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  • Title: Validation of limited sampling strategy for the estimation of mycophenolic acid exposure in Chinese adult liver transplant recipients.
    Author: Hao C, Erzheng C, Anwei M, Zhicheng Y, Baiyong S, Xiaxing D, Weixia Z, Chenghong P, Hongwei L.
    Journal: Liver Transpl; 2007 Dec; 13(12):1684-93. PubMed ID: 18044788.
    Abstract:
    Mycophenolate mofetil (MMF) is indicated as immunosuppressive therapy in liver transplantation. The abbreviated models for the estimation of mycophenolic acid (MPA) area under the concentration-time curve (AUC) have been established by limited sampling strategies (LSSs) in adult liver transplant recipients. In the current study, the performance of the abbreviated models to predict MPA exposure was validated in an independent group of patients. A total of 30 MPA pharmacokinetic profiles from 30 liver transplant recipients receiving MMF in combination with tacrolimus were used to compare 8 models' performance with a full 10 time-point MPA-AUC. Linear regression analysis and Bland-Altman analysis were used to compare the estimated MPA-AUC0-12h from each model against the measured MPA-AUC0-12h. A wide range of agreement was shown when estimated MPA-AUC0-12h was compared with measured MPA-AUC0-12h, and the range of coefficient of determination (r2) was from 0.479 to 0.936. The model based on MPA pharmacokinetic parameters C1h, C2h, C6h, and C8h had the best ability to predict measured MPA-AUC0-12h, with the best coefficient of determination (r2=0.936), the excellent prediction bias (2.18%), the best prediction precision (5.11%), and the best prediction variation (2SD=+/-7.88 mg.h/L). However, the model based on MPA pharmacokinetic sampling time points C1h, C2h, and C4h was more suitable when concerned with clinical convenience, which had shorter sampling interval, an excellent coefficient of determination (r2=0.795), an excellent prediction bias (3.48%), an acceptable prediction precision (14.37%), and a good prediction variation (2SD=+/-13.23 mg.h/L). Measured MPA-AUC0-12h could be best predicted by using MPA pharmacokinetic parameters C1h, C2h, C6h, and C8h. The model based on MPA pharmacokinetic parameters C1h, C2h, and C4h was more feasible in clinical application.
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