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 (AUC/MIC(24) or AUIC(24)) can be used to make comparisons of antimicrobial activity between fluoroquinolone antibiotics, Limited data exist regarding the generic predictive ability of AUC/MIC(24) for the antimicrobial effects of fluoroquinolones. The purposes of the present investigation were to determine if the AUC/MIC(24) can be used as a generic outcome predictor of fluoroquinolone antibacterial activity and to determine if a similar AUC/MIC(24) breakpoint can be established for different fluoroquinolones, Using an in vitro pharmacodynamic model, 29 duplicate concentration time-kill curve experiments simulated AUC/MIC(24)s 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 Muller-Hinton broth with a starting inoculum of 10(6) 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 (AUEC(24)) was performed for each concentration time-kill curve, Multivariate regression analysis was used to compare pharmacodynamic predictors (AUC/MIC(24), 24-h AUG, peak concentration [C-max] to MIC ratios [C-max:MIC], etc.) with In AUEC(24). To identify threshold breakpoint AUC/MIC(24)s, AUEC(24)s were stratified by the magnitude of AUC/MIC(24) 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/MIC(24) (r(2) = 0.65) and MIC (r(2) = 0.03) were significantly correlated with antibacterial effect, At similar AUC/MIC(24)s, yet different MICs, C(max)s, or elimination half-lives, the AUEC(24)s were similar for both fluoroquinolones. The relationship between AUC/MIC(24) and In AUEC(24) was best described by a sigmoidal maximal antimicrobial effect (E(max)) model (r(2) = 0.72; E(max) = 9.1; AUC/MIC(50) = 119 SIT-1. h; S = 2.01 [S is an exponent that reflects the degree of sigmoidicity]). Ciprofloxacin-bacteria AUC/MIC(24) values of <100 SIT-1. h were significantly different (P <0.05) from the AUC/MIC(24) values of >100 SIT-1. h. An ofloxacin AUC/MIC(24) of >100 SIT-1. h and an AUC/MIC(24) 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/MIC(24), r(2) = 0.40; AUC/MIC(50) = 95 SIT-1. h; S = 1.97; C-max:MIC, r(2) = 0.41; C-max:MIC(50) = 7.3; S = 2.01), These data suggest that AUC/MIC,, may be the most descriptive measurement of fluoroquinolone antimicrobial activity against P. aeruginosa, that ofloxacin and ciprofloxacin have similar AUC/MIC(24) 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/MIC(24) generically describes the antibacterial effects of different fluoroquinolones.