{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T05:15:52Z","timestamp":1783401352628,"version":"3.54.6"},"reference-count":43,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"\n Introduction<\/jats:title>\n The identification of classes of cancer-related fatigue in patients with breast cancer undergoing chemotherapy is crucial for the implementation of individualized intervention measures. This study aims to determine the demographic and clinical characteristics of each profile through latent profile analysis, and particularly examines the association between different profiles of cancer-related fatigue and the quality of life (QoL) of patients.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Patients with breast cancer undergoing chemotherapy for Department of Medical Oncology at a tertiary general hospital in Northwest China between April and August 2023 were recruited using convenience sampling. Employed the General Data Questionnaire, the Cancer Fatigue Scale, and the Functional Assessment of Cancer Therapy-Breast Scale to measure cancer-related fatigue and QoL. Latent profile analysis was performed to identify potential classifications of cancer-related fatigue. Univariable and multivariate logistic analysis were used to determine associated influencing factors.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Three latent profiles of cancer-related fatigue were identified: low physical and cognitive fatigue\u2013high emotional fatigue group (24.4%), moderate fatigue group (39.2%), and high physical and cognitive fatigue\u2013low emotional fatigue group (36.4%). Multivariate logistic analysis identified average daily step count during the past week \u2264 4,999 steps (\n OR<\/jats:italic>\n = 0.214, 95% CI: 0.049~0.940,\n P<\/jats:italic>\n = 0.041) and KPS score \u2264 70 (\n OR<\/jats:italic>\n = 6.377, 95% CI: 1.953~20.819,\n P<\/jats:italic>\n = 0.002) as significant predictors of moderate fatigue group, tumor stage III (\n OR<\/jats:italic>\n = 0.272, 95% CI: 0.080~0.922,\n P<\/jats:italic>\n = 0.037) and absence of pain (\n OR<\/jats:italic>\n = 0.360, 95% CI: 0.180~0.718,\n P<\/jats:italic>\n = 0.004) as important predictors of high physical and cognitive fatigue\u2013low emotional fatigue group.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n There are different characteristic groups of cancer-related fatigue in patients with breast cancer undergoing chemotherapy. Medical staff can formulate personalized intervention plans based on the different types of fatigue characteristics of patients to enhance their QoL.<\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1877774","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T04:23:10Z","timestamp":1783398190000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A latent profile analysis of cancer-related fatigue in patients with breast cancer undergoing chemotherapy and its relationship with quality of life: a cross-sectional study"],"prefix":"10.3389","volume":"14","author":[{"given":"Lingling","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Surgical Oncology, General Hospital of Ningxia Medical University","place":["Yinchuan, 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