A nomogram predicting lymph node metastasis in T1b gastric cancer patients: Korean gastric cancer association-led nationwide survey data
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background This study aimed to establish a nomogram predicting lymph node metastasis in stage T1b gastric cancer patients. Methods The clinicopathological variables of patients with T1b gastric cancer in 2019 were retrieved from the Korean Gastric Cancer Association Survey (KGCAS) database. Univariate and multivariate logistic regression analyses were performed, followed by the construction of a nomogram that predicted lymph node metastasis . External validation was achieved using data obtained from 2007 to 2017 from the eight affiliated hospitals of the Catholic University of Korea. Results A total of 3468 T1b gastric cancer patients were included in this study. In multivariate analysis , gender, the Lauren classification, lymphovascular invasion status, and endoscopic submucosal dissection (ESD) within 90 days before surgery were significantly predictive of lymph node metastasis. Using both these predictive factors and tumor size, a nomogram predicting lymph node metastasis was constructed. The receiver operating characteristic (ROC) curve analysis revealed an area under the curve (AUC) of 0.841. In the internal validation, the AUC was 0.835. The calibration plots of the predicted and actual observations were in good agreement. In the external validation, the AUC was 0.821 for the ROC curve analysis, and the calibration plot was of good quality. Conclusion The nomogram can be used to determine whether standard gastrectomy with lymphadenectomy is appropriate for patients with T1b EGC at a high risk of LNM. Especially, the nomogram included pathologic data, making it even more useful for patients requiring surgical decisions after ESD.
Source: Asian Journal of Surgery
Authors: Ji Won Seo, Seung-Taek Lim, Ki Bum Park, Kyong-Hwa Jun, Hyung Min Chin
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,200
Award: G3980295277
OpenAlex ID: W4409832881
