Construction and validation of a prognostic model for gastrointestinal stromal tumors based on copy number alterations and clinicopathological characteristics.

ABSTRACT:

Background

The increasing incidence of gastrointestinal stromal tumors (GISTs) has led to the discovery of more novel prognostic markers. We aim to establish an unsupervised prognostic model for the early prediction of the prognosis of future patients with GISTs and to guide clinical treatment.

Methods

We downloaded the GISTs dataset through the cBioPortal website. We extracted clinical information and pathological information, including the microsatellite instability (MSI) score, fraction genome altered (FGA) score, tumor mutational burden (TMB), and copy number alteration burden (CNAB), of patients with GISTs. For survival analysis, we used univariate Cox regression to analyze the contribution of each factor to prognosis and calculated a hazard ratio (HR) and 95% confidenc

SUBMITTER: Zhao H 

PROVIDER: S-EPMC9811389 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature