A multi-biomarker nomogram based on miR-155-5p and NETs predicting deep vein thrombosis risk stratification

Abstract Objective Deep vein thrombosis (DVT) represents a major thrombo-inflammatory disorder with substantial diagnostic challenges. Emerging evidence implicates that neutrophil extracellular traps (NETs) and miR-155 are involved in thrombosis, yet their integrated predictive utility remains unexplored. The aim of this study is to develop and validate a multi-biomarker nomogram incorporating miR-155-5p and NETs markers for individualized risk stratification of DVT. Method A total of 110 patients diagnosed with DVT by angiography from January 2022 to December 2023 were selected and matched with 61 healthy subjects. The differences and correlations of serum miR-155-5p and NETs markers between the two groups were compared. Multivariate logistic regression identified independent predictors, and a predictive nomogram was constructed. Internal validation was performed using bootstrap resampling. Discriminative capacity, calibration, and clinical utility were assessed by ROC analysis, calibration curve, and decision curve analysis (DCA). Results The serum miR-155-5p and NETs levels of the two groups were analyzed, and the results showed a significant enhancement in serum miR-155-5p and NETs levels in DVT patients compared to healthy subjects. The study further analyzed the correlation between serum miR-155-5p and related NETs markers, and found that serum miR-155-5p was positively correlated with MPO-DNA (r = 0.480) and citH3 (r = 0.494). Logistic analysis indicated that miR-155-5p (OR = 3.339), citH3 (OR = 2.602), and D-dimer (OR = 2.701) miR-155-5p (OR = 3.339), citH3 (OR = 2.602), D-dimer (OR = 2.701), Neutrophil-to-Lymphocyte Ratio (NLR) (OR = 1.582), and MHR (OR = 1.117) were independent risk factors for the occurrence of DVT. The integrated nomogram demonstrated excellent discriminative performance (AUC = 0.955) and robust calibration with minimal overfitting. DCA confirmed significant clinical utility across a broad threshold probability range. Conclusions We developed and internally validated a novel multi-biomarker nomogram that integrates miR-155-5p, NETs marker citH3, and inflammatory indices, providing a robust, quantitative tool for individualized DVT risk prediction. This model offers superior discriminative capacity and clinical applicability, warranting external validation for translation into clinical practice.