Fernández de Gatta M M, Tamayo M, García M J, Amador D, Rey F, Gutiérrez J R, Domínguez-Gil Hurlé A
Department of Pharmacy, Faculty of Pharmacy, University of Salamanca, Spain.
Ther Drug Monit. 1989 Nov;11(6):637-41. doi: 10.1097/00007691-198911000-00004.
The aim of the present study was to characterize the kinetic behavior of imipramine (IMI) and desipramine in enuretic children and to evaluate the performance of different methods for dosage prediction based on individual and/or population data. The study was carried out in 135 enuretic children (93 boys) ranging in age between 5 and 13 years undergoing treatment with IMI in variable single doses (25-75 mg/day) administered at night. Sampling time was one-half the dosage interval at steady state. The number of data available for each patient varied (1-4) and was essentially limited by clinical criteria. Pharmacokinetic calculations were performed using a simple proportional relationship (method 1) and a multiple nonlinear regression program (MULTI 2 BAYES) with two different options: using the ordinary least-squares method (method 2) and the least-squares method based on the Bayesian algorithm (method 3). The results obtained point to a coefficient of variation for the level/dose ratio of the drug (58%) that is significantly lower than that of the metabolite (101.4%). The forecasting capacity of method 1 is deficient both regarding accuracy [mean prediction error (MPE) = -5.48 +/- 69.15] and precision (root mean squared error = 46.42 +/- 51.39). The standard deviation of the MPE (69) makes the method unacceptable from the clinical point of view. The more information that is available concerning the serum levels, the greater are the accuracy and precision of methods (2 and 3). With the Bayesian method, less information on drug serum levels is needed to achieve clinically acceptable predictions.
本研究的目的是描述遗尿症儿童体内丙咪嗪(IMI)和地昔帕明的动力学行为,并评估基于个体和/或群体数据的不同剂量预测方法的性能。该研究在135名年龄在5至13岁的遗尿症儿童(93名男孩)中进行,这些儿童接受夜间服用不同单剂量(25 - 75毫克/天)的IMI治疗。采样时间为稳态时给药间隔的一半。每个患者可获得的数据数量各不相同(1 - 4个),且主要受临床标准限制。使用简单比例关系(方法1)和具有两种不同选项的多元非线性回归程序(MULTI 2 BAYES)进行药代动力学计算:使用普通最小二乘法(方法2)和基于贝叶斯算法的最小二乘法(方法3)。所得结果表明,药物的血药浓度/剂量比变异系数(58%)显著低于代谢物的变异系数(101.4%)。方法1的预测能力在准确性[平均预测误差(MPE)= -5.48 +/- 69.15]和精密度(均方根误差 = 46.42 +/- 51.39)方面均存在不足。MPE的标准差(69)使得该方法从临床角度来看不可接受。关于血清水平可获得的信息越多,方法2和方法3的准确性和精密度就越高。使用贝叶斯方法时,实现临床可接受的预测所需的药物血清水平信息较少。