Hidefumi Kasai1, Yasuhiro Tsuji2, Yoichi Hiraki3, Moeko Tsuruyama3, Hideto To4, Yoshihiro Yamamoto5. 1. Department of Medical Pharmaceutics, Faculty of Pharmaceutical Sciences, University of Toyama, 2630 Sugitani, Toyama, Toyama, 930-0194, Japan; Certara G.K., 4-2-12, Minato-ku, Tokyo, 105-0001, Japan. 2. Department of Medical Pharmaceutics, Faculty of Pharmaceutical Sciences, University of Toyama, 2630 Sugitani, Toyama, Toyama, 930-0194, Japan. Electronic address: ytsuji@pha.u-toyama.ac.jp. 3. Department of Pharmacy, National Hospital Organization Beppu Medical Center, 1473 Uchikamado, Beppu, Oita, 874-0011, Japan. 4. Department of Medical Pharmaceutics, Faculty of Pharmaceutical Sciences, University of Toyama, 2630 Sugitani, Toyama, Toyama, 930-0194, Japan. 5. Department of Clinical Infectious Diseases, Graduate School of Medicine and Pharmaceutical Sciences for Research, University of Toyama, 2630 Sugitani, Toyama, Toyama, 930-0194, Japan.
Abstract
OBJECTIVE: Serum cystatin C (CysC) has recently been proposed as an alternative marker to serum creatinine (SCR) for estimating renal clearance. In the present study, we performed a population pharmacokinetic analysis of teicoplanin (TEIC), which is mainly eliminated through the kidneys, using CysC as a predictor for renal clearance. METHODS: Thirty-six patients with MRSA infections who were administrated to the National Hospital Organization Beppu Medical Center between January 2012 and December 2013 were enrolled and gave 123 sets of blood TEIC concentration data. Renal clearance was estimated by the Hoek equation using CysC, by creatinine clearance predicted by the Cockcroft-Gault equation using SCR, or directly by CysC. One compartment open model with inter-individual variabilities for renal clearance and the volume of distribution as well as an additional residual error model was used to estimate population pharmacokinetic parameters for TEIC. RESULTS: The model with the best predictability was that with CysC as a predictor for renal clearance; it showed better significance than the models using estimated the glomerular filtration rate by the Hoek equation or CLcr. The final model was as follows: CL (L/hr) = 0.510 × (CysC/1.4)-0.68 × Total body weight/600.81, omega (CL) = 19.8% CV, VC (L) = 78.1, omega (V) = 42.7% CV. CONCLUSION: The present results show the usefulness of CysC to more accurately predict the pharmacokinetics of drugs mainly eliminated through the kidneys, such as TEIC. However, since the sample size in this study was relatively small, further investigations on renal clearance predictability using CysC are needed.
OBJECTIVE: Serum cystatin C (CysC) has recently been proposed as an alternative marker to serum creatinine (SCR) for estimating renal clearance. In the present study, we performed a population pharmacokinetic analysis of teicoplanin (TEIC), which is mainly eliminated through the kidneys, using CysC as a predictor for renal clearance. METHODS: Thirty-six patients with MRSA infections who were administrated to the National Hospital Organization Beppu Medical Center between January 2012 and December 2013 were enrolled and gave 123 sets of blood TEIC concentration data. Renal clearance was estimated by the Hoek equation using CysC, by creatinine clearance predicted by the Cockcroft-Gault equation using SCR, or directly by CysC. One compartment open model with inter-individual variabilities for renal clearance and the volume of distribution as well as an additional residual error model was used to estimate population pharmacokinetic parameters for TEIC. RESULTS: The model with the best predictability was that with CysC as a predictor for renal clearance; it showed better significance than the models using estimated the glomerular filtration rate by the Hoek equation or CLcr. The final model was as follows: CL (L/hr) = 0.510 × (CysC/1.4)-0.68 × Total body weight/600.81, omega (CL) = 19.8% CV, VC (L) = 78.1, omega (V) = 42.7% CV. CONCLUSION: The present results show the usefulness of CysC to more accurately predict the pharmacokinetics of drugs mainly eliminated through the kidneys, such as TEIC. However, since the sample size in this study was relatively small, further investigations on renal clearance predictability using CysC are needed.