Use of pharmacodynamic parameters to predict efficacy of combination therapy by using fractional inhibitory concentration kinetics

Combination therapy with antimicrobial agents can be used against bacteria that have reduced susceptibilities to single agents. We studied various tobramycin and ceftazidime dosing regimens against four resistant Pseudomonas aeruginosa strains in an in vitro pharmacokinetic model to determine the usability of combination therapy for the treatment of infections due to resistant bacterial strains. For the selection of an optimal dosing regimen it is necessary to determine which pharmacodynamic parameter best predicts efficacy during combination therapy and to find a simple method for susceptibility testing. An easy to-use, previously described E-test method was evaluated as a test for susceptibility to combination therapy. That test resulted in a MICcombi, which is the MIC of, for example, tobramycin in the presence of ceftazidime. By dividing the tobramycin and ceftazidime concentration by the MICcombi, at each time point during the dosing interval, fractional inhibitory concentration (FIC) curves were constructed, and from these curves new pharmacodynamic parameters for combination therapy were calculated (i.e., AUC(combi), Cmax-combi, T>MIC-combi, T->FICi, where AUC(combi), Cmax-combi, T>MIC-combi, and T->FICi are the area under the FICcombi curve, the peak concentration of FICcombi the time that the concentration of the combination is above the MICcombi, and the time above the FIC index, respectively). By stepwise multilinear regression analysis, the pharmacodynamic parameter T->FICi proved to be the best predictor of therapeutic efficacy during combination therapy with tobramycin and ceftazidime (R-2 = 0.6821; P < 0.01). We conclude that for combination therapy with tobramycin and ceftazidime the T->FICi is the parameter best predictive of efficacy and that the E-test for susceptibility testing of combination therapy gives promising results. These new pharmacodynamic parameters for combination therapy promise to provide better insight into the rationale behind combination therapy.