S. Corvaisier (1), N. Bleyzac (2), P. Maire (1,3).
(1) ADCAPT, Pharmacy department, A. Charial hospital, Francheville (France); (2) Pharmacy department, Debrousse hospital, Lyon (France); (3) Laboratory of Applied Pharmacokinetics, USC School of Medicine, Los Angeles, California (USA).
Objectives: Influence of quality data collected for TDM (administered doses, AD; infusion duration, ID; blood sampling time, BST) has already been studied on individual PK parameters. The aim of this work is to evaluate this influence on PK population parameters and especially on the proposed a priori dosage regimens.
Methods: In clinical conditions, carefully recording and checking data could minimise important errors in data collection. Fifty amikacin patient files collected in this condition are considered as few mistaken, and constituted Reference Population (RP). Amikacin volume of distribution related to the weight (Vs, l/kg) and renal elimination rate constant (kel, h-1) have been estimated (NPEM2) with a non-renal elimination rate fixed at 0.00693 h-1. Systematic errors in BST (+/–18, 12, 6 min) have been introduced one after the other in all files, for only T1 (new populations: ST11 to ST16), for only T2 (ST21 to ST26), and both T1/T2 (ST31 to ST36). Systematic errors have been also introduced in ID (+/–10, +/–5, +30, +60 min: ID01 to ID06), and in AD (-20, +/–10, +/–5%: DA01 to DA06). Thus, BST, ID, and AD have been separately modified in all files with random errors (3 replicates, respectively STR1 to STR3, IDR1 to IDR3, and ADR1 to ADR3 populations). Finally, all of these random errors have been introduced (populations ALR1 to ALR3). New parameter values have been estimated for all of these modified populations. A priori amikacin dosage regimen for 20 news patients have been proposed with its.
Results-Discussion: Vs and kel values are respectively 0.34±0.07 l/kg and 3,9±1,1.10-3 min.ml-1.h-1 for RP. The more the systematic error is important, the more the influence on PK parameter values increase, and consequently, the more the influence on proposed dosage regimens (-8.9 to 4.0%) and dose intervals (-1.8 to 3.8%) is important. With random errors, influence on proposed a priori dosage regimens is less important (AD: 1 to 3%; ID: 0.3 to 3.0%). It could be explained by a possible compensation of random errors. With all types randomised errors introduction, each type tended to compensate each other. Indeed, in comparison to dosage regimen proposed using RP parameters, absolute errors on a priori proposed dosage regimen are above 7.5% for AD and above 5.0% for ID.
Conclusion: NPEM produces robust parameter value estimations despite random error introduction. Even if, patient files are mistaken due to erroneous collected data, proposed doses are not really different than those obtained with RP.
Reference: PAGE 8 () Abstr 144 [www.page-meeting.org/?abstract=144]
Poster: poster