Figurski Michal J, Nawrocki Artur, Pescovitz Mark D, Bouw Rene, Shaw Leslie M
Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
Ther Drug Monit. 2008 Aug;30(4):445-55. doi: 10.1097/FTD.0b013e318180c986.
Limited sampling strategies for estimation of the area under the concentration time curve (AUC) for mycophenolic acid (MPA) co-administered with sirolimus (SRL) have not been previously evaluated. The authors developed and validated 68 regression models for estimation of MPA AUC for two groups of patients, one with concomitant SRL (n = 24) and the second with concomitant cyclosporine (n=14), using various combinations of time points between 0 and 4 hours after drug administration. To provide as robust a model as possible, a dataset-splitting method similar to a bootstrap was used. In this method, the dataset was randomly split in half 100 times. Each time, one half of the data was used to estimate the equation coefficients, and the other half was used to test and validate the models. Final models were obtained by calculating the median values of the coefficients. Substantial differences were found in the pharmacokinetics of MPA between these groups. The mean MPA AUC as well as the standard deviation was much greater in the SRL group, 56.4 +/- 23.5 mg.h/L, compared with 30.4 +/- 11.0 mg.h/L in the cyclosporine group (P < 0.001). Mean maximum concentration was also greater in the SRL group: 16.4 +/- 7.7 mg/L versus 11.7 +/- 7.1mg/L (P < 0.005). The second absorption peak in the pharmacokinetic profile, presumed to result from enterohepatic recycling of glucuronide MPA, was observed in 70% of the profiles in the SRL group and in 35% of profiles from the cyclosporine group. Substantial differences in the predictive performance of the regression models, based on the same time points, were observed between the two groups. The best model for the SRL group was based on 0 (trough) and 40 minutes and 4 hour time points with R2, root mean squared error, and predictive performance values of 0.82, 10.0, and 78%, respectively. In the cyclosporine group, the best model was 0 and 40 minutes and 2 hours, with R2, RMSE, and predictive performance values of 0.86, 4.1, and 83%, respectively. The model with 2 hours as the last time point is also recommended for the SRL group for practical reasons, with the above parameters of 0.77, 11.3, and 69%, respectively.
对于与西罗莫司(SRL)联合使用的霉酚酸(MPA),此前尚未评估过用于估算其浓度-时间曲线下面积(AUC)的有限采样策略。作者针对两组患者开发并验证了68个回归模型,用于估算MPA的AUC,一组患者同时使用SRL(n = 24),另一组同时使用环孢素(n = 14),使用给药后0至4小时之间不同时间点的各种组合。为了尽可能提供一个稳健的模型,使用了一种类似于自助法的数据集拆分方法。在这种方法中,数据集被随机分成两半,共100次。每次,一半数据用于估算方程系数,另一半用于测试和验证模型。通过计算系数的中位数获得最终模型。发现这些组之间MPA的药代动力学存在显著差异。SRL组的平均MPA AUC以及标准差要大得多,分别为56.4±23.5mg·h/L,而环孢素组为30.4±11.0mg·h/L(P < 0.001)。SRL组的平均最大浓度也更高:分别为16.4±7.7mg/L和11.7±7.1mg/L(P < 0.005)。药代动力学曲线中的第二个吸收峰,推测是由MPA葡糖醛酸的肠肝循环导致的,在SRL组70%的曲线中观察到,在环孢素组35%的曲线中观察到。基于相同时间点,观察到两组回归模型的预测性能存在显著差异。SRL组的最佳模型基于0(谷值)、40分钟和4小时时间点,R2、均方根误差和预测性能值分别为0.82、10.0和78%。在环孢素组中,最佳模型是0、40分钟和2小时,R2、RMSE和预测性能值分别为0.86、4.1和83%。出于实际原因,对于SRL组也推荐以2小时作为最后一个时间点的模型,上述参数分别为0.77、11.3和69%。