Division of Pharmacology, Leiden/Amsterdam Center for Drug Research, Leiden, The Netherlands.
Pharm Res. 2011 Apr;28(4):797-811. doi: 10.1007/s11095-010-0333-1. Epub 2010 Dec 14.
A framework for the evaluation of paediatric population models is proposed and applied to two different paediatric population pharmacokinetic models for morphine. One covariate model was based on a systematic covariate analysis, the other on fixed allometric scaling principles.
The six evaluation criteria in the framework were 1) number of parameters and condition number, 2) numerical diagnostics, 3) prediction-based diagnostics, 4) η-shrinkage, 5) simulation-based diagnostics, 6) diagnostics of individual and population parameter estimates versus covariates, including measurements of bias and precision of the population values compared to the observed individual values. The framework entails both an internal and external model evaluation procedure.
The application of the framework to the two models resulted in the detection of overparameterization and misleading diagnostics based on individual predictions caused by high shrinkage. The diagnostic of individual and population parameter estimates versus covariates proved to be highly informative in assessing obtained covariate relationships. Based on the framework, the systematic covariate model proved to be superior over the fixed allometric model in terms of predictive performance.
The proposed framework is suitable for the evaluation of paediatric (covariate) models and should be applied to corroborate the descriptive and predictive properties of these models.
提出了一种用于评估儿科群体模型的框架，并将其应用于两种不同的吗啡儿科群体药代动力学模型。一个协变量模型基于系统协变量分析，另一个基于固定的体表面积比例缩放原则。
该框架中的六个评估标准为：1）参数数量和条件数；2）数值诊断；3）基于预测的诊断；4）η 收缩；5）基于模拟的诊断；6）个体和群体参数估计与协变量的诊断，包括与观察到的个体值相比，对群体值的偏倚和精度的测量。该框架需要内部和外部模型评估过程。
将该框架应用于这两个模型，结果发现由于高收缩导致参数过度拟合和基于个体预测的误导性诊断。个体和群体参数估计与协变量的诊断在评估获得的协变量关系方面非常有信息量。基于该框架，系统协变量模型在预测性能方面优于固定体表面积模型。
所提出的框架适用于儿科（协变量）模型的评估，应应用于证实这些模型的描述性和预测性。
