Nomogram for predicting overall survival after curative gastrectomy using inflammatory, nutritional and pathological...

Area of Science:

• Oncology
• Surgical Oncology
• Biostatistics

Background:

• Gastric cancer (GC) poses a significant global health challenge, necessitating improved prognostic tools.
• Accurate prediction of overall survival (OS) is crucial for personalized treatment strategies in GC patients.

Purpose of the Study:

• To develop and validate a nomogram for predicting OS in GC patients undergoing curative gastrectomy.
• To identify key inflammatory, nutritional, and pathological factors influencing GC patient survival.

Main Methods:

• A cohort of 366 GC patients was divided into training (70%) and validation (30%) sets.
• Univariate and multivariate Cox regression analyses were employed to identify independent prognostic factors.
• A nomogram was constructed using significant variables and validated for discrimination and calibration.

Main Results:

• Age, CA50, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), and tumor stage (T and N) were identified as independent predictors of OS.
• The nomogram demonstrated good discriminative ability, with Area Under the ROC Curve (AUC) values ranging from 0.77 to 0.86 for 1- to 5-year survival.
• The nomogram effectively stratified patients into low, intermediate, and high-risk groups with significantly different OS.

Conclusions:

• A robust nomogram integrating PNI, SII, and pathological factors was established for predicting OS in GC patients.
• The nomogram's predictive accuracy was confirmed through internal validation and stratified analysis, offering a valuable tool for clinical decision-making.