Development and validation of a predictive model for overall survival in esophageal squamous cell carcinoma post-esophagectomy: the role of lymph node metastatic Stations

食管切除术 医学 阶段(地层学) 食管癌 食管鳞状细胞癌 淋巴结 肿瘤科 单变量分析 内科学 比例危险模型 癌症 多元分析 生物 古生物学
作者
Kexun Li,Simiao Lu,Kunyi Du,Chenghao Wang,Wenwu He,Qifeng Wang,Yong Han,Xuefeng Leng,Lin Peng
出处
期刊:International Journal of Surgery [Wolters Kluwer]
标识
DOI:10.1097/js9.0000000000002188
摘要

Background: Esophageal squamous cell carcinoma (ESCC) poses a substantial healthcare challenge, particularly in areas such as East Asia. The pathologic nodal (pN) stage of ESCC remains a controversial factor. Accurately predicting overall survival (OS) after esophagectomy is crucial for treatment planning and improving treatment outcomes. Method: An analysis was conducted using data from our hospital [Details blind for peer review], spanning from January 2010 to December 2017. Our study aimed to examine the clinicopathological characteristics, lymph node resection at individual stations, and treatment details of patients with ESCC who underwent esophagectomy. In addition, a novel nodal stage (N stage) based on the number of lymph node metastasis (LNM) stations and devised a prediction model for OS using the pN stage and the newly proposed N stage. Results: After analysing 49 indicators through univariate and multifactorial analyses, 25 of the most significant factors affecting OS after esophagectomy were identified. Further analysis using least absolute shrinkage and selection operator regression revealed six key factors. Models were developed based on the pN stage and the newly introduced N stage. Evaluation of the area under the curve indicated that Model 2 exhibited slightly superior clinical utility compared to Model 1. Conclusions: Our study demonstrates that the newly introduced N stage, based on the number of LNM stations, exhibits comparable performance to the current American Joint Committee on Cancer/Union for International Cancer Control pN system, with a slight advantageous edge.
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