Machine Learning Model Accurately Predicts Early Recurrence in PCCA Patients

A multicenter study developed a machine learning model to predict early recurrence in patients with perihilar cholangiocarcinoma (PCCA) after curative surgery. The model, leveraging five key factors, including carbohydrate antigen 19-9 and tumor size, achieved superior predictive performance, particularly with the random forest algorithm (AUC: 0.983) compared to others. High-risk patients showed significantly different recurrence-free survival compared to low-risk individuals (p < 0.001), facilitating informed treatment decisions for physicians.