Development and validation of a prognostic prediction model for elderly gastric cancer patients based on oxidative stress biochemical markers.

ABSTRACT:

Background

The potential of the application of artificial intelligence and biochemical markers of oxidative stress to predict the prognosis of older patients with gastric cancer (GC) remains unclear.

Methods

This retrospective multicenter study included consecutive patients with GC aged ≥ 65 years treated between January 2012 and April 2018. The patients were allocated into three cohorts (training, internal, and external validation). The GC-Integrated Oxidative Stress Score (GIOSS) was developed using Cox regression to correlate biochemical markers with patient prognosis. Predictive models for five-year overall survival (OS) were constructed using random forest (RF), decision tree (DT), and support vector machine (SVM) methods, and validated using area under the curve (AUC)

SUBMITTER: Zhang XQ 

PROVIDER: S-EPMC11786569 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature