S. Dhaese (1), J. De Waele (1) and P. Colin (2,3)
(1) Ghent University Hospital, Department of Critical Care Medicine, Ghent, Belgium. (2) University of Groningen, University Medical Center Groningen, Department of Anesthesiology, Groningen, The Netherlands. (3) Ghent University, Laboratory of Medical Biochemistry and Clinical Analysis, Ghent, Belgium
Objectives:Evidence on the linearity of piperacillin clearance at therapeutic plasma concentrations in patients in conflicting [1–5]. Non-linearity in piperacillin clearance impacts the optimal dosing regimen and this is particularly relevant given the recent introduction of continuous as opposed to intermittent infusion of beta-lactam antibiotics in several ICU’s worldwide[3,6].
The aim of this study was to revisit the evidence on the (non-)linearity of piperacillin clearance using clinical trial simulations. For this, the type I error rate and power for detecting non-linear piperacillin CL of published clinical trials on piperacillin PKs was evaluated. The difference between non-parametric (NPAG) vs. parametric parameter estimation in type I error rate and power was also investigated. Based on the same principles, an optimal experimental trial design was developed to inform a clinical-trial on non-linearity of piperacillin clearance.
Methods:Piperacillin PK profiles were simulated according to the design of different published studies on piperacillin PK in patients (i.e. same number of patients, number of observations, mode of administration, doses, sampling times, etc.). For these simulations, the PopPK model by Landersdorfer et al[1],on piperacillin PKs in healthy volunteers, served as the true model. Cohorts of patients with non-linear piperacillin PKs were simulated according to the final parameter estimates by Landersdorfer (H1). In parallel, cohorts with linear PKs were simulated by fixing the Vmaxestimate to zero (H0). Two nested models, a two-compartment linear model and a two-compartment model with parallel linear / non-linear elimination, were fitted to the simulated datasets. The likelihood ratio testat the 5% level of significance was used to compare both models.
The type I error rate and power were approximated by the frequency of significant LRT in the simulated datasets without non-linear (H0) and with non-linear piperacillin CL (H1), respectively. In addition, a type I error calibration was implemented and the statistical power was calculated with this calibrated chi-square value in order to obtain the power of a specific study design corresponding to a type I error rate ≤ 5%[7].
The accuracy of Kmand Vmaxestimates was assessed by the percentage of times the estimated values for both Kmand Vmaxfell within a two-fold range (i.e. -50%; +100%) of the original mean Kmand Vmaxestimations reported by Landersdorfer, et al[1].
Parameter estimation was performed using the NPAG estimation routine as implemented in Pmetrics (Version 1.5.2; Laboratory of Applied Pharmacokinetics, Los Angeles, CA, USA) and the FOCE-I algorithm in NONMEM (Version 7.3; GloboMax LLC, Hanover, MD, USA).
Results:Six published piperacillin PopPK models were selected from the literature of which three[4,5,8]described linear clearance of piperacillin while the other three[3,9,10]described non-linear clearance of piperacillin. The number of patients per study ranged between 8 and 50 and the number of observations per patient ranged between 6 and 27.
The type I error rate was between 1.4% and 26% with NPAG and between 1.9% and 75% with FOCE-I. The calibrated power of the study designs was between 5.1% and 97.1% with NPAG and between 0.2% and 47.9% with FOCE-I. None of the NPAG estimates for Kmand Vmaxfell within a two-fold range of the true Kmand Vmaxvalues used for simulation, not even in the study with high calibrated power[8]. For FOCE-I, accuracy was also low except for the study with high calibrated power [8]where 16.4% of estimates were within the 2-fold range. Our proposed study design (based on 10 patients) resulted in a type I error rate of 3.0%, a power of 100% with 47% of parameter estimates within 2-fold of the values used for simulation. When NPAG was used instead of FOCE-I, the type I error rate increased to 12% without significantly affecting power. Remarkably, both for Vmax and Km parameter estimates were always higher than 2-fold the value used for simulation.
Conclusions: Published studies evaluating the non-linear pharmacokinetics of piperacillin were poorly powered and likely resulted in in-accurate estimates for Vmaxand Km. An optimal experimental design to study piperacillin non-linearity is proposed. Further work is necessary to study the influence of the estimation algorithm on the statistical inference in the context of the differentiation between linear and non-linear PKs in clinical trials with patients.
References:
[1] Landersdorfer CB, Bulitta JB, Kirkpatrick CM, Kinzig M, Holzgrabe U, Drusano GL, et al. Population pharmacokinetics of piperacillin at two dose levels: influence of nonlinear pharmacokinetics on the pharmacodynamic profile. Antimicrob Agents Chemother 2012;56:5715–23.
[2] Bulitta JBB, Kinzig M, Jakob V, Holzgrabe U, Sörgel F, Holford NH. Nonlinear pharmacokinetics of piperacillin in healthy volunteers–implications for optimal dosage regimens. Br J Clin Pharmacol 2010;70:682–93.
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[6] Tabah A, De Waele J, Lipman J, Zahar JR, Cotta MO, Barton G, et al. The ADMIN-ICU survey: a survey on antimicrobial dosing and monitoring in ICUs. J Antimicrob Chemother 2015;70:2671–7.
[7] Hilgers R-DD, Bogdan M, Burman C-FF, Dette H, Karlsson M, König F, et al. Lessons learned from IDeAl – 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials. Orphanet J Rare Dis 2018;13:77.
[8] Roberts JA, Kirkpatrick CM, Roberts MS, Dalley AJ, Lipman J. First-dose and steady-state population pharmacokinetics and pharmacodynamics of piperacillin by continuous or intermittent dosing in critically ill patients with sepsis. Int J Antimicrob Agents 2010;35:156–63.
[9] Butterfield JM, Lodise TP, Beegle S, Rosen J, Farkas J, Pai MP. Pharmacokinetics and pharmacodynamics of extended-infusion piperacillin/tazobactam in adult patients with cystic fibrosis-related acute pulmonary exacerbations. J Antimicrob Chemother 2014;69:176–9.
[10] Felton TW, Hope WW, Lomaestro BM, Butterfield JM, Kwa AL, Drusano GL, et al. Population pharmacokinetics of extended-infusion piperacillin-tazobactam in hospitalized patients with nosocomial infections. Antimicrob Agents Chemother 2012;56:4087–94.
Reference: PAGE 28 (2019) Abstr 8894 [www.page-meeting.org/?abstract=8894]
Poster: Study Design