LASSO-based nomograms predict early death in small cell lung cancer (SCLC) patients with brain metastasis.

ABSTRACT:

Background

Small cell lung cancer with brain metastasis (SCLC-BM) is associated with a poor prognosis and a high probability of death. However, to date, few models exist to predict early death (ED) in patients with SCLC-BM. This study aimed to construct nomograms to predict ED in patients diagnosed with SCLC-BM.

Methods

The data of SCLC-BM patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2015). The patients were randomly divided into training and test cohorts at a 7:3 ratio. Univariate regression was first performed to assess the significance of each variable. Least absolute shrinkage and selection operator (LASSO) regression was then applied to identify the most critical and minimum prognostic factors. Subsequently, a multiv

SUBMITTER: Liu X 

PROVIDER: S-EPMC12776076 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature