Construction and evaluation of a risk model for adverse outcomes of necrotizing enterocolitis based on LASSO-Cox regression

Objective This study aimed to develop a nomogram to predict adverse outcomes in neonates with necrotizing enterocolitis (NEC). Methods In this retrospective study on neonates with NEC, data on perinatal characteristics, clinical features, laboratory findings, and x-ray examinations were collected for the included patients. A risk model and its nomogram were developed using the least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Results A total of 182 cases of NEC were included and divided into a training set (148 cases) and a temporal validation set (34 cases). Eight features, including weight p = 0.471, HR = 0.99 (95% CI: 0.98–1.00), history of congenital heart disease p 0.001, HR = 3.13 (95% CI:1.75–5.61), blood transfusion before onset p = 0.757, HR = 0.85 (95%CI:0.29–2.45), antibiotic exposure before onset p = 0.003, HR = 5.52 (95% CI:1.81–16.83), C-reactive protein (CRP) at onset p = 0.757, HR = 1.01 (95%CI:1.00–1.02), plasma sodium at onset p 0.001, HR = 4.73 (95%CI:2.61–8.59), dynamic abdominal x-ray score change p = 0.001, HR = 4.90 (95%CI:2.69–8.93), and antibiotic treatment regimen p = 0.250, HR = 1.83 (0.65–5.15), were ultimately selected for model building. The C-index for the predictive model was 0.850 (95% CI: 0.804–0.897) for the training set and 0.7880.788 (95% CI: 0.656–0.921) for the validation set. The area under the ROC curve (AUC) at 8-, 10-, and 12-days were 0.889 (95% CI: 0.822–0.956), 0.891 (95% CI: 0.829–0.953), and 0.893 (95% CI:0.832–0.954) in the training group, and 0.812 (95% CI: 0.633–0.991), 0.846 (95% CI: 0.695–0.998), and 0.798 (95%CI: 0.623–0.973) in the validation group, respectively. Calibration curves showed good concordance between the predicted and observed outcomes, and DCA demonstrated adequate clinical benefit. Conclusions The LASSO-Cox model effectively identifies NEC neonates at high risk of adverse outcomes across all time points. Notably, at earlier time points (such as the 8-day mark), the model also demonstrates strong predictive performance, facilitating the early prediction of adverse outcomes in infants with NEC. This early prediction can contribute to timely clinical decision-making and ultimately improve patient prognosis.