Georges B, Conil J-M, Seguin T, Dieye E, Cougot P, Decun J-F, Lavit M, Samii K, Houin G, Saivin S
Anesthésie Réanimation, CHU Rangueil, Toulouse, France.
Int J Clin Pharmacol Ther. 2008 Apr;46(4):157-64. doi: 10.5414/cpp46157.
The purpose of our study was to define and validate a population-pharmacokinetic model including the influence of patients' characteristics on the pharmacokinetics of cefepime.
A total of 55 patients were randomized in Group 1 (34 patients, 320 cefepime concentrations) for the model building and Group 2 (21 patients, 196 cefepime concentrations) for the validation group. They received cefepime as 2 g A 2 or as 4 g continuously. The population pharmacokinetic analysis was carried out using NONMEM and a baseline model was constructed for studying the influence of demographic and biological variables. The model was then validated by a comparison of the predicted and observed concentrations in Group 2. A final model was elaborated from the whole population.
Total clearance (CL) was significantly correlated with the serum creatinine (CREA) and the central volume of distribution (V1) was correlated with the body weight (WT). The final model was: CL = 7.14 + (-0.0133 A CREA). V1 = (-16.8) + (0.475 A WT). Q (intercompartmental clearance) = 10.5. V2 = 18.1. The mean pharmacokinetic parameters and their individual variability were: CL (8.24 l/h, 45%), V1 (20.89 l, 60%), V2 (17.95 l, 49%), total volume (38.85 l, 42%) and Q (10.56 l/h, 9%). The bias (1.07 mg/l, IC 95% = -40.46 -+42.60), precision (21.19%) and AFE (1.15) demonstrated the performance of the model.
We have developed and validated a pharmacokinetic model to estimate cefepime concentrations. We showed that serum creatinine and body weight are factors that may influence the standard dose of cefepime. Our model enabled us to predict cefepime concentrations in other patients.
本研究的目的是定义并验证一个群体药代动力学模型,该模型包括患者特征对头孢吡肟药代动力学的影响。
共55例患者被随机分为两组,第1组(34例患者,320个头孢吡肟浓度)用于模型构建,第2组(21例患者,196个头孢吡肟浓度)用于验证。他们接受2g每2次或4g持续静脉滴注的头孢吡肟。使用NONMEM进行群体药代动力学分析,并构建一个基线模型以研究人口统计学和生物学变量的影响。然后通过比较第2组中预测浓度和观察浓度来验证该模型。从总体人群中构建了最终模型。
总清除率(CL)与血清肌酐(CREA)显著相关,中央分布容积(V1)与体重(WT)相关。最终模型为:CL = 7.14 + (-0.0133×CREA),V1 = (-16.8) + (0.475×WT),Q(隔室间清除率) = 10.5,V2 = 18.1。平均药代动力学参数及其个体变异性为:CL(8.24 l/h,45%),V1(20.89 l,60%),V2(17.95 l,49%),总体积(38.85 l,42%)和Q(10.56 l/h,9%)。偏差(1.07 mg/l,95%置信区间 = -40.46~42.60)、精密度(21.19%)和预测误差(1.15)证明了该模型的性能。
我们开发并验证了一个用于估算头孢吡肟浓度的药代动力学模型。我们表明血清肌酐和体重是可能影响头孢吡肟标准剂量的因素。我们的模型使我们能够预测其他患者体内的头孢吡肟浓度。