Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
Identifying symptom clusters and temporal interconnections in patients with lung tumors after CT-guided microwave ablation: A network analysis.
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Liu Chunqin, Liu Tianchi, Fang Jia, Liu Xiaohua, Du Chunling, Luo Qin, Song Liqin, Liu Guangxin, Li Wenjuan, Li Weifeng, Geng Li
Аннотация
PURPOSE: To explore symptom clusters and interrelationships using a network analysis approach among symptoms in patients with lung tumors who underwent computed tomography (CT)-guided microwave ablation (MWA).
METHODS: A longitudinal study was conducted, and 196 lung tumor patients undergoing MWA were recruited and were measured at 24 h, 48 h, and 72 h after MWA. The Chinese version of the MD Anderson Symptom Inventory and the Revised Lung Cancer Module were used to evaluate symptoms. Network analyses were performed to explore the symptom clusters and interrelationships among symptoms.
RESULTS: Four stable symptom communities were identified within the networks. Distress, weight loss, and chest tightness were the central symptoms. Distress, and weight loss were also the most key bridge symptoms, followed by cough. Three symptom networks were temporally stable in terms of symptom centrality, global connectivity, and network structure.
CONCLUSION: Our findings identified the central symptoms, bridge symptoms, and the stability of symptom networks of patients with lung tumors after MWA. These network results will have important implications for future targeted symptom management intervention development. Future research should focus on developing precise interventions for targeting central symptoms and bridge symptoms to promote patients' health.
METHODS: A longitudinal study was conducted, and 196 lung tumor patients undergoing MWA were recruited and were measured at 24 h, 48 h, and 72 h after MWA. The Chinese version of the MD Anderson Symptom Inventory and the Revised Lung Cancer Module were used to evaluate symptoms. Network analyses were performed to explore the symptom clusters and interrelationships among symptoms.
RESULTS: Four stable symptom communities were identified within the networks. Distress, weight loss, and chest tightness were the central symptoms. Distress, and weight loss were also the most key bridge symptoms, followed by cough. Three symptom networks were temporally stable in terms of symptom centrality, global connectivity, and network structure.
CONCLUSION: Our findings identified the central symptoms, bridge symptoms, and the stability of symptom networks of patients with lung tumors after MWA. These network results will have important implications for future targeted symptom management intervention development. Future research should focus on developing precise interventions for targeting central symptoms and bridge symptoms to promote patients' health.