The Investigation and Prediction of Voriconazole-Associated Hepatotoxicity under Therapeutic Drug Monitoring

Voriconazole is commonly used as the first-line agent to treat invasive fungal infections (IFIs), but the induction of hepatotoxicity limits its use. To improve the treatment outcomes and minimize toxicity, doctors often administer Therapeutic Drug Monitoring (TDM) to patients receiving voriconazole treatment. Here, we conducted a real-world clinical investigation of voriconazole-treated patients and found significant differences between the TDM (n=318) and non-TDM cohort (n=6,379), and such incidence of hepatotoxicity showed 10.6% in the non-TDM cohort, compared with 21.5% in the TDM cohort. Based on our previous investigation, we presented and compared several machine learning models (including AdaBoost, decision tree, GBDT, logistic regression, neural networks, and random forest) for the early warning of voriconazole- associated hepatoxicity. Through the five-fold cross validation, the logistic model outperformed other models with a mean AUC of 0.7933 +/- 0.0934. Our findings offer important insights into the safe and effective application of voriconazole.