Radiomics nomogram for prediction disease-free survival and adjuvant chemotherapy benefits in patients with resected stage I lung adenocarcinoma.

ABSTRACT:

Background

Robust imaging biomarkers are needed for risk stratification in stage I lung adenocarcinoma patients in order to select optimal treatment regimen. We aimed to construct and validate a radiomics nomogram for predicting the disease-free survival (DFS) of patients with resected stage I lung adenocarcinoma, and further identifying candidates benefit from adjuvant chemotherapy (ACT).

Methods

Using radiomics approach, we analyzed 554 patients' computed tomography (CT) images from three multicenter cohorts. Prognostic radiomics features were extracted from computed tomography (CT) images and selected using least absolute shrinkage and selection operator (LASSO) Cox regression model to build a radiomics signature for DFS stratification. The biological basis of radiomics w

SUBMITTER: Xie D 

PROVIDER: S-EPMC7481634 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature