Development of a prognostic nomogram and risk factor analysis for survival in H. pylori-positive non-cardia gastric adenocarcinoma patients.

Abstract

Background: Currently, there is limited research on the prognosis and influencing factors of non-cardia gastric adenocarcinoma (NCGAC) patients. This study aims to explore the factors influencing overall survival (OS) in Helicobacter pylori (H. pylori)-positive NCGAC patients and to develop a nomogram model to provide guidance for clinicians.

Methods: We retrospectively analyzed clinicopathological data from 413 H. pylori-positive NCGAC patients who underwent radical gastrectomy at the General Hospital of Ningxia Medical University. The dataset was randomly split into a training cohort (70%) and a validation cohort (30%). Univariate Cox proportional hazards regression analysis was used to identify prognostic factors, and factors with multicollinearity [variance inflation factor (VIF) >4] were excluded using the VIF. Factors of interest and those with P<0.05 were included in the multivariate Cox proportional hazards regression model. A nomogram prediction model was constructed based on factors with P<0.05. The model's performance was finally assessed using the area under the receiver operating characteristic curve (AUC) and calibration curves. The Kaplan-Meier survival curves visualize the impact of independent prognostic factors.

Results: Univariate Cox regression analysis was performed on the training cohort to select variables with P<0.5, including alcohol consumption, tumor size, differentiation grade, lymph node metastasis, tumor (T) stage, node (N) stage, and tumor node metastasis (TNM) stage. Multicollinearity was assessed, and covariates with VIF >4, such as lymph node metastasis, were excluded. The remaining factors were included in the multivariate Cox regression model. Significant variables (P<0.05), including alcohol consumption, differentiation grade, and T stage, were used to construct a nomogram, which showed a concordance index (C-index) of 0.727 in the training cohort and 0.728 in the validation cohort. The model's performance was validated with AUC and calibration curves (training cohort: 1-year AUC: 0.74, 3-year AUC: 0.78, 4-year AUC: 0.80; validation cohort: 1-year AUC: 0.67, 3-year AUC: 0.71, 4-year AUC: 0.72). Kaplan-Meier survival curves illustrated the impact of independent prognostic factors.

Conclusions: We developed a nomogram to predict survival in H. pylori-positive NCGAC patients, based on alcohol consumption, tumor differentiation, and T stage. The model showed strong predictive performance, with C-index values of 0.727 in the training cohort and 0.728 in the validation cohort. AUC values and calibration curves further confirmed its accuracy, suggesting the nomogram is a reliable tool for predicting prognosis and guiding treatment decisions.