Multiparameter diagnostic model using S100A9, CCL5 and blood biomarkers for nasopharyngeal carcinoma.

ABSTRACT: This study aimed to analyze S100A9 and CCL5 levels in patients with nasopharyngeal carcinoma (NPC) and evaluate their predictive value as blood-based indicators for NPC diagnosis. Serum S100A9 and CCL5 levels were measured in 123 patients newly diagnosed with NPC and 107 patients without NPC. Additionally, 38 patients (19 with NPC and 19 without) were recruited from Xiangya Hospital as an external validation cohort. Logistic regression was used to identify risk factors for NPC. Variable selection was conducted using least absolute shrinkage and selection operator (LASSO) regression. NPC prediction models were developed using four machine-learning algorithms, and their performance was evaluated with ROC curves. Calibration curves, decision curve analysis (DCA), and Shapley additive explanat

SUBMITTER: Long L 

PROVIDER: S-EPMC11876657 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature