Construction of a preoperative nomogram model for predicting perineural invasion in advanced gastric cancer.

ABSTRACT:

Objective

This study aimed to develop and validate a clinical and imaging-based nomogram for preoperatively predicting perineural invasion (PNI) in advanced gastric cancer.

Methods

A retrospective cohort of 351 patients with advanced gastric cancer who underwent surgical resection was included. Multivariable logistic regression analysis was conducted to identify independent risk factors for PNI and to construct the nomogram. The performance of the nomogram was assessed using calibration curves, the concordance index (C-index), the area under the curve (AUC), and decision curve analysis (DCA). The disparity in disease-free survival (DFS) between the nomogram-predicted PNI-positive group and the nomogram-predicted PNI-negative group was evaluated using the Log-Rank test and Ka

SUBMITTER: Cong R 

PROVIDER: S-EPMC11190154 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature