res Treat Date: 2021-01-04 Impact factor: 4.872
Authors: Andrew W Manigault; Kate R Kuhlman; Michael R Irwin; Steve W Cole; Patricia A Ganz; Catherine M Crespi; Julienne E Bower Journal: Brain Behav Immun Date: 2021-03-09 Impact factor: 7.217
Authors: Ines Vaz-Luis; Antonio Di Meglio; Julie Havas; Mayssam El-Mouhebb; Pietro Lapidari; Daniele Presti; Davide Soldato; Barbara Pistilli; Agnes Dumas; Gwenn Menvielle; Cecile Charles; Sibille Everhard; Anne-Laure Martin; Paul H Cottu; Florence Lerebours; Charles Coutant; Sarah Dauchy; Suzette Delaloge; Nancy U Lin; Patricia A Ganz; Ann H Partridge; Fabrice André; Stefan Michiels Journal: J Clin Oncol Date: 2022-03-15 Impact factor: 50.717
Authors: Julienne E Bower; Kate R Kuhlman; Patricia A Ganz; Michael R Irwin; Catherine M Crespi; Steve W Cole Journal: Brain Behav Immun Date: 2020-04-02 Impact factor: 7.217
Authors: Hannah M Fisher; Joseph G Winger; Shannon N Miller; Arianna N Wright; Jennifer C Plumb Vilardaga; Catherine Majestic; Sarah A Kelleher; Tamara J Somers Journal: Support Care Cancer Date: 2021-03-15 Impact factor: 3.603