Wacke R, Rohde B, Engel G, Kundt G, Hehl E M, Bast R, Seiter H, Drewelow B
Department of Clinical Pharmacology, Institute of Experimental and Clinical Pharmacology and Toxicology, University of Rostock, Germany.
Eur J Clin Pharmacol. 2000 Apr;56(1):43-8. doi: 10.1007/s002280050718.
The clinical outcome of patients after organ transplantation is correlated with cyclosporin A (CyA) exposure. It is generally accepted that the area under the concentration-time curve (AUC) provides a reliable means for drug exposure. However, in routine therapeutic drug monitoring (TDM) of CyA, trough levels are mostly used. Currently, a number of different new concepts of CyA-TDM, including approaches such as single, double or triple time-point and abbreviated AUC determinations, have been introduced. The purpose of this study was to compare the predictive value of the different strategies of TDM.
Calculations were based on 40 individual concentration time profiles after oral administration of CyA to patients who had been included into an ongoing prospective clinical trial. Non-compartmental analysis was used to calculate the AUC0-12h. Multiple linear regression was performed to describe the relationship between the different sets of blood concentrations and the respective AUC0-12h as well as to evaluate their predictive value regarding AUC. Predictive performance was assessed by prediction bias and prediction precision, which were estimated as the mean prediction error and root mean squared error, respectively.
When comparing the various combinations of time points, it was found that one-point approaches showed the strongest differences with regard to the predictive value; the associated r2 values differed from 0.203 to 0.792. The two and three time-point approaches showed lower differences - r2 0.802-0.972. The four-point and five-point approaches (r2 0.942-0.982) were the strongest predictors for CyA AUC0-12h. Relative bias ranged from -27.7% to 63.8% and changed significantly when multiple-point predictors were used. In those cases, the predictive performance improved. Considering the predictive performance as well as the smallest bias and highest prediction precision, C3, C1 + C3, C1 + C3 + C6 and C1 + C2 + C3 + C6 were the best predictors.
The results of this study indicate that in kidney transplant patients a clinically sufficient precise estimation of the CyA AUC is possible using two or three concentration time points.
器官移植患者的临床结局与环孢素A（CyA）暴露相关。一般认为，浓度-时间曲线下面积（AUC）为药物暴露提供了可靠的衡量方法。然而，在CyA的常规治疗药物监测（TDM）中，大多使用谷浓度。目前，已经引入了许多不同的CyA-TDM新概念，包括单点、双点或三点以及简化AUC测定等方法。本研究的目的是比较不同TDM策略的预测价值。
计算基于对纳入一项正在进行的前瞻性临床试验的患者口服CyA后的40个个体浓度-时间曲线。采用非房室分析计算AUC0-12h。进行多元线性回归以描述不同血药浓度组与各自AUC0-12h之间的关系，并评估它们对AUC的预测价值。通过预测偏差和预测精度评估预测性能，分别将其估计为平均预测误差和均方根误差。
比较不同时间点组合时发现，单点法在预测价值方面差异最大；相关的r2值在0.203至0.792之间。两点和三点法差异较小——r2为0.802-0.972。四点和五点法（r2为0.942-0.982）是CyA AUC0-12h最强的预测指标。相对偏差范围为-27.7%至63.8%，使用多点预测指标时显著变化。在这些情况下，预测性能有所改善。综合考虑预测性能、最小偏差和最高预测精度，C3、C1 + C3、C1 + C3 + C6和C1 + C2 + C3 + C6是最佳预测指标。
本研究结果表明，对于肾移植患者，使用两个或三个浓度时间点可以实现临床上对CyA AUC的足够精确估计。
