Radiomics Signature Predicts the Recurrence-Free Survival in Stage I Non-Small-Cell Lung Cancer

Abstract Background We aimed to explore the predictive value of radiomics signature for the recurrence-free survival (RFS) in patients with resected stage I non-small-cell lung cancer (NSCLC). Methods From January 2009 to December 2011, patients with resected stage I NSCLC were divided into sub-solid and pure-solid groups according to presence of ground glass opacity (GGO) in computed tomography (CT). A total of 107 extracted radiomics features were reduced to 8 features by using LASSO-Cox analysis to develop a radiomics signature for RFS prediction. Univariate and multivariate survival analyses were applied to identify independent prognostic variables, the Harrell concordance index (C-index) was measured to assess their prediction performance. Results Our study included 378 patients with a median follow-up time of 63.2 months. The radiomics signature could stratify all patients into high-risk (180/378) and low-risk group (198/378) with different RFS (p Conclusion Radiomics signature may be an independent imaging biomarker for predicting the survival, which may guide for personalizing treatment option in patients with stage I NSCLC.