An inflammation-nutrition-surgery-based INSEP model and a web-based clinical decision support system for predicting early postoperative infection in elderly patients with hepatocellular carcinoma: a multicenter retrospective study

Abstract

Background Early postoperative infection (EPI) is common in elderly patients with hepatocellular carcinoma (HCC) and is associated with poor prognosis. Effective risk prediction tools are urgently needed for early identification. This study aimed to develop and validate an inflammation-, nutrition-, and surgery-based INSEP nomogram model for predicting EPI-related adverse events in this population. Methods A total of 988 elderly HCC patients from two medical centers were retrospectively enrolled and randomly divided into a training dataset (n = 692) and an internal validation dataset (n = 296), while 381 patients from a third medical center served as an external validation dataset. Restricted cubic spline (RCS), receiver operating characteristic (ROC), least absolute shrinkage and selection operator (LASSO), and multivariable logistic regression analyses were performed to identify independent predictors of EPI and develop the INSEP nomogram. An online risk calculator was established, and model performance was assessed using ROC, calibration, decision curve, and clinical impact curve analyses. Results The INSEP model incorporated five independent predictors: SII ≥600 (OR 2.73, p = 0.023), CONUT ≥ 3 (OR 7.84, p < 0.001), ECOG 2–4 (OR 4.96, p < 0.001), laparoscopic surgery (OR 0.83, p = 0.025), and surgical duration ≥180 min (OR 7.44, p < 0.001). The model achieved AUCs of 0.870 in the training dataset, 0.803 in internal validation, and 0.798 in external validation, with good calibration and clinical utility. Two representative case demonstrations confirmed the model's accurate risk stratification: a low-risk patient (predicted EPI 3.3%) had no infection, while a high-risk patient (predicted 97.0%) developed pneumonia. Usability testing by three independent hepatobiliary surgeons (6–10 years of experience) showed efficient operation (25–60 s per case), intuitive interface, and clear output, with no system errors identified. Conclusion The INSEP model is a reliable and practical tool for individualized EPI risk assessment in elderly HCC patients undergoing curative hepatectomy, demonstrating good predictive performance, clinical applicability, and user acceptability.