Development of a Clinicopathological Prognostic Model and Risk Classification to Predict Disease-Free Survival in Patients with Gastric Adenocarcinoma Following Neoadjuvant Chemotherapy and Curative Gastrectomy

Vollständiger Abstract

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Background: Prognostic assessment after neoadjuvant chemotherapy and curative gastrectomy remains challenging in patients with gastric adenocarcinoma because postoperative outcomes are influenced by both pretreatment disease burden and pathological response. We aimed to develop and internally validate a clinicopathological prognostic model and a simple postoperative risk classification for predicting disease-free survival (DFS). Methods: This single-center retrospective cohort study included patients with gastric adenocarcinoma who underwent neoadjuvant chemotherapy followed by curative gastrectomy. Pretreatment clinicopathological variables, Becker tumor regression grade (TRG), and serum tumor markers were evaluated. Logistic regression was used to identify predictors of favorable pathological response, whereas Cox proportional hazards regression was performed to identify independent prognostic factors for disease-free survival (DFS). Sequential prognostic models were developed and internally validated using 1000 bootstrap resamples. A simplified postoperative clinicopathological risk classification based on pretreatment clinical N stage and Becker tumor regression grade was additionally developed to facilitate clinical interpretation and postoperative risk stratification. Results: A total of 109 patients were included. Favorable pathological response (Becker TRG1–2) was achieved in 68 patients (62.4%), whereas 41 patients (37.6%) had minimal or no pathological response (TRG3). In multivariable logistic regression analysis, pretreatment clinical T stage (cT4 vs. cT1–3) and clinical N stage (cN2–3 vs. cN0–1) were independently associated with a lower likelihood of achieving a favorable pathological response. For disease-free survival, pretreatment clinical N stage, Becker tumor regression grade, and log10-transformed CA19-9 remained independent prognostic factors in the multivariable Cox model. Sequential model development demonstrated progressive improvement in model discrimination, with the optimism-corrected Harrell’s C-index increasing from 0.697 for the clinical N stage model to 0.770 for the final model incorporating clinical N stage, Becker tumor regression grade, and CA19-9. Bootstrap internal validation demonstrated minimal optimism, and calibration analysis showed good agreement between predicted and observed disease-free survival. A simple postoperative clinicopathological risk classification successfully stratified patients into distinct prognostic groups. Conclusions: A clinicopathological prognostic model integrating pretreatment clinical N stage, Becker tumor regression grade, and serum CA19-9 demonstrated improved prognostic discrimination for disease-free survival compared with clinical N stage alone. The derived postoperative risk classification may provide a simple framework for postoperative risk stratification and could assist in individualizing postoperative surveillance. External validation is warranted before routine clinical implementation.