Tumor regression patterns predict ypN positivity in advanced gastric cancer patients

ObjectiveTo analyze the relationship between tumor regression patterns and ypN positivity and explore their implications for postoperative nodal-risk stratification after neoadjuvant or conversion therapy in advanced gastric cancer, while generating hypotheses for future individualized lymphadenectomy research.MethodsTumor regression patterns were classified as centripetal, diffuse/mixed, or centrifugal. Clinical and pathological characteristics were compared using the Kruskal–Wallis and χ² tests. Using ypN positivity as the outcome, a multivariable logistic regression model was constructed. Sensitivity analyses were performed in the subgroup with ≥16 retrieved lymph nodes, after additional adjustment for ypT and Becker tumor regression grade (TRG), and in the non-pCR subgroup. Internal validation was performed using a 7:3 stratified random split and 10-fold cross-validation. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), 95% confidence intervals, calibration, and the Brier score. We additionally compared a baseline clinicopathological model with a combined model incorporating regression pattern to assess incremental predictive value.ResultsAmong 195 patients, 74 (38.0%) exhibited centripetal regression, 43 (22.1%) had diffuse/mixed regression, and 78 (40.0%) demonstrated centrifugal regression. Centripetal regression was characterized by low PRI, higher LRI and CER, and a very low ypN positivity rate (5.4%), whereas centrifugal regression showed the opposite pattern and the highest ypN positivity rate (75.6%); diffuse/mixed regression showed intermediate features (all p < 0.001). Multivariable analysis identified diffuse/mixed and centrifugal regression as the strongest independent predictors of ypN positivity. The apparent full-cohort model demonstrated an AUC of 0.875 (95% CI 0.826–0.922) with good calibration and a Brier score of 0.137. These associations remained robust after additional adjustment for ypT and Becker TRG and in the non-pCR subgroup. Internal validation showed acceptable performance, with a validation AUC of 0.826 in the 7:3 split-sample analysis and a pooled AUC of 0.822 in 10-fold cross-validation. Addition of regression pattern to the baseline clinicopathological model improved discrimination and reduced prediction error.ConclusionPathological regression patterns provide effective stratification of residual lymph node metastasis after neoadjuvant or conversion therapy. Centripetal regression indicates a very low residual nodal-risk phenotype, whereas centrifugal regression is associated with a heavier nodal burden. At present, regression patterns may be most appropriately used for postoperative risk assessment and multidisciplinary stratification. Their potential role in individualized lymphadenectomy should be viewed as a future translational direction requiring validated preoperative or intraoperative surrogate markers and prospective confirmation.