Population Pharmacokinetics of PEGylated Asparaginase in Children with Acute Lymphoblastic Leukemia: Treatment Phase Dependency and Predictivity in Case of Missing Data

Würthwein G, Lanvers-Kaminsky C, Siebel C, Gerß J, Möricke A, Zimmermann M, Stary J, Smisek P, Schrappe M, Rizzari C, Zucchetti M, Hempel G, Wicha SG, Boos J

Abstract

BACKGROUND AND OBJECTIVES The pharmacokinetics of polyethylene glycol-conjugated asparaginase (PEG-ASNase) are characterized by an increase in elimination over time, a marked increase in ASNase activity levels from induction to reinduction, and high inter- and intraindividual variability. A population pharmacokinetic (PopPK) model is required to estimate individual dose intensity, despite gaps in monitoring compliance. METHODS In the AIEOP-BFM ALL 2009 trial, two PEG-ASNase administrations (2500~U/m2 intravenously) during induction (14-day interval) and one administration during reinduction were administered in children with acute lymphoblastic leukemia. ASNase activity levels were monitored weekly. A PopPK model was used for covariate modeling and external validation. The predictivity of the model in case of missing data was tested for observations, as well as for the derived parameters of the area under the concentration time curve (AUC0-∞) and time above different thresholds. RESULTS Compared to the first administration in induction (1374 patients, 6069 samples), the initial clearance and volume of distribution decreased by 11.0{\%} and 15.9{\%}, respectively, during the second administration during induction and by 41.2{\%} and 28.4{\%} during reinduction. Furthermore, the initial clearance linearly increased for children aged >~8 years and was 7.1{\%} lower for females. The model was successfully externally validated (1253 patients, 5523 samples). In case of missing data, >~52{\%} of the predictions for observations and >~82{\%} for derived parameters were within ±~20{\%} of the nominal value. CONCLUSION A PopPK model that describes the complex pharmacokinetics of PEG-ASNase was successfully externally validated. AUC0-∞ or time above different thresholds, which are parameters describing dose intensity, can be estimated with high predictivity, despite missing data. ( www.clinicaltrials.gov , NCT01117441, first submitted date: May 3, 2010).