DUAL VALIDATION ANALYSIS OF SERUM CYP3A4 IN PREDICTING NEC IN PRETERM INFANTS

Objective: Necrotizing enterocolitis (NEC) is a life-threatening condition in premature infants, where timely diagnosis and intervention are crucial. This study investigated the potential of serum CYP3A4 as an early predictive biomarker for NEC and developed a predictive model incorporating CYP3A4. Methods: Bioinformatics analyses were performed to assess the association between CYP3A4 and NEC. Serum samples were collected from preterm infants with a gestational age of less than 32 weeks, born between January 2023 and December 2024. The cohort included 34 infants with NEC and 34 without NEC. Serum CYP3A4 levels were measured using enzyme-linked immunosorbent assay, and clinical characteristics of NEC infants were analyzed using machine learning to identify predictive factors. A multivariate logistic regression model was constructed and evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results: Serum CYP3A4 levels were significantly higher in NEC infants and were positively associated with disease severity ( P < 0.05). CYP3A4 demonstrated positive correlations with inflammatory markers, including C-reactive protein and the neutrophil-to-lymphocyte ratio, indicating its potential role in the inflammatory cascade and intestinal barrier disruption. In the predictive model, CYP3A4 emerged as a key variable, achieving an area under the ROC curve of 0.877, reflecting strong predictive accuracy. Calibration plots and DCA confirmed the model's reliability and clinical utility. Conclusion: Serum CYP3A4 is a promising biomarker for the early diagnosis of NEC, and the prediction model demonstrates robust performance. Future multicenter studies are warranted to validate its consistency and elucidate the underlying mechanisms.