Establishing a predictive model for tumor mutation burden status based on CT radiomics and clinical features of non-small cell lung cancer patients.

ABSTRACT:

Background

Tumor mutation burden (TMB) is one of the biomarkers for efficacy of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC). Due to the potential of radiomic signatures to identify microscopic genetic and molecular differences, thus radiomics is considered a suitable tool for judging the TMB status probably. In this paper, the radiomics method was applied to analyze the TMB status of NSCLC patients, so as to construct a prediction model for distinguishing between TMB-high and TMB-low status.

Methods

A total of 189 NSCLC patients with TMB detection result were retrospectively included between 30 November 2016 and 1 January 2021, and were divided into two groups: TMB-high (≥10/Mb, 46 patients) and TMB-low (<10/Mb, 143 patients). Some clinical feat

SUBMITTER: Yang J 

PROVIDER: S-EPMC10183386 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature