Prognostic value of modified Lauren classification in gastric cancer
Fei‐Long Ning, Nannan Zhang, Jun Wang, Yifeng Jin, Hong-Guang Quan, Jun‐Peng Pei, Yan Zhao, Xian‐Tao Zeng, Masanobu Abe, Chun‐Dong Zhang
Abstract
BACKGROUND: It remains controversial as to which pathological classification is most valuable in predicting the overall survival (OS) of patients with gastric cancer (GC). AIM: To assess the prognostic performances of three pathological classifications in GC and develop a novel prognostic nomogram for individually predicting OS. METHODS: Patients were identified from the Surveillance, Epidemiology, and End Results program. Univariate and multivariate analyses were performed to identify the independent prognostic factors. Model discrimination and model fitting were evaluated by receiver operating characteristic curves and Akaike information criteria. Decision curve analysis was performed to assess clinical usefulness. The independent prognostic factors identified by multivariate analysis were further applied to develop a novel prognostic nomogram. RESULTS: edition tumor-node-metastasis classification. CONCLUSION: The modified Lauren classification shows superior net benefits over the Lauren classification and tumor differentiation grade in predicting OS. A novel prognostic nomogram incorporating the modified Lauren classification shows good model discriminative ability, model-fitting performance, and net benefits.