Distinct evening fatigue profiles in oncology outpatients receiving chemotherapy. Issue 3 (3rd July 2017)

• Record Type: Journal Article
• Authors: Wright, Fay; Cooper, Bruce A.; Conley, Yvette P.; Hammer, Marilyn J.; Chen, Lee-May; Paul, Steven M.; Levine, Jon D.; Miaskowski, Christine; Kober, Kord M.
• Is Part Of: Fatigue. Volume 5:Issue 3(2017)
• Page Start: 131
• Page End: 144
• Publication Date: 2017-07-03
• Subjects: Evening fatigue -- chemotherapy -- diurnal variations -- symptom profiles -- latent class analysis; Chronic fatigue syndrome -- Periodicals; Myalgic encephalomyelitis -- Periodicals; 616.047805
• DOI: 10.1080/21641846.2017.1322233
• Languages: English
• ISSNs: 2164-1846

Abstract

ABSTRACT: Background : Fatigue is the most common and debilitating symptom experienced by oncology patients during chemotherapy (CTX). Fatigue severity demonstrates a large amount of inter-individual and diurnal variability. Purpose : Study purposes were to evaluate for subgroups of patients with distinct evening fatigue profiles and evaluate how these subgroups differed on demographic, clinical, and symptom characteristics. Methods : Outpatients with breast, gastrointestinal, gynecological, or lung cancer ( n = 1332) completed questionnaires six times over two cycles of CTX. Lee Fatigue Scale evaluated evening fatigue severity. Latent profile analysis was used to identify distinct evening fatigue profiles. Results : Four distinct evening fatigue classes (i.e. Low (14.0%), Moderate (17.2%), High (36.0%), and Very High (32.8%)) were identified. Compared to the Low class, patients in the Very High evening fatigue class were: younger, female, had childcare responsibilities, had more years of education, had a lower functional status, had a higher comorbidity burden, and were diagnosed with breast cancer. Patients in the Very High class reported higher levels of depressive symptoms, sleep disturbance, and evening fatigue at enrollment. Conclusions : Findings provide new insights into modifiable risk factors for higher levels of evening fatigue. Clinicians can use this information to identify higher risk patients and plan appropriate interventions.