The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models

In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70kg or 1kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CLpop) parameter estimates. The influence of normalization weight (70, 1kg or median weight) on the precision of the CLpop estimate, expressed as relative standard error (RSE), was illustrated using data from a pharmacokinetic study in neonates with a median weight of 2.7kg. In addition, a simulation study was performed to show the impact of normalization to 70kg in pharmacokinetic studies with paediatric or obese patients. The RSE of the CLpop parameter estimate in the neonatal dataset was lowest with normalization to median weight (8.1%), compared with normalization to 1kg (10.5%) or 70kg (48.8%). Typical clearance (CL) predictions were independent of the normalization weight used. Simulations showed that the increase in RSE of the CLpop estimate with 70kg normalization was highest in studies with a narrow weight range and a geometric mean weight away from 70kg. When, instead of normalizing with median weight, a weight outside the observed range is used, the RSE of the CLpop estimate will be inflated, and should therefore not be used for model selection. Instead, established mathematical principles can be used to calculate the RSE of the typical CL (CLTV) at a relevant weight to evaluate the precision of CL predictions.