24-HOUR AREA UNDER THE CONCENTRATION-TIME CURVE MIC RATIO AS A GENERIC PREDICTOR OF FLUOROQUINOLONE ANTIMICROBIAL EFFECT BY USING 3 STRAINSOF PSEUDOMONAS-AERUGINOSA AND AN IN-VITRO PHARMACODYNAMIC MODEL

Several investigators have suggested that the 24-h area under the conc entration-time curve (AUC)/MIC ratio (AUC/MIC(24) or AUIC(24)) can be used to make comparisons of antimicrobial activity between fluoroquino lone antibiotics, Limited data exist regarding the generic predictive ability of AUC/MIC(24) for the antimicrobial effects of fluoroquinolon es. The purposes of the present investigation were to determine if the AUC/MIC(24) can be used as a generic outcome predictor of fluoroquino lone 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 ciproflo xacin or ofloxacin against three strains of Pseudomonas aeruginosa. Ea ch 24-h experiment was performed in cation-supplemented Muller-Hinton broth with a starting inoculum of 10(6) CFU/ml. At timed intervals cat ion-supplemented Mueller-Hinton broth samples were collected for CFU a nd fluoroquinolone concentration determinations, Transformation of bac terial counts into the cumulative bacterial effect parameter of the 24 -h area under the effect curve (AUEC(24)) was performed for each conce ntration time-kill curve, Multivariate regression analysis was used to compare pharmacodynamic predictors (AUC/MIC(24), 24-h AUG, peak conce ntration [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 f or differences in antibacterial effect, The Kruskal-Wallis test and su bsequent Tukey's multiple comparison test were used to determine which AUC/MIC subgroups were significantly different, Multiple regression a nalysis revealed that only AUC/MIC(24) (r(2) = 0.65) and MIC (r(2) = 0 .03) were significantly correlated with antibacterial effect, At simil ar AUC/MIC(24)s, yet different MICs, C(max)s, or elimination half-live s, the AUEC(24)s were similar for both fluoroquinolones. The relations hip between AUC/MIC(24) and In AUEC(24) was best described by a sigmoi dal 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 refl ects the degree of sigmoidicity]). Ciprofloxacin-bacteria AUC/MIC(24) values of <100 SIT-1. h were significantly different (P <0.05) from th e AUC/MIC(24) values of >100 SIT-1. h. An ofloxacin AUC/MIC(24) of >10 0 SIT-1. h and an AUC/MIC(24) of <100 SIT-1. h exhibited a trend towar d a significant difference (P > 0.05 but < 0.1). The inverse relations hip 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(5 0) = 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 descri ptive 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 concent ration-dependent selection of resistant organisms may parallel the thr eshold breakpoint of the antimicrobial effect, and that AUC/MIC(24) ge nerically describes the antibacterial effects of different fluoroquino lones.