Prognostic impact of examined lymph-node count for patients with esophageal cancer: development and validation prediction model

Esophageal cancer (EC) is a malignant tumor with high mortality. We aimed to find the optimal examined lymph node (ELN) count threshold and develop a model to predict survival of patients after radical esophagectomy. Two cohorts were analyzed: the training cohort which included 734 EC patients from...

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Bibliographic Details
Published in:Scientific reports 2023-01, Vol.13 (1), p.476-476, Article 476
Main Authors: Yuan, Shasha, Wei, Chen, Wang, Mengyu, Deng, Wenying, Zhang, Chi, Li, Ning, Luo, Suxia
Format: Article
Language:English
Subjects:
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Epidemiology
Esophageal cancer
Esophageal Neoplasms - diagnosis
Esophageal Neoplasms - pathology
Esophageal Neoplasms - surgery
Humanities and Social Sciences
Humans
Lymph nodes
Lymph Nodes - pathology
Mathematical models
Medical prognosis
multidisciplinary
Neoplasm Staging
Prediction models
Prognosis
Regression Analysis
Science
Science (multidisciplinary)
Survival
Training
Tumors
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Summary:Esophageal cancer (EC) is a malignant tumor with high mortality. We aimed to find the optimal examined lymph node (ELN) count threshold and develop a model to predict survival of patients after radical esophagectomy. Two cohorts were analyzed: the training cohort which included 734 EC patients from the Chinese registry and the external testing cohort which included 3208 EC patients from the Surveillance, Epidemiology, and End Results (SEER) registry. Cox proportional hazards regression analysis was used to determine the prognostic value of ELNs. The cut-off point of the ELNs count was determined using R-statistical software. The prediction model was developed using random survival forest (RSF) algorithm. Higher ELNs count was significantly associated with better survival in both cohorts (training cohort: HR = 0.98, CI = 0.97–0.99, P  
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-022-27150-6