Format

Send to

Choose Destination
J Antimicrob Chemother. 2013 Apr;68(4):900-6. doi: 10.1093/jac/dks468. Epub 2012 Nov 28.

Optimal exposures of ceftazidime predict the probability of microbiological and clinical outcome in the treatment of nosocomial pneumonia.

Author information

1
Department of Medical Microbiology, Radboud University Nijmegen Medical Centre, PO Box 9101, 6500 HB, Nijmegen, The Netherlands. muller.research@gmail.com

Abstract

OBJECTIVES:

The %fT>MIC of ceftazidime has been shown to correlate with microbiological outcome of Gram-negative bacteria (GNB) in preclinical studies. However, clinical data are still lacking. We explored the relationship of ceftazidime exposure and outcome in patients with nosocomial pneumonia using data from a recent randomized, double-blind Phase 3 clinical trial.

PATIENTS AND METHODS:

Pharmacokinetic (PK) and demographic data from three clinical trials were used to construct a population PK model using non-linear mixed-effects modelling. Individual concentration-time curves and PK/pharmacodynamic indices were determined for individual patients. The MICs used in the analyses were the highest MICs for any GNB cultured at baseline or end of therapy.

RESULTS:

A two-compartment model best fit the data, with creatinine clearance as covariate on clearance and age on the central compartment. Classification and regression tree analysis showed a breakpoint value of 44.9% (P<0.0001) for GNB in 154 patients. The Emax model showed a good fit (R(2) =0.93). The benefit of adequate treatment increased from an eradication rate of 0.4848 at %fT>MIC of 0% to 0.9971 at 100%. The EC50 was 46.8% and the EC90 was 95.5% for %fT>MIC. Exposure correlated significantly with both microbiological and clinical outcome at test-of-cure.

CONCLUSIONS:

We conclude that exposures to ceftazidime predict microbiological as well as clinical outcome, and the %fT>MIC required to result in a likely favourable outcome is >45% of the dosing interval. This value is similar to that observed in animal models and underscores the principle that adequate dosing can be predicted and is beneficial to patient care.

PMID:
23190766
DOI:
10.1093/jac/dks468
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center