Department of Experimental & Clinical Pharmacology, 717 Delaware Street, University of Minnesota, Minneapolis, MN 55455, USA.
Pharmacogenomics. 2012 Jul;13(10):1141-7. doi: 10.2217/pgs.12.98.
Tacrolimus is an immunosuppressant used in transplantation. This article reports the validation of the authors' recently developed genetics-based tacrolimus equation that predicts troughs.
Validation was performed in an independent cohort of 795 kidney transplant recipients receiving tacrolimus. The performance of the equation to predict initial troughs was assessed by calculating the bias and precision of the equation. For all troughs in the first 6 months post-transplant, a comparison was made between the troughs predicted using the equation versus those predicted using a basic apparent clearance model with no covariates.
For initial troughs, the equation had a low bias (0.2 ng/ml) and high precision (1.8 ng/ml). For all troughs, the equation predicted troughs significantly better than the basic apparent clearance model.
The tacrolimus equation had good bias and precision in predicting initial troughs and performed better than a basic apparent clearance model for all the troughs.
他克莫司是一种在移植中使用的免疫抑制剂。本文报告了作者最近开发的基于遗传学的他克莫司预测谷浓度公式的验证。
在接受他克莫司治疗的 795 例肾移植受者的独立队列中进行了验证。通过计算方程预测初始谷浓度的偏差和精度来评估方程预测初始谷浓度的性能。对于移植后前 6 个月的所有谷浓度，使用方程预测的谷浓度与不包含协变量的基本表观清除模型预测的谷浓度进行了比较。
对于初始谷浓度，该方程的偏差较低（0.2ng/ml），精度较高（1.8ng/ml）。对于所有的谷浓度，该方程预测的谷浓度明显优于基本表观清除模型。
该他克莫司方程在预测初始谷浓度时具有良好的偏差和精度，并且对于所有谷浓度，其表现均优于基本表观清除模型。
