首页> 外文期刊>Therapeutic Drug Monitoring >A population pharmacokinetic model of cyclosporine in the early postoperative phase in patients with liver transplants, and its predictive performance with Bayesian fitting.
【24h】

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

机译:肝移植患者术后早期环孢素的总体药代动力学模型及其在贝叶斯拟合中的预测性能。

获取原文
获取原文并翻译 | 示例
       

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 microg/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.
机译:个人计算机程序可用于个性化药物治疗方案,激发了人们对群体药代动力学建模的兴趣。这项研究使用NPEM2软件在术后第一周内确定第一批25例肝移植受者中环孢菌素群体的药代动力学参数值和分布。在第二组25名患者中,作者使用这些值通过USC * PACK PC程序评估环孢菌素血药浓度的贝叶斯预测性能。在研究期间,所有患者均接受连续静脉输注治疗。一室模型药代动力学参数-体积与体重的斜率(Vs)和消除速率常数(Kel)值(平均值:Vs = 2.177 l / kg,Kel = 0.235 h(-1);中值:Vs = 1.559 l / kg,Kel = 0.163 h(-1);变异系数百分比(Vs = 92%,Kel = 79%)显得合理,并显示了NPEM2处理稀疏数据的能力。在第1天,第2天或第3天的浓度下进行研究时,预测偏倚分别为-0.030,-0.013和0.013 microg / ml,这表明手术后即刻环孢菌素的清除率更高,此后的清除率降低。前三个血液水平和贝叶斯拟合程序,在第二组移植接受者的四分之三以上(76%)中,有可能准确地预测每个患者至少一半的后续测量血液水平(20%以内) ,对于40%的患者,作者在100%的患者中获得了准确的预测以后的血液水平。对于少数患者(12%),他们发现预测很差。原因尚不清楚。结果表明,该人群模型和使用两个或三个血液水平的贝叶斯拟合程序可以合理,谨慎地用于实时控制大多数新肝移植患者的环孢素血液水平。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号