Predictive Models Enhance Surgical Decision-Making in Hepatic Echinococcosis

A study developed predictive models to aid surgical decision-making for hepatic cystic echinococcosis (CE). Analyzing data from 406 patients, the Cox regression model achieved a concordance index of 0.94 and AUC of 0.96. The decision tree model highlighted imaging findings, cyst stage, and symptoms as key predictors, with a mean AUC of 0.950. These validated models aim to optimize patient management by integrating dynamic tools into clinical practice, improving allocation to surgical or non-surgical interventions.