Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; Department of Pharmacokinetics, Toxicology and Targeting, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.
Eur J Pharm Sci. 2017 Nov 15;109S:S78-S82. doi: 10.1016/j.ejps.2017.05.021. Epub 2017 May 13.
In pharmacokinetic modelling, a combined proportional and additive residual error model is often preferred over a proportional or additive residual error model. Different approaches have been proposed, but a comparison between approaches is still lacking.
The theoretical background of the methods is described. Method VAR assumes that the variance of the residual error is the sum of the statistically independent proportional and additive components; this method can be coded in three ways. Method SD assumes that the standard deviation of the residual error is the sum of the proportional and additive components. Using datasets from literature and simulations based on these datasets, the methods are compared using NONMEM.
The different coding of methods VAR yield identical results. Using method SD, the values of the parameters describing residual error are lower than for method VAR, but the values of the structural parameters and their inter-individual variability are hardly affected by the choice of the method.
Both methods are valid approaches in combined proportional and additive residual error modelling, and selection may be based on OFV. When the result of an analysis is used for simulation purposes, it is essential that the simulation tool uses the same method as used during analysis.
在药代动力学建模中，与比例或加性残差模型相比，通常更倾向于使用组合比例和加性残差模型。已经提出了不同的方法，但仍缺乏对这些方法的比较。
描述了方法的理论背景。方法 VAR 假设残差的方差是统计上独立的比例和加性分量之和；这种方法可以用三种方式进行编码。方法 SD 假设残差的标准差是比例和加性分量之和。使用文献中的数据集和基于这些数据集的模拟，使用 NONMEM 对这些方法进行了比较。
方法 VAR 的不同编码产生了相同的结果。使用方法 SD，描述残差的参数值低于方法 VAR，但结构参数及其个体间变异性的值几乎不受方法选择的影响。
这两种方法都是联合比例和加性残差建模的有效方法，可以根据 OFV 进行选择。当分析的结果用于模拟目的时，模拟工具使用与分析期间相同的方法是至关重要的。
