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Application of fluoroquinolone pharmacodynamics
D H Wright1, G H Brown, M L Peterson
1College of Pharmacy, University of Minnesota, Minneapolis, MN and Clinical Pharmacy, Regions Hospital, 640 Jackson Street, St Paul, MN 55101, USA.
The Journal of Antimicrobial Chemotherapy
|November 4, 2000
Summary
Optimizing quinolone antibiotic dosing requires understanding pharmacodynamics. Specific ratios like AUC/MIC are crucial for predicting treatment success and preventing resistance, but vary by bacterial pathogen.
Area of Science:
- Pharmacology
- Infectious Diseases
- Microbiology
Background:
- Pharmacodynamics (PD) links drug concentration to antimicrobial effect, aiding rational dosing.
- Objective prescribing decisions can be improved by identifying meaningful PD outcome parameters, moving beyond static in vitro Minimum Inhibitory Concentration (MIC) data.
- Quinolone antibiotics exhibit concentration-dependent killing, with Peak/MIC and Area Under the Curve (AUC)/MIC ratios as potential predictors of clinical outcomes and resistance.
Purpose of the Study:
- To evaluate the clinical application of pharmacodynamic (PD) parameters for quinolone antibiotics.
- To determine the most accurate PD predictors for clinical and microbiological success and to limit bacterial resistance development.
- To investigate pathogen-specific variations in PD parameters for quinolone therapy.
Main Methods:
- Review of existing literature on quinolone pharmacodynamics and clinical outcomes.
- Analysis of proposed pharmacodynamic outcome parameters, including Peak/MIC and AUC/MIC ratios.
- Comparison of PD parameter efficacy across different bacterial pathogens, including Gram-negative bacteria and Streptococcus pneumoniae.
Main Results:
- Established Peak/MIC ratios (>10) and AUC/MIC ratios (100-125) are suggested for Gram-negative bacteria to predict success and limit resistance.
- Recent data indicate that these ratios may not be suitable for Streptococcus pneumoniae, with an AUC/MIC ratio of <40 appearing more predictive.
- Significant variability exists in PD calculations and outcome parameters, highlighting quinolone- and pathogen-specific effects.
Conclusions:
- Pharmacodynamic parameters are essential for optimizing quinolone dosing regimens.
- Current PD predictors for quinolones, primarily derived from Gram-negative studies, require re-evaluation for other pathogens like Streptococcus pneumoniae.
- Further prospective clinical research is necessary to define optimal PD outcome predictors for Gram-positive bacteria, anaerobes, and atypical respiratory pathogens.
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