Anderson Brian J, Allegaert Karel, Holford Nicholas H G
Department of Anaesthesiology, University of Auckland, Auckland, New Zealand.
Eur J Pediatr. 2006 Dec;165(12):819-29. doi: 10.1007/s00431-006-0189-x. Epub 2006 Jun 29.
Population modelling using mixed effects models provides a means to study variability in paediatric drug responses among individuals representative of those in whom the drug will be used clinically.
Explanatory covariates explain the predictable part of the between-individual variability. Growth and development are two major aspects of children not seen in adults. These aspects can be investigated by using size and age as covariates. Problems attributable to co-linearity can be approached by using size as the first covariate. Size standardisation is achieved using allometric scaling, a mechanistic approach that has a strong theoretical and empirical basis. Age is used to describe the maturation of clearance. The quantitative models (linear, exponential, first-order, variable slope sigmoidal) used to describe this maturation process vary depending on the span of the ages under investigation. Measures of response are not always straightforward and can be more difficult to quantify in children.
Covariate investigation in children is improving the understanding of developmental aspects of drug disposition and effects in the paediatric population, ultimately leading to more effective use of medications.
使用混合效应模型进行人群建模提供了一种手段,用于研究在临床上使用该药物的代表性个体中儿科药物反应的变异性。
解释性协变量解释个体间变异性的可预测部分。生长和发育是儿童特有的两个主要方面,而在成人中不存在。可以通过将身高和年龄作为协变量来研究这些方面。由于共线性导致的问题可以通过将身高作为第一个协变量来解决。使用异速生长标度法实现身高标准化,这是一种具有强大理论和实证基础的机制方法。年龄用于描述清除率的成熟度。用于描述这种成熟过程的定量模型(线性、指数、一阶、可变斜率S形)因所研究年龄范围的不同而有所差异。反应的测量并不总是简单直接的,在儿童中可能更难以量化。
对儿童协变量的研究正在加深对儿科人群药物处置和效应发育方面的理解,最终导致药物的更有效使用。