MIC-Based Interspecies Prediction of the Antimicrobial Effects of Ciprofloxacin on Bacteria of Different Susceptibilities in an In Vitro Dynamic Model

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 of Staphylococcus aureus, Escherichia coli 11775 (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 (I(E(max))) and the extent of sigmoidicity (s) were not related to the MIC. Both T(eff) and log AUC/MIC correlated well with I(E) (r(2) = 0.98 in both cases) in a species-independent fashion. Unlike T(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 (r(2) = 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.

现有多数研究通常未同时考察氟喹诺酮类抗菌效应（fluoroquinolone antimicrobial effects, AMEs）的多种预测因子。为对比浓度-时间曲线下面积（area under the concentration-time curve, AUC）与最低抑菌浓度（minimum inhibitory concentration, MIC）之比（AUC/MIC）、高于MIC的AUC（AUC(eff)）以及高于MIC的持续时间（T(eff)）的预测效能，本研究借助体外动态模型，探究了4株细菌暴露于单指数递减浓度环丙沙星后的杀菌与再生长动力学。金黄色葡萄球菌、大肠埃希菌11775（菌株I）、大肠埃希菌204（菌株II）以及铜绿假单胞菌临床分离株对环丙沙星的MIC分别为0.6、0.013、0.08与0.15 μg/ml。设计的AUC模拟值旨在使AUC/MIC范围覆盖1000倍（金黄色葡萄球菌、大肠埃希菌I与铜绿假单胞菌）或2000倍（大肠埃希菌II）。除最高AUC/MIC组外，所有组别观察期均覆盖了时间杀菌曲线研究中的完全再生长过程。AME以效应强度I(E)表示，即对照生长曲线与杀菌-再生长曲线之间，直至再生长细菌的活菌数接近无药条件下观测到的最大值的区域面积。对于多数AUC范围，I(E)-AUC曲线可通过最大效应（E(max)）模型拟合，但极高AUC下观测到的效应高于该模型的预测值。产生50%最大AME的AUC与受试菌株的MIC呈正比，但最大AME（I(E(max))）以及曲线的S形陡峭程度（s）与MIC无关。T(eff)与log(AUC/MIC)均以物种非依赖的方式与I(E)呈良好相关性（两者的决定系数r²均为0.98）。与T(eff)或log(AUC/MIC)不同，I(E)与log(AUC(eff))之间的特定关系因菌株而异。尽管每组I(E)与log(AUC(eff))的散点图均可通过线性回归拟合（r²=0.97~0.99），但这些散点图无法重合，因此存在细菌物种依赖性。综上，AUC/MIC与T(eff)均优于AUC(eff)，可作为环丙沙星AME的更佳预测因子。本研究提示，针对特定喹诺酮类药物的AME最优预测因子（喹诺酮内预测因子），可通过考察其对不同敏感性细菌的AME来确定。此前研究已证实T(eff)是最佳的喹诺酮间预测因子，但与AUC/MIC不同，其无法用于比较不同喹诺酮类药物。在不同喹诺酮类药物的对比中，AUC/MIC或许是AME的最佳预测因子。