Development and validation of an individualized nomogram for predicting distant metastases in gastric cancer using a CT radiomics-clinical model.

ABSTRACT:

Purpose

This study aimed to develop and validate a model for accurately assessing the risk of distant metastases in patients with gastric cancer (GC).

Methods

A total of 301 patients (training cohort, n = 210; testing cohort, n = 91) with GC were retrospectively collected. Relevant clinical predictors were determined through the application of univariate and multivariate logistic regression analyses. Then the clinical model was established. Venous phase computed tomography (VPCT) images were utilized to extract radiomic features, and relevant features were selected using univariate analysis, Spearman correlation coefficient, and the least absolute shrinkage and selection operator (Lasso) regression. Subsequently, radiomics scores were calculated based on the selected feature

SUBMITTER: Xue HB 

PROVIDER: S-EPMC11672336 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature