Machine learning predicts surgical outcomes in cholangiocarcinoma patients

A machine learning model developed from 376 intrahepatic cholangiocarcinoma patients effectively predicts textbook outcomes. Key preoperative factors include Child-Pugh classification, ECOG score, hepatitis B status, and tumor size. The model achieved high accuracy during internal (AUC = 0.8825) and external validation (AUC = 0.8346). Survival analysis indicated that patients achieving textbook outcomes had disease-free survival rates of 64.2%, 56.8%, and 43.4% at one, two, and three years, respectively.