Prediction of first-line immunotherapy response in patients with extensive-stage small cell lung cancer using a clinical-radiomics combined model.

ABSTRACT:

Objective

This study aimed to explore the value of clinical-radiomics features for predicting response to immunotherapy in extensive-stage small cell lung cancer (ES-SCLC).

Methods

This retrospective study enrolled patients with ES-SCLC who received immunotherapy as first-line treatment from two centers. Patients were divided into a training and an external test cohort. Chest Computed Tomography (CT) images were obtained at baseline and after 2-3 cycles of immunotherapy. Each lesion was segmented based on intratumoral regions (ITR) in the plain scan (PS) and venous phase (VP) CT images. Radiomic features, including absolute and relative delta features were extracted. Four signatures were established by the least absolute shrinkage and selection operator (LASSO) after selecti

SUBMITTER: Fan J 

PROVIDER: S-EPMC12741101 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature