Normalization weighted combination scores re-evaluate TNM staging of gastric cancer: a retrospective cohort study based on a multicenter database

Background: The pathological depth of tumor invasion (pT) and lymph node metastasis (pN) are critical independent prognostic factors for patients with gastric cancer (GC), representing effective methods for evaluating prognosis. In this study, the authors employed a normalization weight combination score to calculate the weight ratio of the pT stage and pN stage. Subsequently, the authors established a novel weighted TN (wTN) staging model based on these T and N weights, evaluating its prognostic capacity. Methods: This study utilized a training cohort from A Medical University Cancer Hospital and a validation cohort from the SEER database. Least absolute shrinkage and selection operator (LASSO) and Cox regression were employed to screen clinical characteristics. Multivariate linear regression and cluster analysis calculated the weight ratio of T stage and N stage in the training and validation cohorts, respectively, followed by re-staging. Prognostic value was evaluated using C-index, likelihood ratio, Wald, and Score tests for wTN stage and tumor–node–metastasis (TNM) stage. A nomogram model was developed, and accuracy was assessed using receiver operating characteristic curve (ROC), decision curve analysis (DCA), and restricted cubic spline (RCS) analyses. Results: LASSO was used for initial screening, selecting eight potential features for Cox analysis. Age, tumor size, metastasis lymph nodes (MLNs), and tumor location were confirmed as independent prognostic factors. wTN was calculated in the training and validation cohorts, and nomograms were established with the independent factors. N stage had a higher weight proportion than T stage in both cohorts (0.625/0.375 in training cohort, 0.556/0.444 in validation cohort). wTN outperformed the 8th TNM stage in C-index, likelihood ratio, Wald, and Score tests in the training cohort, with successful validation in the validation cohort. Stratified analysis of distinct pathological types further demonstrates that wTN staging exhibits superior prognostic performance. Conclusion: The wTN staging model based on T stage and N stage weights has a good prognostic value for GC patients. The same conclusion was obtained in different pathological stratification.