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Symptom profiles and related factors among patients with advanced cancer: A latent profile analysis

OBJECTIVE: This study aimed to investigate symptom subgroups and associated influencing factors in patients with advanced cancer. METHODS: A cross-sectional study was conducted, involving 416 patients with advanced cancer. The study examined five symptoms: fatigue, pain, sleep impairment, anxiety, a...

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Detalles Bibliográficos
Autores principales: Hu, Huixiu, Zhao, Yajie, Sun, Chao, Wang, Pei, Yu, Lijuan, Peng, Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10597764/
https://www.ncbi.nlm.nih.gov/pubmed/37885766
http://dx.doi.org/10.1016/j.apjon.2023.100296
Descripción
Sumario:OBJECTIVE: This study aimed to investigate symptom subgroups and associated influencing factors in patients with advanced cancer. METHODS: A cross-sectional study was conducted, involving 416 patients with advanced cancer. The study examined five symptoms: fatigue, pain, sleep impairment, anxiety, and depression. Latent Profile Analysis (LPA) was utilized to classify symptom subgroups. A multiple logistic regression analysis was conducted to explore factors associated with the identified symptom subgroups. RESULTS: The analysis revealed three distinct subgroups among the participants: “all low” (58.2%), characterized by normal symptoms except for moderate sleep quality; “all moderate” (35.1%), exhibiting normal symptoms except for poor sleep quality and fatigue; and “all high” (6.7%), experiencing normal pain, moderate depression, moderate anxiety, poor sleep quality, and fatigue. Malnutrition risk, cancer diagnosis, and cancer survivorship duration were found to be associated with a more severe symptom burden. CONCLUSIONS: Patients in the “all high” subgroup faced an increased risk of malnutrition and a longer cancer survivorship duration. Additionally, patients in the “all moderate” subgroup were distinguished by having a breast cancer diagnosis. These findings have significant implications for allocating medical resources and implementing person-centered symptom management strategies.