Vancomycin pharmacokinetics in preterm neonates and the prediction of adult clearance

Abstract

What is already known about this subject: *Effects of size, renal function, age (postnatal age, gestational age and postmenstrual age) as predictors of vancomycin clearance in premature neonates are established, but the relative contribution of each component remains poorly quantified, largely because these variables are closely correlated. *We have quantified the covariates contributing to vancomycin clearance population parameter variability in order to establish the major covariates required for dosing predictions. Size, standardized using allometric models, was the primary covariate used in our analysis.

What this study adds: *Size explained 49.8%, postmenstrual age 18.2% and renal function 14.1% of clearance variability. *Descriptors of the relationship between age and clearance in premature neonates vary. *The use of a variable slope sigmoidal model to describe the relationship between clearance and postmenstrual age predicted an adult clearance of 3.79 l h(-1) 70 kg(-1) (95% confidence interval 2.76, 4.98) from premature neonatal data.

Aim: To identify and quantify factors describing the variability of vancomycin clearance in premature neonates.

Methods: Population pharmacokinetics were estimated (NONMEM) in 214 neonates [postmenstrual age (PMA) 30.4 weeks, range 24-34 weeks; postnatal age 11.9 days, range 1-27 days; weight 1.30 kg, range 0.42-2.6 kg] using therapeutic drug monitoring data. Covariate analysis included weight, PMA, serum creatinine, use of inotropes or ibuprofen, positive blood culture and respiratory support. A one-compartment linear disposition model with zero order input and first-order elimination was used to describe the data (604 observations).

Results: The population estimate for volume of distribution (V) was 39 l 70 kg(-1) (coefficient of variation 19.4%). Clearance (CL) increased from 0.897 l h(-1) 70 kg(-1) at 24 weeks PMA to 2.02 l h(-1) 70 kg(-1) by 34 weeks PMA. The between-subject variability for CL was 18.6% and the between-occasion variability was 12.2%. The use of ibuprofen reduced clearance, but this effect was attributable to reduced renal function. Overall, 82% of the variability of CL was predictable. Size explained 49.8%, PMA 18.2% and renal function 14.1%. The use of a variable slope sigmoidal model to describe the relationship between clearance and PMA predicted an adult clearance of 3.79 l h(-1) 70 kg(-1) (95% confidence interval 2.76, 4.98).

Conclusions: Size, renal function and PMA are the major contributors to clearance variability in premature neonates. The small (18%) unexplained variability in clearance suggests target concentration intervention is unnecessary if size, age and renal function are used to predict the dose. Extrapolation to an adult clearance from neonatal data is possible using allometric size models and a function describing clearance maturation.

Figure 1

(a) The four models used to investigate the relationship between age and clearance maturation are similar in the age range of the population studied. (b) The first-order and linear models intercept the abscissa before 0. This seems unlikely as organogenesis is occurring during the second trimester of pregnancy. The exponential and variable slope sigmoidal models (Hill equation) allow for gradual clearance maturation which starts early in fetal life. (c) The first-order and variable slope sigmoidal models predict a ‘mature’ vancomycin clearance. The first-order model shows that 80% of the ‘mature’ value at 62 weeks postmenstrual age (PMA), whereas the variable slope sigmoidal model is at 90% of the ‘mature’ value at 62 weeks PMA. Exponential (.––.); first order (......); Hill (––); liner (——)

Figure 2

Individual predicted vancomycin clearances (CL), standardized to a 70-kg person, from the NONMEM post hoc step, are plotted against postmenstrual age. The solid line represents the linear relation between clearance and age

Figure 3

Creatinine concentrations in those neonates greater than 2 days postnatal age are plotted against postmenstrual age. Creatinine concentration is a function of both production and renal clearance

Figure 4

Individual predicted vancomycin clearances (CL) from the linear postmenstrual age (PMA) model, standardized to a 70-kg person, from the NONMEM post hoc step, and corrected for age, creatinine clearance and ventilation, are plotted against PMA. The horizontal line represents clearance in an average neonate (30 weeks PMA)

Figure 5

Individual Bayesian concentration predictions from the linear postmenstrual age model based on values of the parameters for the specific individual are compared with those observed. The line x = y is the line of identity