Identification of CT based radiomic biomarkers for progression free survival in head and neck squamous cell carcinoma.

ABSTRACT: This study addresses the limited noninvasive tools for Head and Neck Squamous Cell Carcinoma (HNSCC) progression-free survival (PFS) prediction by identifying Computed Tomography (CT)-based biomarkers for predicting prognosis. A retrospective analysis was conducted on data from 203 HNSCC patients. An ensemble feature selection involving correlation analysis, univariate survival analysis, best-subset selection, and the LASSO-Cox algorithm was used to select functional features, which were then used to build final Cox Proportional Hazards models (CPH). Our CPH achieved a 0.69 concordance index in an external indepedent cohort of 77 patients. The model identified five CT-based radiomics features, Gradient ngtdm Contrast, Log_σ=33D-FirstorderRootMeanSquared, Log_σ=0.13D-gls

SUBMITTER: Ling X 

PROVIDER: S-EPMC11711663 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature