Twenty-four-hour area under the concentration-time curve/MIC ratio as a generic predictor of fluoroquinolone antimicrobial effect by using three strains of Pseudomonas aeruginosa and an in vitro pharmacodynamic model

Several investigators have suggested that the 24-h area under the concentration-time curve (AUC)/MIC ratio (AUCTMIC₂₄ or AUIC₂₄) can be used to make comparisons of antimicrobial activity between fluoroquinolone antibiotics. Limited data exist regarding the generic predictive ability of AUC/MIC₂₄ for the antimicrobial effects of fluoroquinolones. The purposes of the present investigation were to determine if the AUC/MIC₂₄ can be used as a generic outcome predictor of fluoroquinolone antibacterial activity and to determine if a similar AUC/MIC₂₄ breakpoint can be established for different fluoroquinolones. Using an in vitro pharmacodynamic model, 29 duplicate concentration time-kill curve experiments simulated AUC/MIC₂₄s ranging from 52 to 508 SIT^-1 · h (inverse serum inhibitory titer integrated over time) with ciprofloxacin or ofloxacin against three strains of Pseudomonas aeruginosa. Each 24-h experiment was performed in cation-supplemented Mueller-Hinton broth with a starting inoculum of 10⁶ CFU/ml. At timed intervals cation-supplemented Mueller-Hinton broth samples were collected for CFU and fluoroquinolone concentration determinations. Transformation of bacterial counts into the cumulative bacterial effect parameter of the 24-h area under the effect curve (AUEC₂₄) was performed for each concentration time-kill curve. Multivariate regression analysis was used to compare pharmacodynamic predictors (AUC/MIC₂₄, 24-h AUC, peak concentration [C_max] to MIC ratios [C_max:MIC], etc.) with In AUEC₂₄. To identify threshold breakpoint AUC/MIC₂₄s, AUEC₂₄s were stratified by the magnitude of AUC/MIC₂₄ into subgroups, which were analyzed for differences in antibacterial effect. The Kruskal-Wallis test and subsequent Tukey's multiple comparison test were used to determine which AUC/MIC subgroups were significantly different. Multiple regression analysis revealed that only AUC/MIC₂₄ (r² = 0.65) and MIC (r² = 0.03) were significantly correlated with antibacterial effect. At similar AUC/MIC₂₄s, yet different MICs, C_maxs, or elimination half-lives, the AUEC₂₄s were similar for both fluoroquinolones. The relationship between AUC/MIC₂₄ and in AUEC₂₄ was best described by a sigmoidal maximal antimicrobial effect (E_max) model (r² = 0.72; E_max = 9.1; AUc/MIC₅₀ = 119 SIT^-1 · h; S = 2.01 [S is an exponent that reflects the degree of sigmoidicity]). Ciprofloxacin-bacteria AUC/MIC₂₄ values of <100 SIT^-1 · h were significantly different (P <0.05) from the AUC/MIC₂₄ values of >100 SIT^-1 · h An ofloxacin AUC/MIC₂₄ of >100 SIT^-1 · h and an AUC/MIC₂₄ of <100 SIT^-1 · h exhibited a trend toward a significant difference (P > 0.05 but < 0.1). The inverse relationship between drug exposure and MIC increase postexposure was described by a sigmoidal fixed E_max model (AUC/MIC₂₄, r² = 0.40; AUC/MIC₅₀ = 95 SIT^-1 · h; S = 1.97; C_max:MIC, r² = 0.41; C_max:MIC₅₀ = 7.3; S = 2.01). These data suggest that AUC/MIC₂₄ may be the most descriptive measurement of fluoroquinolone antimicrobial activity against P. aeruginosa, that ofloxacin and ciprofloxacin have similar AUC/ MIC₂₄ threshold breakpoints at approximately 100 SIT^-1 · h, that the concentration-dependent selection of resistant organisms may parallel the threshold breakpoint of the antimicrobial effect, and that AUC/MIC₂₄ generically describes the antibacterial effects of different fluoroquinolones.