A nomogram based on ¹⁸F-fluorodeoxyglucose PET/CT and clinical features to predict epidermal growth factor receptor mutation status in patients with lung adenocarcinoma.

ABSTRACT:

Background

Identifying epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma (LADC) is vital for treatment decision-making. This study aimed to establish a convenient and noninvasive nomogram prediction model based on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) imaging and clinical features to predict EGFR mutation status in patients with LADC.

Methods

A total of 274 patients (male 130, female 144, median age 65 years) were enrolled in this retrospective study. Imaging data from ¹⁸F-FDG PET/CT and clinical information were analyzed, with the Mann-Whitney U test, Student's t-test, and chi-square test used to compare categorical or continuous covariates as appropriate. Logis

SUBMITTER: Guo Y 

PROVIDER: S-EPMC9622444 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature