Department of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
Institute of Clinical Pharmacy, Central South University, Changsha, China.
Clin Transl Sci. 2021 Mar;14(2):702-711. doi: 10.1111/cts.12932. Epub 2020 Nov 30.
Voriconazole is the mainstay for the treatment of invasive fungal infections in patients who underwent a kidney transplant. Variant CYP2C19 alleles, hepatic function, and concomitant medications are directly involved in the metabolism of voriconazole. However, the drug is also associated with numerous adverse events. The purpose of this study was to identify predictors of adverse events using binary logistic regression and to measure its trough concentration using multiple linear modeling. We conducted a prospective analysis of 93 kidney recipients cotreated with voriconazole and recorded 213 trough concentrations of it. Predictors of the adverse events were voriconazole trough concentration with the odds ratios (OR) of 2.614 (P = 0.016), cytochrome P450 2C19 (CYP2C19), and hemoglobin (OR 0.181, P = 0.005). The predictive power of these three factors was 91.30%. We also found that CYP2C19 phenotypes, hemoglobin, platelet count, and concomitant use of ilaprazole had quantitative relationships with voriconazole trough concentration. The fit coefficient of this regression equation was R = 0.336, demonstrating that the model explained 33.60% of interindividual variability in the disposition of voriconazole. In conclusion, predictors of adverse events are CYP2C19 phenotypes, hemoglobin, and voriconazole trough concentration. Determinants of the voriconazole trough concentration were CYP2C19 phenotypes, platelet count, hemoglobin, concomitant use of ilaprazole. If we consider these factors during voriconazole use, we are likely to maximize the treatment effect and minimize adverse events.
伏立康唑是治疗接受肾移植患者侵袭性真菌感染的主要药物。CYP2C19 等位基因变异、肝功能和伴随用药直接参与伏立康唑的代谢。然而，该药物也与许多不良事件相关。本研究旨在使用二项逻辑回归识别不良事件的预测因子，并使用多元线性建模测量其谷浓度。我们对 93 例接受伏立康唑联合治疗的肾移植受者进行了前瞻性分析，并记录了 213 次伏立康唑谷浓度。不良事件的预测因子是伏立康唑谷浓度，其比值比（OR）为 2.614（P=0.016）、细胞色素 P450 2C19（CYP2C19）和血红蛋白（OR 0.181，P=0.005）。这三个因素的预测能力为 91.30%。我们还发现，CYP2C19 表型、血红蛋白、血小板计数和奥美拉唑的同时使用与伏立康唑谷浓度呈定量关系。该回归方程的拟合系数 R 为 0.336，表明该模型解释了伏立康唑个体间处置变异性的 33.60%。总之，不良事件的预测因子是 CYP2C19 表型、血红蛋白和伏立康唑谷浓度。伏立康唑谷浓度的决定因素是 CYP2C19 表型、血小板计数、血红蛋白、奥美拉唑的同时使用。如果我们在使用伏立康唑时考虑这些因素，我们可能会最大限度地提高治疗效果并最小化不良事件。
