Latent profile analysis of fatigue in patients with radiation-induced pulmonary fibrosis and non-small cell lung cancer
10.3760/cma.j.cn115682-20250219-00767
- VernacularTitle:放射性肺纤维化NSCLC患者疲劳程度的潜在剖面分析
- Author:
Cong ZHANG
1
;
Jing YANG
1
;
Xiaona KANG
1
;
Xiaodan HAN
1
Author Information
1. 郑州大学第一附属医院放疗三科，郑州 450000
- Publication Type:Journal Article
- Keywords:
Lung neoplasms;
Non-small cell lung cancer;
Radiation-induced pulmonary fibrosis;
Fatigue;
Latent profile analysis
- From:
Chinese Journal of Modern Nursing
2025;31(29):3998-4003
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the latent profile characteristics of fatigue in patients with non-small cell lung cancer (NSCLC) complicated by radiation-induced pulmonary fibrosis (RIPF), and to provide evidence for developing precision nursing strategies.Methods:A convenience sample of 120 patients with RIPF and NSCLC who received treatment at the First Affiliated Hospital of Zhengzhou University between January 2022 and December 2023 was recruited. Baseline demographic and clinical data and the Multidimensional Fatigue Inventory (MFI) were collected. Latent profile analysis (LPA) was performed to classify fatigue levels, and multinomial logistic regression was used to identify influencing factors. A total of 120 questionnaires were distributed, and 116 valid responses were obtained, with a valid response rate of 96.67% (116/120) .Results:LPA identified three latent classes of fatigue among the 116 patients: the physiological-cognitive compound fatigue group ( n=52), the emotional-sleep disturbance group ( n=38), and the mildly adaptive group ( n=26). Multinomial logistic regression revealed that age, Eastern Cooperative Oncology Group performance status (ECOG-PS), Karnofsky Performance Status (KPS), sleep quality, and anxiety were significant factors associated with the physiological-cognitive compound fatigue group ( P<0.05). Sleep quality, anxiety, depression, pain, and KPS were significant factors associated with the emotional-sleep disturbance group ( P<0.05) . Conclusions:Patients with RIPF and NSCLC can be classified into three subtypes of fatigue. Differentiated nursing strategies should be developed accordingly to achieve precise and individualized interventions.
