The selection of bacterial resistance was examined in relationship to antibiotic pharmacokinetics (PK) and organism MICs in the patients from four nosocomial lower respiratory tract infection clinical trials. The evaluable database included 107 acutely ill patients, 128 pathogens, and five antimicrobial regimens. Antimicrobial pharmacokinetics were characterized by using serum concentrations, and culture and sensitivity tests were performed daily on tracheal aspirates to examine resistance. Pharmacodynamic (PD) models were developed to identify factors associated with the probability of developing bacterial resistance. Overall, in 32 of 128 (25%) initially susceptible cases resistance developed during therapy. An initial univariate screen and a classification and regression tree analysis identified the ratio of the area under the concentration-time curve from 0 to 24 h to the MIC (AUC0–24/MIC) as a significant predictor of the development of resistance (P < 0.001). The final PK/PD model, a variant of the Hill equation, demonstrated that the probability of developing resistance during therapy increased significantly when antimicrobial exposure was at an AUC0–24/MIC ratio of less than 100. This relationship was observed across all treatments and within all organism groupings, with the exception of β-lactamase-producing gram-negative organisms (consistent with type I β-lactamase producers) treated with β-lactam monotherapy. Combination therapy resulted in much lower rates of resistance than monotherapy, probably because all of the combination regimens examined had an AUC0–24/MIC ratio in excess of 100. In summary, the selection of antimicrobial resistance appears to be strongly associated with suboptimal antimicrobial exposure, defined as an AUC0–24/MIC ratio of less than 100.

Pharmacokinetic/pharmacodynamic surrogate relationships have been used to describe the antibacterial activity of various classes of antimicrobial agents. Studies that have evaluated these relationships were reviewed to determine which of these surrogate markers were further dependent on antimicrobial class. The fluoroquinolone and aminoglycoside agents exhibit concentration-dependent killing. Studies have demonstrated that peak serum concentration: minimum inhibitory concentration (MIC) and area under the serum concentration-time curve (AUC): MIC ratios are important predictors of outcome for these antimicrobial agents. Area under the inhibitory concentration-time curve (AUIC24) [i.e. AUC24/MIC] is a useful parameter for describing efficacy for these agents, while an adequate peak concentration: MIC ratio seems necessary to prevent selection of resistant organisms. For beta-lactam antibiotics, the duration of time that the serum concentration exceeds the MIC (T > MIC) was the significant pharmacokinetic/pharmacodynamic surrogate in cases where the bacterial inoculum was low, or where very sensitive organisms were tested. However, in studies using more resistant organisms or larger inoculum sizes there is some concentration-dependence to the observed effect. Studies using reasonable dosage intervals have demonstrated covariance between T > MIC and AUC/MIC ratio for beta-lactam antibiotics. Since glycopeptide antibiotics display relatively slow but concentration-independent killing, and are cell wall active agents similar to beta-lactams, it has been presumed that T > MIC is the important pharmacokinetic surrogate related to efficacy for these agents. Some studies have shown that a concentration multiple of the MIC may be necessary for successful outcome with vancomycin. AUIC24 may prove to be an important pharmacokinetic surrogate if both time and concentration are indeed important parameters. To select an appropriate antimicrobial agent, the clinician must consider many patient-specific as well as organism-specific factors. Utilisation of known pharmacokinetic/pharmacodynamic surrogate relationships should help to optimise treatment outcome.

We extensively studied the epidemiology and time course of endemic methicillin-resistant Staphylococcus aureus (MRSA) in the Millard Fillmore Hospital, a 600-bed teaching hospital in Buffalo. The changeover from methicillin-susceptible S. aureus to MRSA begins on the first hospital day, when patients are given cefazolin as presurgical prophylaxis. Under selective antibiotic pressure, colonizing flora change within 24 to 48 hours. For patients remaining hospitalized, subsequent courses of third-generation cephalosporins further select and amplify the colonizing MRSA population. Therefore, managing antibiotic selective pressure might be essential. Other strategies include attention to dosing, so that serum concentrations of drug exceed the minimum inhibitory concentration, and antibiotic cycling. Although there are some promising new antibiotics on the horizon, it is necessary to deal with many resistance patterns by using the combined strategies of infection control and antibiotic management.