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JAC Advance Access originally published online on September 4, 2007
Journal of Antimicrobial Chemotherapy 2007 60(5):1038-1044; doi:10.1093/jac/dkm325
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© The Author 2007. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Pharmacodynamics of ceftazidime and meropenem in cerebrospinal fluid: results of population pharmacokinetic modelling and Monte Carlo simulation

T. P. Lodise1,2,3, R. Nau4, M. Kinzig1, G. L. Drusano3, R. N. Jones5 and F. Sörgel1,*

1 Institute for Biomedical and Pharmaceutical Research, Nürnberg-Heroldsberg, Germany 2 Albany College of Pharmacy, Albany, NY, USA 3 Ordway Research Institute, Albany, NY, USA 4 University of Göttingen, Göttingen, Germany 5 JMI Laboratories, North Liberty, IA, USA

* Corresponding author. Tel: +49-911-518290; Fax: +49-911-5182920; E-mail: ibmp{at}osn.de

Received 26 February 2007; returned 12 May 2007; revised 23 July 2007; accepted 2 August 2007


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Background: Ceftazidime and meropenem are frequently used in the empirical treatment of hospital-acquired cerebrospinal fluid (CSF) infections. Although their dispositions in CSF have been described, the ability of these agents to achieve critical pharmacodynamic targets against the array of nosocomial CSF Gram-negative bacteria encountered in practice has not been reported.

Methods: Serum and CSF pharmacokinetic data were obtained from hospital patients with external ventricular drains and who received ceftazidime or meropenem. Concentration–time profiles in serum and CSF were modelled using a three-compartment model with zero-order infusion and first-order elimination and transfer. The model parameters were identified using population pharmacokinetic analysis [Big Non-Parametric Adaptive Grid (BigNPAG)]. A Monte Carlo simulation (9999 subjects) estimated the probability of target attainment (PTA) for total drug CSF concentrations at 50% and 100% T>MIC for ceftazidime 2 g intravenously every 8 h and meropenem 2 g intravenously every 8 h. The Gram-negative infection isolates of the seven most prevalent Gram-negative bacilli from the Meropenem Yearly Susceptibility Test Information Collection Program were used as a measure of contemporary MIC distribution.

Results: Post-Bayesian measures of bias and precision, observed-predicted plots and R2 values were highly acceptable for both drugs. Although the PTA in CSF was approximately one dilution higher for ceftazidime compared with meropenem at a given MIC value, the cumulative fraction of response (CFR) in CSF against all Gram-negatives was markedly higher for meropenem when compared with ceftazidime secondary to the higher occurrence of lower MIC values for meropenem. Both agents had a low CFR against Pseudomonas aeruginosa.

Conclusions: The pharmacodynamics of meropenem was superior to that of ceftazidime against Gram-negative pathogens in the CSF.

Keywords: population PK , CSF , Gram-negative bacteria


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Nosocomial bacterial meningitis and cerebrospinal fluid (CSF) shunt infections, although uncommon, are major medical concerns and are associated with considerable morbidity and mortality.1 Nosocomial bacterial meningitis and CSF shunt infections are frequently caused by Gram-negative bacteria including Escherichia coli, Pseudomonas aeruginosa and Enterobacter spp.2 To ensure the highest probability of a favourable clinical and microbiological outcome, early diagnosis and prompt delivery of bactericidal antibiotic therapy are vital.3–7 It is essential to select antimicrobials that rapidly penetrate and achieve bactericidal concentrations in the CSF because the immune system is relatively ineffective early in the course of disease. Because antimicrobial therapy is often administered prior to the availability of microbiology and antibiotic susceptibility data, empirical treatment for CSF infections should offer bactericidal activity against the most likely pathogens, including those with only moderate susceptibility.3–7

Two agents that are frequently used in the empirical treatment of nosocomial CSF infections to provide coverage against hospital-acquired Gram-negative bacteria are ceftazidime and meropenem.7 Both are highly active against the majority of Gram-negative bacteria frequently encountered in nosocomial CSF infection,2 and studies have demonstrated that these antibiotics penetrate the CSF reasonably well.8,9 The ability of these agents, however, to achieve the pharmacodynamic targets associated with maximal bacterial killing in the CSF has not been explored. This study characterizes and compares the pharmacodynamics of ceftazidime and meropenem in the CSF. Specifically, population pharmacokinetic modelling and Monte Carlo simulation were used to characterize and compare the probability that ceftazidime and meropenem achieved bactericidal concentrations in the CSF against the array of Gram-negative organisms encountered in clinical practice.


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Patient population

The serum and CSF concentration–time data were obtained from open-labelled studies of hospitalized patients who had undergone external ventriculostomies for non-inflammatory occlusive hydrocephalus and who received either ceftazidime (n = 8) or meropenem (n = 10) to treat extracerebral infections.8,9 These studies did not include patients with inflammatory CNS diseases or major renal impairment (serum creatinine of > 177.0 µmol/L). There were no significant differences in clinical characteristics between groups (Table 1).


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  		Table 1. Clinical characteristics of patients participating in the study8,9

 
Patients received either ceftazidime 3 g (0.5 h infusion) or meropenem 2 g. For both studies, nine simultaneous blood and CSF samples were drawn within 16 h after the first dose: end, 30 min and 1, 2, 4, 7, 10, 13 and 16 h after the termination of the antibiotic infusion. For meropenem, an additional blood sample was measured 10 min after the termination of the antibiotic infusion. As described previously, ceftazidime concentrations in serum and CSF were measured by reversed-phase HPLC with an ultraviolet detection method and meropenem concentrations in serum and CSF were measured by liquid chromatography–mass spectroscopy/mass spectroscopy (LC–MC/MS).8,9

Population pharmacokinetic modelling

All data were analysed in a population pharmacokinetic model using the Big Non-Parametric Adaptive Grid with adaptive {gamma} (BigNPAG) program of Leary, Jelliffe, Schumitzky and Van Guilder. The pharmacokinetic model was parameterized as a three-compartment model with zero-order infusion. Elimination from the central compartment and all inter-compartmental distribution processes were modelled as first-order processes.



Formula

where X(1) is the amount of drug in the central compartment (in milligrams); X(2) the amount of drug in the peripheral compartment (in milligrams); X(3) the amount of drug in the CSF compartment (in milligrams); CL the clearance from the central compartment (L/h); k12, k21, k13 and k31 the first-order inter-compartmental transfer rate constants (in h–1); VC a scalar and represents the volume of the central compartment (in litres) and R(t) the time-delimited zero-order drug input rate (piecewise input function) into the central compartment (in mg/h). The amount of drug in the CSF compartment was scaled to the volume of the CSF compartment (VCSF).

The inverse of the estimated assay variance was used as the first estimate for weighting in the pharmacokinetic modelling. Weighting was accomplished by making the assumption that total observation variance was proportional to assay variance. Assay variance was determined on a between-day basis. The analysis was performed with adaptive gamma, a scalar which multiplies the polynomial described earlier and is optimized with each cycle to produce the best approximation to the homoscedastic assumption.

Upon attaining convergence, Bayesian estimates for each patient were obtained using the ‘population of one’ utility within BigNPAG. The mean, median and modal values were employed as measures of central tendency for the population parameter estimates and were evaluated in the Bayesian analysis. Scatter plots were examined for individual patients and for the population as a whole. Goodness of fit was assessed by regression with an observed–predicted plot, coefficients of determination and log-likelihood values. Predictive performance evaluation was based on weighted mean error and on the bias-adjusted weighted mean-squared error.

Monte Carlo simulation

The mean parameter vector and major diagonal from the population pharmacokinetic model were embedded in Subroutine PRIOR of the ADAPT II package of programs of D'Argenio and Schumitzky.10 The population simulation without process noise option was employed. A Monte Carlo simulation with 9999 subjects was performed for the following regimens: ceftazidime 2 g intravenously every 8 h (0.5 h infusion) and meropenem 2 g intravenously every 8 h (0.5 h infusion). Both normal and log-normal distributions were evaluated and these were discriminated on their ability to recreate the original mean parameter values and corresponding SD from the population analyses. The parameter values from the optimal distributions were employed to simulate steady-state concentrations (24 h after the start of dosing) and to generate serum and CSF concentration–time curves for each dosing regimen. The serum pharmacokinetic data for ceftazidime and meropenem were adjusted for 10% and 2% protein binding, respectively, to reflect unbound or free drug concentrations in the data analysis. The CSF pharmacokinetic data were not adjusted for protein binding, because the protein binding of meropenem and ceftazidime in the CSF is currently unknown. For each regimen examined, the fraction of simulated subjects who achieved 50% and 100% time above the MIC (T>MIC) in the CSF for ascending MIC values was calculated for both agents. For serum, the fraction of simulated subjects who achieved 40% free time above the MIC (40% f T>MIC) and 60% f T>MIC was calculated for meropenem and ceftazidime, respectively. The probability of attaining these pharmacodynamic endpoints was profiled because these indices have been identified as critical pharmacodynamic targets in meningeal and non-meningeal in vitro and animal model studies.4,5,11–18

Organism-specific probability of target attainment analysis

The 1999–2005 Gram-negative infection isolates (surrogate for CSF) of the six most prevalent enteric Gram-negative bacilli (Citrobacter spp., Enterobacter spp., E. coli, Klebsiella spp., Proteus mirabilis and Serratia spp.) and P. aeruginosa from the Meropenem Yearly Susceptibility Test Information Collection (MYSTIC) Program (USA) were used as a measure of MIC distribution and frequency for the organism-specific probability of target attainment (PTA) analysis.19–25 All participating USA MYSTIC Program centres provided the specific quota amount of Gram-negative isolates per centre originating from serious clinical infections to a central monitoring and processing facility (IA, USA).19,24,25 Organism identifications were confirmed at the central laboratory and the MICs for antimicrobials were determined by CLSI (formerly NCCLS) reference techniques.26,27

In the organism-specific analysis, because the fraction of organism collection at each MIC was known, the cumulative fraction of response (CFR) was calculated for each organism under study. This was performed by multiplying the PTA for a specific MIC with the frequency of occurrence for this MIC. This product was calculated for each MIC of interest. The sum of all products was then divided by the overall number of MICs measured and this ratio yielded the overall PTA or CFR for each organism examined.


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Population pharmacokinetic modelling

The mean population parameter estimates (SD) identified by BigNPAG for the pharmacokinetic model are displayed in Table 2. Using the population mean parameter values as the measure of central tendency, the models fit the data well after the Bayesian step. For ceftazidime, the observed-predicted plots for serum and CSF after the Bayesian step showed a best fit regression line of observed = 1.11 x predicted –3.01 (serum) and observed = 1.01 x predicted + 0.00047 (CSF) and the r2 values for serum and CSF were 0.94 and 0.89, respectively. For meropenem, the observed-predicted plots for serum and CSF after the Bayesian step showed a best fit regression line of observed = 0.99 x predicted + 0.35 (serum) and observed = 1.02 x predicted – 0.01 (CSF) and the r2 values for serum and CSF were 0.99 and 0.95, respectively. The mean weighted error (measure of bias) and bias-adjusted weighted mean squared error (measure of precision) in the serum and CSF were highly acceptable for both ceftazidime and meropenem. For ceftazidime, the mean weighted errors for serum and CSF were –0.13 and –0.18, respectively; the bias-adjusted weighted mean squared errors for serum and CSF were 1.65 and 1.01, respectively. For meropenem, the mean weighted errors for serum and CSF were –0.14 and 0.06, respectively; the bias-adjusted weighted mean squared errors for serum and CSF were 1.59 and 0.26, respectively.


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  		Table 2. Population pharmacokinetic mean and SD parameters obtained by BigNPAG

 
For ceftazidime, the mean ± SD AUCCSF:AUCSERUM ratio was 0.07 ± 0.11. The median penetration ratio was 0.04 and the 25th and 75th percentile value ratios were 0.02 and 0.08, respectively. For meropenem, the mean AUCCSF:AUCSERUM was 0.06 ± 0.06. Similar to ceftazidime, the median penetration ratio was 0.04 and the 25th and 75th percentile value ratios were 0.02 and 0.08, respectively.


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  		Table 3. Comparison of MIC distribution between ceftazidime and meropenem for the Gram-negative infection isolates from the MYSTIC Program (USA) 1999–2005

 
The results of target attainment analysis in serum are displayed in Figure 1. For both agents, the probability of achieving a bactericidal effect was < 90% for MICs of ≥2 mg/L. The results of the PTA in CSF are displayed in Figures 2 and 3. The probability of achieving a bactericidal effect in CSF (50% to 100% T>MIC) was higher for ceftazidime than for meropenem for MICs of > 0.125 mg/L. Meropenem only had a > 80% probability of achieving 50% and 100% T>MIC for MICs of ≤0.25 and ≤0.125 mg/L, respectively. In contrast, the probability of achieving 50% and 100% T>MIC in CSF for ceftazidime exceeded 80% for MICs ≤0.5 and ≤0.25 mg/L, respectively.


Figure 1
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  		Figure 1. Probability of attaining a bactericidal effect in serum for ceftazidime 2 g intravenously every 8 h (0.5 h infusion) and meropenem 2 g intravenously every 8 h (0.5 h infusion). Bactericidal effects in serum were 60% free time above the MIC (f T>MIC) for ceftazidime and 40% f T>MIC for meropenem.

 


Figure 2
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  		Figure 2. Probability of achieving 50% T>MIC in CSF for ceftazidime 2 g intravenously every 8 h (0.5 h infusion) and meropenem 2 g intravenously every 8 h (0.5 h infusion).

 


Figure 3
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  		Figure 3. Probability of achieving 100% T>MIC in CSF for ceftazidime 2 g intravenously every 8 h (0.5 h infusion) and meropenem 2 g intravenously every 8 h (0.5 h infusion).

 
Comparison of MIC distribution between ceftazidime and meropenem for the Gram-negative infection isolates from the MYSTIC Program (USA: 1999–2005) is displayed in Table 3. The MIC50 and MIC90 values were lower for meropenem when compared with ceftazidime for all MYSTIC Program Gram-negatives studied. In the organism-specific analysis, meropenem was associated with a higher CFR in both serum and CSF for all Gram-negative organisms studied when compared with ceftazidime (Table 4). For meropenem, the CFR in both serum (40% f T>MIC) and CSF (50% and 100% T>MIC) exceeded 95% for all Gram-negatives except P. aeruginosa. Against P. aeruginosa, the meropenem CFR of 40% f T>MIC in serum was 87.7% and its CFR of achieving 50% and 100% T>MIC in CSF was < 55%. For ceftazidime, the CFR of achieving 60% f T>MIC in serum was >80% for all organisms studied except P. aeruginosa. In CSF, CFR of achieving 50% T>MIC for ceftazidime was < 80% for Citrobacter spp., Enterobacter spp. and P. aeruginosa. Given the low CFR observed against P. aeruginosa, we performed a post hoc analysis and examined the influence of infusing the maximum daily dose (6 g/day) of both ceftazidime and meropenem as continuous infusions. Continuous infusion did not result in any appreciable improvement in the CFR against P. aeruginosa for either antibiotic.


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  		Table 4. Comparison of the CFR (in %) between ceftazidime and meropenem in serum and CSF for nosocomial Gram-negative bacilli from the MYSTIC Program (1999–2005)

 

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Treatment of nosocomial CSF infections is problematic and depends entirely upon attainment of bactericidal antibiotic concentrations at the site of infection.3–7 Two agents frequently used to treat nosocomial CSF infections are ceftazidime and meropenem. Given the importance of having sufficient drug exposure at the site of infection, population pharmacokinetic modelling and Monte Carlo simulation were used to characterize and compare the ability of these agents to achieve critical pharmacodynamic targets (50% and 100% T>MIC) in CSF against the array of Gram-negative pathogens encountered in clinical practice. Population pharmacokinetic modelling and Monte Carlo Simulation have been used by several other investigators to estimate drug penetration and PTA at the site of infection and have become a widely accepted methodology for such studies.28–31 To the best of our knowledge, this is the first study to specifically compare the pharmacodynamic profiles of maximal recommended ceftazidime and meropenem dosing regimens in the CSF.

In serum, ceftazidime and meropenem had a similar probability of achieving a bactericidal effect for a given MIC value. In CSF, ceftazidime and meropenem had a similar probability of achieving a bactericidal effect for a given MIC value. Ceftazidime demonstrated a higher probability of achieving a bactericidal effect in the CSF than meropenem for a given MIC value: the PTA was consistently about one-dilution higher for ceftazidime when compared with meropenem. However, meropenem had a more robust CFR against all Gram-negative organisms compared with ceftazidime. The stark differences between ceftazidime and meropenem in the CSF CFR against Gram-negatives were a function of variations in the MIC distributions; there was a higher occurrence of lower MIC results for meropenem when compared with ceftazidime for each Gram-negative organism examined. As one might expect, the most notable difference observed was among the AmpC-producing Gram-negative organisms. Both agents performed poorly against P. aeruginosa and the risk of a higher dose should be weighed when treating P. aeruginosa CSF infections, especially when the MIC of the infecting P. aeruginosa exceeds 0.5 mg/L for ceftazidime and 0.25 mg/L for meropenem. These findings emphasize the importance of linking PTA results with relevant microbiological surveillance studies and institution-specific susceptibility rates.

Several factors must be considered when interpreting these results. First, only a limited number of patients were included in the analysis; a greater number of patients would enable one to better estimate the dispersion surrounding PK parameter estimates and thus provide more precise PTA estimates. It, however, should be noted that the variation surrounding the PK estimates observed in this study was reasonable and enabled us to characterize the full dispersion of time–concentration profiles one would expect to see if the drug was given to the entire population. Secondly, this study was performed in patients with minimal meningeal inflammation; such a condition would most likely facilitate greater drug penetration and subsequently result in higher CSF PTA than observed here.4,6,11,32,33 Although it is anticipated that the rate and extent of penetration of beta-lactams into the CSF would be increased by inflammation, it would only improve the PTA by one to two log2 dilutions and thus would not significantly alter the observed results. It is also important to note that most nosocomial CSF infections are associated with minimal-to-mild disturbances in the blood–CSF barrier.4,6,11,32,33 Thus, the probabilities of target attainment calculated in this study should be readily applicable to clinical practice. Thirdly, VCSF should not be viewed as the physiological volume in CSF. Rather, the anticipated amount of drug in the CSF compartment was scaled to the volume of the CSF compartment VCSF. Specifically, VCSF is an output from differential equations and is a scalar term that explains the concentrations observed in the CSF relative to the amount of drug given. This is why VCSF is so high; only a minimal amount of total drug administered penetrated the CSF and the higher VCSF is used to reflect this.

Finally, the precise pharmacodynamic target for bactericidal activity in the CSF is still a subject of debate, but we believe that the data strongly support a CSF target of 50% to 100% T>MIC. Although the initial target was believed to be a peak/MBC ratio ≥10,34–39 a recent animal model study suggested that the pharmacodynamic target is 100% T>MBC and this target is consistent with other sites of infection.16 Furthermore, several experimental meningitis animal model studies suggest that 50% T>MBC is required for bactericidal activity.11 Although these studies recommend T>MBC, there was no major distinction between MIC and MBC in these studies,11,16,34–39 and the MBC was identical or within one dilution of MIC.34–39 In studies in which the MIC was not the same as the MBC, the MIC values were all ≤0.25 mg/L.16

In summary, we used population pharmacokinetic modelling and Monte Carlo simulation to characterize the pharmacodynamic profiles of ceftazidime and meropenem in serum and CSF against the most common Gram-negative bacilli observed in clinical practice. Although the PTA was approximately one-dilution higher for ceftazidime when compared with meropenem at a given MIC, the CFR in CSF against all Gram-negatives was markedly higher for meropenem when compared with ceftazidime secondary to its lower MIC distribution. Specifically, there was a higher occurrence of lower MIC results for meropenem compared with ceftazidime for each Gram-negative organism examined. Both agents had a low CFR against P. aeruginosa and the risk versus benefit of higher doses should be considered when treating CNS infections caused by this pathogen.


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No funding was received for this study.


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None to declare.


   Acknowledgements
 
This article has greatly benefited from the thoughtful editing of Allison Krug, MPH.


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