A Nomogram for Predicting Recurrence in Stage I Non-Small Cell Lung Cancer.

ABSTRACT:

Background

Early-stage non-small cell lung cancer (NSCLC) is being diagnosed increasingly, and in 30% of diagnosed patients, recurrence will develop within 5 years. Thus, it is urgent to identify recurrence-related markers to optimize the management of patient-tailored therapeutics.

Methods

The eligible datasets were downloaded from TCGA and GEO. In the discovery phase, two algorithms, least absolute shrinkage and selector operation and support vector machine-recursive feature elimination, were used to identify candidate genes. The recurrence-associated signature was developed by penalized Cox regression. The nomogram was constructed and further tested via other independent cohorts.

Results

In this retrospective study, 14 eligible datasets and 7 published signatures w

SUBMITTER: Bian R 

PROVIDER: S-EPMC11586294 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature