Construction and validation of a prediction model for pyloric lymph node metastasis in upper gastric cancer
10.19405/j.cnki.issn1000–1492.2026.02.020
- VernacularTitle:胃上部癌幽门区淋巴结转移预测模型的构建与验证
- Author:
Zhisheng MA
1
;
Zhaoyu SONG
1
;
Peifeng CHEN
1
;
Wannian SUI
1
;
Zhangming CHEN
1
;
Wenxiu HAN
1
Author Information
1. Department of General Surgery， The First Affiliated Hospital of Anhui Medical University， Hefei 230022
- Publication Type:Journal Article
- Keywords:
lymph node metastasis;
risk factors;
nomogram;
pyloric lymph nodes;
upper gastric cancer;
Logistic regression analysis;
lymphovascular invasion;
fibrinogen degradation product
- From:
Acta Universitatis Medicinalis Anhui
2026;61(2):328-334
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo identify the independent risk factors for pyloric lymph node （PLN） metastasis in patients with upper gastric cancer （UGC） and to construct a nomogram prediction model applicable for UGC patients. MethodsClinical data of 823 UGC patients attended between January 2020 and November 2023 were retrospectively collected. Patients were randomly divided into a training set （n=576） and a validation set （n=247） at a 7∶3 ratio. Based on the training set， multivariate Logistic regression analysis was performed to identify independent risk factors for PLN metastasis， and a nomogram prediction model was constructed accordingly. The model's discriminative ability and calibration were assessed using receiver operating characteristic （ROC） curves and calibration curves. Finally， external validation was conducted using the validation set to evaluate the model's stability and generalizability. ResultsMultivariate Logistic regression analysis revealed that tumor size （OR=1.324， 95%CI： 1.053-1.667）， T3 stage （OR=5.738， 95%CI： 1.281-25.695）， T4 stage （OR=7.680， 95%CI： 1.542-38.247）， lymphovascular invasion （LVI） （OR=6.623， 95%CI： 1.384-31.708）， differentiation extent （OR=3.108， 95%CI： 1.545-6.251）， and fibrinogen degradation product （FDP） level （OR=4.849， 95%CI： 2.071-11.355） were independent risk factors for PLN metastasis in UGC patients.The nomogram model constructed based on these factors demonstrated areas under the ROC curve （AUC） of 0.815 （95%CI： 0.751-0.815） in the training set and 0.832 （95%CI： 0.731-0.933） in the validation set. Calibration curves indicated good agreement between predicted and observed outcomes. ConclusionThis nomogram prediction model exhibits good predictive performance for assessing the risk of PLN metastasis in UGC patients.
