Abstract：Objective This study aims to construct and validate a nomogram for predicting postoperative survival probability in
patients with gastric cancer. Method A retrospective analysis was conducted on 370 patients diagnosed with gastric cancer who
underwent radical surgery at Liaoning Cancer Hospital between January 2017 and May 2021. Stratified sampling method was used to
divide the data into a training cohort n = 246 and a validation cohort n = 124 at a 2 ∶ 1 ratio. Clinical data including baseline
characteristics prognostic nutritional index PNI pathological features inflammatory factors and tumor markers were collected as
candidate variables. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent
risk factors associated with postoperative survival dependent variables . Subsequently a nomogram prediction model was developed
based on these identified factors. The performance of the nomogram—including its accuracy and discriminative ability—was evaluated
using the area under the receiver operating characteristic curve AUC calibration curves and compared against that of the traditional
TNM staging system. Additionally decision curve analysis DCA and Kaplan-Meier survival curves were employed to further assess
its clinical utility. Result Cox regression analyses identified four independent prognostic factors PNI lymph node metastasis depth of
invasion and CA125 levels. These factors were incorporated into the nomogram for visual representation of survival predictions. The
nomogram demonstrated significantly superior prognostic performance compared to traditional TNM staging this was evidenced by
higher AUC values improved calibration through calibration plots and greater net clinical benefit as determined by DCA. Conclusion
The nomogram incorporating nutritional indicators—including PNI—can accurately predict postoperative survival in patients with gastric
cancer thereby providing a reliable tool for personalized clinical decision-making.
李 雪,张剑军,纪美虹,张 丹,王文韬,张 兰. 基于营养指数胃癌手术患者预后风险模型构建及效能
评价[J]. 肿瘤代谢与营养电子杂志, 2025, 12(6): 794-804.
Li Xue, Zhang Jianjun, Ji Meihong, Zhang Dan, Wang Wentao, Zhang Lan. A nutritional index-derived prognostic risk model for postoperative gastric cancer patients development and performance
evaluation. Electron J Metab Nutr Cancer, 2025, 12(6): 794-804.
