Department of Anesthesiology, Maastricht University Medical Centre, Maastricht, the Netherlands.
Ther Drug Monit. 2012 Oct;34(5):526-34. doi: 10.1097/FTD.0b013e3182616937.
Observational data sets can be used for population pharmacokinetic (PK) modeling. However, these data sets are generally less precisely recorded than experimental data sets. This article aims to investigate the influence of erroneous records on population PK modeling and individual maximum a posteriori Bayesian (MAPB) estimation.
A total of 1123 patient records of neonates who were administered vancomycin were used for population PK modeling by iterative 2-stage Bayesian (ITSB) analysis. Cut-off values for weighted residuals were tested for exclusion of records from the analysis. A simulation study was performed to assess the influence of erroneous records on population modeling and individual MAPB estimation. Also the cut-off values for weighted residuals were tested in the simulation study.
Errors in registration have limited the influence on outcomes of population PK modeling but can have detrimental effects on individual MAPB estimation. A population PK model created from a data set with many registration errors has little influence on subsequent MAPB estimates for precisely recorded data. A weighted residual value of 2 for concentration measurements has good discriminative power for identification of erroneous records.
ITSB analysis and its individual estimates are hardly affected by most registration errors. Large registration errors can be detected by weighted residuals of concentration.
观察性数据集可用于群体药代动力学（PK）建模。然而，这些数据集通常比实验数据集记录得不够准确。本文旨在研究错误记录对群体 PK 建模和个体最大后验贝叶斯（MAPB）估计的影响。
采用迭代 2 阶段贝叶斯（ITSB）分析，对接受万古霉素治疗的新生儿的 1123 例患者记录进行群体 PK 建模。测试了加权残差的截止值，以排除分析中的记录。进行了一项模拟研究，以评估错误记录对群体建模和个体 MAPB 估计的影响。还在模拟研究中测试了加权残差的截止值。
注册错误对群体 PK 建模结果的影响有限，但对个体 MAPB 估计有不利影响。从存在大量注册错误的数据集中创建的群体 PK 模型对精确记录的数据的后续 MAPB 估计几乎没有影响。浓度测量的加权残差为 2 具有良好的辨别力，可用于识别错误记录。
ITSB 分析及其个体估计受大多数注册错误的影响较小。浓度的加权残差可检测到较大的注册错误。
