2005 年 125 巻 5 号 p. 441-447
Cyclosporine (CyA) is the most commonly used immunosuppressive agent in patients who undergo kidney transplantation. Dosage adjustment of CyA is usually based on trough levels. Recently, trough levels have been replacing the area under the concentration-time curve during the first 4 h after CyA administration (AUC0—4). The aim of this study was to compare the predictive values obtained using three different methods of AUC0—4 monitoring. AUC0—4 was calculated from 0 to 4 h in early and stable renal transplant patients using the trapezoidal rule. The predicted AUC0—4 was calculated using three different methods: the multiple regression equation reported by Uchida et al.; Bayesian estimation for modified population pharmacokinetic parameters reported by Yoshida et al.; and modified population pharmacokinetic parameters reported by Cremers et al. The predicted AUC0—4 was assessed on the basis of predictive bias, precision, and correlation coefficient. The predicted AUC0—4 values obtained using three methods through measurement of three blood samples showed small differences in predictive bias, precision, and correlation coefficient. In the prediction of AUC0—4 measurement of one blood sample from stable renal transplant patients, the performance of the regression equation reported by Uchida depended on sampling time. On the other hand, the performance of Bayesian estimation with modified pharmacokinetic parameters reported by Yoshida through measurement of one blood sample, which is not dependent on sampling time, showed a small difference in the correlation coefficient. The prediction of AUC0—4 using a regression equation required accurate sampling time. In this study, the prediction of AUC0—4 using Bayesian estimation did not require accurate sampling time in the AUC0—4 monitoring of CyA. Thus Bayesian estimation is asumed to be clinically useful in the dosage adjustment of CyA.