A population pharmacokinetic model of cyclosporine in the early postoperative phase in patients with liver transplants, and its predictive performance with Bayesian fitting

被引:21
作者
Charpiat, B
Falconi, I
Breant, V
Jelliffe, RW
Sab, JM
Ducerf, C
Fourcade, N
Thomasson, A
Baulieux, J
机构
[1] Hop Croix Rousse, Dept Pharm, F-69317 Lyon 04, France
[2] Univ So Calif, Sch Med, Lab Appl Pharmcokinet, Los Angeles, CA USA
[3] Hop Croix Rousse, Crit Care Unit, F-69317 Lyon, France
[4] Hop Croix Rousse, Dept Transplantat, F-69317 Lyon, France
[5] Hop Croix Rousse, Dept Anesthesiol, F-69317 Lyon, France
关键词
cyclosporine; population pharmacokinetic analysis; liver transplant; NPEM;
D O I
10.1097/00007691-199804000-00005
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
The availability of personal computer programs to individualize drug regimens has stimulated interest in modeling population pharmacokinetics, This study used the NPEM2 software to determine cyclosporine population pharmacokinetic parameter values and distributions in a first group of 25 recipients of liver transplants during their first postoperative week, On a second group of 25 patients, the authors used these values to evaluate Bayesian predictive performance of cyclosporine blood concentrations with the USC*PACK PC program. During the study period, all the patients have been treated by continuous intravenous infusion, The one-compartment model pharmacokinetic parameter-the slope of volume to body weight (Vs) and the elimination rate constant (Kel) values found (mean values: Vs = 2.177 l/kg, Kel = 0.235 h(-1): median values: Vs = 1.559 l/kg, Kel = 0.163 h(-1); the percent coefficient of variation (Vs = 92%, Kel = 79%) appear reasonable and show the ability of NPEM2 to deal with sparse data. When the predictions were studied with day 1, day 2, or day 3 concentrations, predictive bias was respectively -0.030, -0.013, and 0.013 mu g/ml, suggesting a greater clearance of cyclosporine immediately after surgery, the clearance decreasing in the days after. With the first three blood levels and the Bayesian fitting procedure, it was possible to predict at least half the subsequent measured blood levels of each patient accurately (within 20%) in more than three-quarters (76%) of the second group of recipients of transplants, and for 40% of patients the authors obtained accurate predictions in 100% of the subsequent blood levels, For a few patients (12%) they found quite poor predictions. The reason for this is unclear, The results suggest that this population model and the Bayesian fitting procedure using two or three blood levels can be reasonably and carefully used to control, in real time, cyclosporine blood levels in a majority of new patients with liver transplants.
引用
收藏
页码:158 / 164
页数:7
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