Respiratory Tract Infections

Abstract

Fluoroquinolone antibiotic agents have demonstrated efficacy in the treatment of respiratory tract infections. This analysis was designed to examine the relationship between drug exposure, as measured by the free-drug area under the concentration-time curve at 24 h (AUC 24 )/MIC ratio, and clinical and microbiological responses in patients with community-acquired respiratory tract infections involving Streptococcus pneumoniae. The study population included 58 adult patients (34 males, 24 females) who were enrolled in either of two phase III, randomized, multicenter, double-blind studies of levofloxacin versus gatifloxacin for the treatment of community-acquired pneumonia or acute exacerbation of chronic bronchitis. Clearance equations from previously published population pharmacokinetic models were used in conjunction with dose and adjusted for protein binding to estimate individual patient free-drug AUC 24 s. In vitro susceptibility was determined in a central laboratory by broth microdilution in accordance with NCCLS guidelines. Pharmacodynamic analyses were performed on data from all evaluable patients with documented S. pneumoniae infection using univariate and multivariable logistic regression; pharmacodynamic breakpoints were estimated using Classification and Regression Tree analysis. A statistically significant (P ‫؍‬ 0.013) relationship between microbiological response and the free-drug AUC 24 /MIC ratio was detected. At a free-drug AUC 24 /MIC ratio of <33.7, the probability of a microbiological response was 64%, and at a free-drug AUC 24 /MIC ratio of >33.7, it was 100% (P < 0.01). These findings may provide a minimum target free-drug AUC 24 /MIC ratio for the treatment of infections involving S. pneumoniae with fluoroquinolone antibiotics and provide a paradigm for the selection of fluoroquinolones to be brought forward from drug discovery into clinical development and dose selection for clinical trials. Further, when target free-drug AUC 24 /MIC ratios are used in conjunction with stochastic modeling techniques, these findings may be used to support susceptibility breakpoints for fluoroquinolone antibiotics and S. pneumoniae.