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Updated: Aug 15, 2026
Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
[Prediction of lymph node metastasis with binary logistic regression in gastric carcinoma]
Jun-qiang Chen1, Wen-hua Zhan, Yu-long He
1Department of Gastrointestinopancreatic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China.
Objective:
To investigate more specific markers to predict the lymph node metastasis in gastric carcinoma.
Methods:
The expression of heparanase mRNA was detected by reverse transcription polymerase chain reaction (RT-PCR) in 43 cases with gastric cancer. The expressions of CD44V6, MMP-7, nm23 and syndecan-1 protein were examined by streptavidin-peroxidase (SP) two-step method. Clinicopathological features influencing lymphatic metastasis such as age,sex,tumor size,tumor location, Borrmann classification, histological type, differentiation and serosal infiltration were also analyzed.
Results:
Twenty-seven cases (62.8%) in 43 gastric cancer patients had lymphatic metastasis. The incidence of metastatic lymph nodes was(36.3 +/- 30.8)%. The median incidence was 19%. Univariate analysis showed that tumor size, serosal infiltration, expressions of heparanase mRNA, CD44V6, nm23 and syndecan-1 protein were risk factors for lymph node metastasis in gastric carcinoma. Multivariate analysis showed expressions of nm23 and syndecan-1 protein, serosal infiltration were independent factors for lymph node metastasis.
Conclusion:
Gastric cancer with serosal infiltration, positive expressions of nm23 and syndecan-1 has greater possibility of lymph node metastasis.
