Objective: This study aims to investigate the distribution characteristics of symptoms in patients with lung cancer during chemotherapy, identify the symptom clusters (SCs) and explore the underlying mechanisms. The findings will provide evidence to assist clinical staff in effectively managing symptoms and SCs.
Methods: Participants were recruited from the Oncology Department of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, between July 2022 and December 2022. The incidence and severity of symptoms were assessed and SCs were identified. Spearman's correlation analysis was used to examine the correlation between lung cancer-specific SC and routine blood indices.
Results: A total of 169 patients participated in the study. The most prevalent and severe symptom was loss of appetite. Based on the occurrence rate and severity of symptoms, SC extraction was performed for mild, moderate, and severe symptoms, resulting in the identification of five SCs: psycho-emotional SC, chemotherapy-related SC, lung cancer-specific SC, urinary-related SC, and gastrointestinal SC. When only the moderate and severe symptoms were considered, two SCs were identified: chemotherapy-related SC and lung cancer-specific SC. Additionally, the lung cancer-specific SC showed a negative correlation with eosinophils.
Conclusion: Patients with lung cancer undergoing chemotherapy experience complex and diverse symptoms. A total of five SCs were extracted based on mild, moderate and severe symptoms and two SCs were extracted based on moderate and severe symptoms. The results of the study showed that lung cancer-specific SC was negatively correlated with eosinophils. Future research should focus on developing and refining research tools, methodologies, understanding the pathogenesis, and exploring intervention measures for SCs.
Keywords: Chemotherapy; Exploratory factor analysis; Lung cancer; Symptom burden; Symptom clusters.
© 2024. The Author(s).