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ORIGINAL RESEARCH article

Front. Pharmacol.

Sec. Pharmacoepidemiology

Voriconazole-Associated Liver Injury: Clinical Risk Factor Identification and Predictive Nomogram Construction

Provisionally accepted
Dongge  FengDongge Feng1,2Ma  YiyiMa Yiyi1Xiaoyi  LiuXiaoyi Liu1,2Si  TangSi Tang1,2Shijian  XiangShijian Xiang3*Shasha  LiShasha Li1*
  • 1First Affiliated Hospital of Jinan University, Guangzhou, China
  • 2Jinan University Department of Pharmacy, Guangzhou, China
  • 3Department of Pharmacy, the Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China

The final, formatted version of the article will be published soon.

Objective: Investigate the high risk factors contributed to voriconazole-induced liver injury and develop a predictive nomogram for voriconazole-induced liver injury risk, thereby optimizing the clinical medication safety. Methods: This observational study retrospectively analyzed the electronic health records of hospitalized patients who received voriconazole treatment or prophylaxis at a tertiary hospital. Patients who met the inclusion and exclusion criteria were enrolled between June 2020 and June 2024, and their general biological data were collected. The diagnosis and severity grading of voriconazole-associated liver injury were determined according to the diagnostic and treatment guidelines for drug-induced liver injury. Patients were categorized into liver injury and non-injury groups based on the results of post-treatment liver function tests. Associations between baseline characteristics and liver injury were analyzed using non-parametric and chi-squared tests. To avoid omitting potentially significant factors, variables demonstrating P ≤ 0.1 in univariate screening and retained through least absolute shrinkage and selection operator (LASSO) regression underwent multivariate logistic regression to identify independent predictors. The nomogram was developed and internally validated through receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA). Results: Among the 1,964 patients screened, 1,196 were excluded, leaving 768 patients included in the statistical analysis. Liver injury occurred in 95 patients, resulting in an incidence rate of 12.4%. Multivariable logistic regression analysis demonstrated that total cholesterol (TC) (OR = 1.893, P<0.01), concomitant use of glucocorticoids (OR=1.861, P=0.041), ezetimibe (OR=7.453, P=0.047), and caspofungin (OR=2.485, P=0.032). Patients with TC levels exceeding 4.485 mmol/L exhibited a significantly elevated risk of liver injury. ROC analysis revealed an area under the curve (AUC) of 0.728 (95% CI:0.66-0.797), with a sensitivity of 0.661 and specificity of 0.722. Internal validation indicated good discrimination and calibration, with predicted probabilities closely aligned with actual outcomes. The decision curve analysis suggested a substantial net clinical benefit. These findings were subsequently validated in a test cohort. Conclusion: Concomitant use of ezetimibe, caspofungin, glucocorticoids, and TC levels exceeding 4.485 mmol/L are independent risk factors for voriconazole-induced liver injury. The developed nomogram model offers clinically meaningful predictions for drug-induced liver injury risk, facilitating the optimization of voriconazole therapy safety.

Keywords: Voriconazole, nomogram, Drug-Induced Liver Injury, predictive model, Real-world study

Received: 19 Aug 2025; Accepted: 01 Dec 2025.

Copyright: © 2025 Feng, Yiyi, Liu, Tang, Xiang and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Shijian Xiang
Shasha Li

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