A L Gray1, J H Botha, R Miller. 1. Department of Pharmacy, University of Durban-Westville, South Africa. agray@pixie.udw.ac.za
Abstract
OBJECTIVE: To derive a model describing carbamazepine (CBZ) clearance in children, in terms of individual patient characteristics. METHODS: One hundred and eighteen steady-state serum carbamazepine concentration measurements were gathered during normal routine care of 72 compliant outpatients (2.3-16.3 years old). Levels were obtained from patients receiving monotherapy (55%), concomitant valproate (26%), or concomitant inducers (phenytoin, phenobarbitone; 19%). A one-compartment model was used to fit the data with the computer programme Nonlinear Mixed Effects Model (NONMEM). RESULTS: Weight, age and concomitant medication were all important determinants of clearance. The final model for clearance (1.h-1) was: CL = [0.7(WT) 0.4] . M, where WT is patient weight (kg) and M is a scaling factor for concomitant medication, with a value of 1 for patients on CBZ monotherapy or concomitant valproate and 1.4 for those receiving concomitant inducers. For the purposes of this analysis, bioavailability (f) was assumed to be complete, i.e., f is thus included in the term CL. CONCLUSIONS: CBZ clearance decreased with increasing age. As age and weight were correlated, either variable was a satisfactory predictor. The influence of both the inducers and valproate on CBZ clearance was as expected. This model, which describes clearance in terms of patient-specific details, can be used when predicting the maintenance dose required to achieve a target mean steady-state CBZ concentration in children.
OBJECTIVE: To derive a model describing carbamazepine (CBZ) clearance in children, in terms of individual patient characteristics. METHODS: One hundred and eighteen steady-state serum carbamazepine concentration measurements were gathered during normal routine care of 72 compliant outpatients (2.3-16.3 years old). Levels were obtained from patients receiving monotherapy (55%), concomitant valproate (26%), or concomitant inducers (phenytoin, phenobarbitone; 19%). A one-compartment model was used to fit the data with the computer programme Nonlinear Mixed Effects Model (NONMEM). RESULTS: Weight, age and concomitant medication were all important determinants of clearance. The final model for clearance (1.h-1) was: CL = [0.7(WT) 0.4] . M, where WT is patient weight (kg) and M is a scaling factor for concomitant medication, with a value of 1 for patients on CBZ monotherapy or concomitant valproate and 1.4 for those receiving concomitant inducers. For the purposes of this analysis, bioavailability (f) was assumed to be complete, i.e., f is thus included in the term CL. CONCLUSIONS:CBZ clearance decreased with increasing age. As age and weight were correlated, either variable was a satisfactory predictor. The influence of both the inducers and valproate on CBZ clearance was as expected. This model, which describes clearance in terms of patient-specific details, can be used when predicting the maintenance dose required to achieve a target mean steady-state CBZ concentration in children.
Authors: D D Milovanovic; J R Milovanovic; M Radovanovic; I Radosavljevic; S Obradovic; S Jankovic; D Milovanovic; N Djordjevic Journal: Balkan J Med Genet Date: 2016-08-02 Impact factor: 0.519
Authors: Vincent L M Yip; Henry Pertinez; Xiaoli Meng; James L Maggs; Daniel F Carr; B Kevin Park; Anthony G Marson; Munir Pirmohamed Journal: Br J Clin Pharmacol Date: 2020-12-14 Impact factor: 4.335