Evidence map›Paper›PMID 41836233›Full record

ArticleFrontiers in oncology2026

Study on the network of postoperative symptoms and its influencing factors in esophageal cancer patients.

Jing Zhao, Yina Liu, Bingbing Xiao, Tingting Tan, Yiting Yin, Yang Hu, Li Li

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Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Jing ZhaoCollege of Nursing, North Sichuan Medical College, Sichuan, China.
Yina LiuCollege of Nursing, North Sichuan Medical College, Sichuan, China.
Bingbing XiaoCollege of Nursing, North Sichuan Medical College, Sichuan, China.
Tingting TanCollege of Nursing, North Sichuan Medical College, Sichuan, China.
Yiting YinCollege of Nursing, North Sichuan Medical College, Sichuan, China.
Yang HuCollege of Nursing, North Sichuan Medical College, Sichuan, China.
Li LiCollege of Nursing, North Sichuan Medical College, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal cancer(EC) is a common and highly invasive malignant tumor of the digestive tract, for which surgery remains a key treatment modality. Postoperative patients frequently experience multiple coexisting physical and psychological symptoms. These symptoms are interrelated, forming a complex network that can substantially affect rehabilitation and health-related quality of life. Current symptom management often relies on traditional classification methods, which may be insufficient to elucidate the intrinsic relationships and core mechanisms among symptoms. Network analysis offers a new approach for identifying core symptoms, bridging symptoms, and key influencing factors. This study employs such methods to explore the relationships among postoperative symptoms in esophageal cancer, with the aim of providing evidence to support precise interventions and to enhance the effectiveness of symptom management. Objective: To construct a symptom network for post-operative esophageal cancer patients, identify core and bridging symptoms, and explore influencing factors, thereby providing references for precise and efficient symptom management. Methods: A convenience sampling method was used to select 263 patients with esophageal cancer undergoing surgery for investigation, and general information questionnaires and esophageal cancer perioperative symptom assessment scales were used. Univariate analysis and multivariate linear regression analysis were used to identify the influencing factors: bridge symptoms between core symptoms and symptom clusters were identified based on network analysis. Results: After surgery, esophageal cancer patients exhibited three symptom clusters: eating-related symptoms, pain and fatigue-related symptoms, and somatic-psychological symptoms, with a cumulative variance contribution rate of 67.841%. In the symptom network, fatigue (strength centrality, Conclusion: Fatigue is the primary symptom for esophageal cancer patients post-surgery; Healthcare providers can use symptom network analysis to promptly identify core symptoms, bridge symptoms, and influencing factors, thereby formulating precise and effective intervention measures to improve symptom management efficiency and reduce the postoperative symptom burden on esophageal cancer patients.

Indexed as

chokingsensationcore symptomsesophageal cancerfatigueinfluencing factorsnetwork analysis

Identifiers

PMID41836233
PMCPMC12982101

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