Multiple predictors of fluoroquinolone antimicrobial effects (AMEs) are not usually examined simultaneously in most studies. To compare the predictive potentials of the area under the concentration-time curve (AUC)-to-MIC ratio (AUC/MIC), the AUC above MIC (AUC_eff), and the time above MIC (T_eff), the kinetics of killing and regrowth of four bacterial strains exposed to monoexponentially decreasing concentrations of ciprofloxacin were studied in an in vitro dynamic model. The MICs of ciprofloxacin for clinical isolates ofStaphylococcus aureus, Escherichia coli11775 (I) and 204 (II), and Pseudomonas aeruginosa were 0.6, 0.013, 0.08, and 0.15 μg/ml, respectively. The simulated values of AUC were designed to provide similar 1,000-fold (S. aureus, E. coli I, and P. aeruginosa) or 2,000-fold (E. coli II) ranges of the AUC/MIC. In each case except for the highest AUC/MIC ratio, the observation periods included complete regrowth in the time-kill curve studies. The AME was expressed by its intensity,I_E (the area between the control growth and time-kill and regrowth curves up to the point where the viable counts of regrowing bacteria are close to the maximum values observed without drug). For most AUC ranges the I_E-AUC curves were fitted by an E_max (maximal effect) model, whereas the effects observed at very high AUCs were greater than those predicted by the model. The AUCs that produced 50% of maximal AME were proportional to the MICs for the strains studied, but maximal AMEs (IE_max) and the extent of sigmoidicity (s) were not related to the MIC. BothT_eff and log AUC/MIC correlated well withI_E (r² = 0.98 in both cases) in a species-independent fashion. UnlikeT_eff or log AUC/MIC, a specific relationship between I_E and log AUC_eff was inherent in each strain. Although each I_E and log AUC_eff plot was fitted by linear regression (r² = 0.97 to 0.99), these plots were not superimposed and therefore are bacterial species dependent. Thus, AUC/MIC and T_eff were better predictors of ciprofloxacin’s AME than AUC_eff. This study suggests that optimal predictors of the AME produced by a given quinolone (intraquinolone predictors) may be established by examining its AMEs against bacteria of different susceptibilities.T_eff was shown previously also to be the best interquinolone predictor, but unlike AUC/MIC, it cannot be used to compare different quinolones. AUC/MIC might be the best predictor of the AME in comparisons of different quinolones.

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