Contributors to between-individual variability of amikacin clearance in neonates
Abstract number: P1247
Allegaert K., De smet K., Scheers I., Adams E., Cossey V., Anderson B.J.
Objectives: We recently documented that size (49%), renal function (14%) and postmenstrual age (PMA 18%) are the major contributors to vancomycin clearance variability in neonates, leaving only 18% of variability unexplained. A variable slope sigmoidal model fitted best to describe the relationship between vancomycin clearance and PMA (1). A similar exercise in a large dataset of amikacin concentrations in neonates was undertaken to test applicability of the current model to others drugs, like amikacin, cleared by renal elimination.
Methods: Population pharmacokinetics were estimated (NONMEM) in a cohort of 715 neonates (PMA 2443 weeks; weight 0.3854.780 kg) and were based on 1 862 amikacin time-concentration points. Covariate analysis included weight, PMA, postnatal age (PNA), creatinaemia, 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.
Results: The population estimate for volume of distribution (V) was 32.1 L/70kg and 1.21 L/h/70kg for clearance (CL). CL increased from 0.84 L/h/70kg at 28 weeks PMA to 1.23 and 1.56 L/h/70kg by 34 and 40 weeks PMA. Overall 92% of the variability of CL was predictable. Size explained 66%, PMA 17% and renal function 9%. The use of a variable slope sigmoidal model to describe the relationship between clearance and PMA predicted an adult amikacin clearance of 3.87 L/h/70kg.
Conclusions: The explained variability of clearance and the relative contribution of the different contributors (size, PMA and renal function) is a similar magnitude with the earlier reported observations on vancomycin clearance and a variable slope sigmoidal model fitted best to predict adult amikacin clearance. These findings strongly suggest that the current model likely describes the underlying maturation of renal drug clearance. The development and subsequent validation of such models should further improve the predictability of drug clearance for drugs cleared by a similar route.
Anderson B et al. Br J Clin Pharmacol 2007;63(1):7584
|Session name:||18th European Congress of Clinical Microbiology and Infectious Diseases|
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