Development and validation of a new staging system for node-negative gastric cancer based on recursive partitioning analysis: An international multi-institutional study

Abstract

Background: Whether the tumor-node-metastasis (TNM) staging system is appropriate for patients with node-negative gastric cancer (GC) is still inconclusive. The modified staging system developed by recursive partitioning analysis (RPA) showed good prognostic performance in a variety of cancers. The application of RPA has not been reported in the prognostic prediction of GC. Methods: Node-negative GC patients who underwent radical resection at Fujian Medical University Union Hospital (n = 862) and Sun Yat-sen University Cancer Center (n = 311) with at least 5 years of follow-up were selected as the training set. RPA was used to develop a modified staging system. Patients from the Surveillance, Epidemiology, and End Results database (n = 1415) were selected as the validation set. Results: The 5-year overall survival (OS) rates of patients with 8th AJCC-TNM stage IA-IIIA in the training set were IA 95.2%, IB 87.1%, IIA 78.3%, IIB 75.8%, and IIIA 72.6%. Multivariate analysis (MVA) showed that larger tumor size, elder age, and deeper depth of invasion were independent predictors for OS in patients with node-negative GC (all P < 0.05). Patients were reclassified into RPA I, RPA II, RPA III, and RPA IV stages based on RPA; the 5-year OS rates were 96.1%, 87.2%, 81.0%, and 64.3%, respectively, with significant difference (P < 0.05). Two-step MVA showed that the RPA staging system was an independent predictor of OS (P < 0.05). Compared with the 8th AJCC-TNM staging system, the RPA staging system had a smaller AIC value (2544.9 vs 2576.2), higher χ2 score (104.2 vs 69.6) and higher Harrell's C-index (0.697 vs 0.669, P = 0.007). The similar results were found in the validation set. Conclusions: A new prognostic predictive system based on RPA was successfully developed and validated, which may be suggested for staging node-negative GC in future.