Pharmacodynamic considerations in the treatment of moderate to severe pseudomonal infections with cefepime

Paul G. Ambrosea,*, Robert C. Owens, Jrb, Michael J. Garveyc and Ronald N. Jonesd

a Cognigen Corporation, 395 Youngs Road, Buffalo, NY 14221-5831; b Maine Medical Center & University of Vermont, College of Medicine, 22 Bramhall Street, Portland, ME 04102-3175; c F. F. Thompson Hospital, 350 Parish Street, Canandiagua, NY 14424; d The Jones Group/JMI Laboratories, 345 Beaver Kreek Centre, Suite A, North Liberty, IA 52317, USA


    Abstract
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
Pseudomonas aeruginosa is one of the more common and clinically difficult-to-treat causes of hospital-acquired infections. Cefepime is a broad-spectrum cephalosporin with potent in vitro activity against Gram-positive cocci, enteric Gram-negative bacilli and Pseudomonas aeruginosa. Cephalosporins exhibit time-dependent bactericidal activity and lack prolonged post-antibiotic effects against Enterobacteriaceae and P. aeruginosa. In non-clinical models of infection against Enterobacteriaceae and P. aeruginosa, antibacterial effects are observed when serum levels are above the MIC for as little as 35% of the dosing interval and are maximized when levels exceed the MIC for 60–70% of the dosing interval. Based on the MIC distribution for P. aeruginosa and pharmacokinetic data obtained from patients with serious bacterial infections (including pneumonia and sepsis), time above MIC targets can be met in infected patients following 2 g doses of cefepime administered every 12 h. An understanding of the integration of target patient population pharmacokinetics and the MIC distribution is crucial for selecting effective dosage regimens, especially in the setting of empirical therapy. Moreover, sufficient clinical outcome data in infected patients exist and support these pharmacodynamic conclusions.


    Introduction
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
Serious infections, such as nosocomial pneumonia, that involve Pseudomonas aeruginosa are associated with significant mortality and place a substantial burden on the healthcare system.1 Mortality in clinical studies ranges from 39% to as high as 96% and has been shown to be dependent upon the severity of the underlying illness, invasiveness of infection, and appropriateness of the selected treatment.2–4 Inadequate treatment selection often leads to clinical failure and may contribute to the development of resistance.4,5 Complicating the selection of treatment regimens is the fact that the susceptibility data generated by clinical laboratories are usually qualitative and actual MIC values are not commonly determined.

Similarly, there is great uncertainty as to the extent of patient drug exposure following standard, fixed doses of an antimicrobial agent. Seldom, if ever, is the drug exposure from an actual patient represented by the idealized drug concentration–time curve published in the manufacturer's labelling. For instance, it has long been known that drug exposures for certain antimicrobial agents are significantly lower in cystic fibrosis patients than in normal healthy volunteers, whose data are represented in manufacturer's labelling. Conversely, drug exposure is generally greater in elderly patients, often dramatically so, than in healthy volunteers.

It is essential that clinicians be aware of regional and national susceptibility data for clinically important pathogens, such as P. aeruginosa, and consider this information along with patient population pharmacokinetic data when selecting empirical therapy. This review will focus on the pharmacodynamics of cefepime against P. aeruginosa. That is, the integration of the microbiological activity data of cefepime against P. aeruginosa with actual pharmacokinetic data obtained from infected patients. Finally, we will review clinical outcome data from patients with serious pseudomonal infection treated with cefepime.


    Population pharmacokinetic data
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
Two of the most important parameters that affect the efficacy of an antimicrobial agent are the MIC of the infecting pathogen to the therapeutic agent and the magnitude of the exposure of the organism to the drug. Most pharmacokinetic data available to the clinician are derived from a limited number of normal healthy volunteers who are usually aged 18–39 years.6–10 Unfortunately, these pharmacokinetic data often do not reflect the drug exposures observed in an ailing population of patients. This is especially true of anti-infective agents used to treat serious infections, such as hospital-acquired pneumonia. A patient with hospital-acquired pneumonia is, typically, over 60 years of age, has impaired renal function and has multiple co-morbid conditions, such as chronic obstructive pulmonary disease, cardiovascular disease, cancer, alcoholism, liver disease, malnutrition, diabetes mellitus and/or hypertension.11–13 Several of these factors are known to alter significantly the antimicrobial pharmacokinetic profiles.

For example, the pharmacokinetics of cefepime were evaluated in patients with various degrees of renal impairment, in whom cefepime was administered intravenously as a 1 g dose over 30 min to five healthy volunteers and 20 subjects with various degrees of renal dysfunction.6 Because the excretion of cefepime is almost exclusively via glomerular filtration, it was not surprising to find that cefepime clearance decreased and serum half-life increased as a result of increased renal insufficiency. In those patients with normal renal function, cefepime clearance was 131 mL/min and the serum half-life was 2.3 h. In contrast, in those patients with creatinine clearance of 61–90 mL/min, cefepime clearance and half-life were 76 mL/min and 3.3 h, respectively. In patients with creatinine clearance of 31–60 mL/min, cefepime clearance and half-life were 61 mL/min and 4.9 h. In patients with creatinine clearance of 11–30 mL/min, cefepime clearance and half-life were 26 mL/min and 10.5 h. In patients with creatinine clearance of <10 mL/min, cefepime clearance and half-life were 19 mL/min and 13.5 h.

The pharmacokinetic profiles of cefepime administered intravenously in various populations9,14–16 are summarized in Table 1Go. As would be expected, the pharmacokinetic profile in young healthy volunteers differs markedly with all patient groups. This is especially true for patients with sepsis syndrome, in whom the serum half-life increases from 2.26 to 3.42 h.


View this table:
[in this window]
[in a new window]
 
Table 1. Pharmacokinetic parameters of cefepime in various populations9,14–16
 

    In vitro susceptibility
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
Typically, susceptibility data reported in the literature consist of a range of MIC values, MIC50, MIC90, and percent susceptible at a breakpoint for each genus and drug studied. Although this information has proven useful and has affected drug use and policy, it provides only a limited sense as to the extent of variability in the data. In other words, one can compare the MIC50 or MIC90 value of one antimicrobial agent with that of another antimicrobial agent for a given microorganism, but this provides a limited description of the actual distribution of the MIC values.

Figure 1Go shows the range of observed MIC values for 1530 clinical isolates of Pseudomonas aeruginosa of cefepime and ceftazidime. All strains were collected from hospitalized patients from January 1999 to December 2000 as part of the SENTRY Antimicrobial Surveillance Programme. If only the range of MIC values and the MIC50 were compared, it would appear that there were no significant differences in the in vitro activity of these two cephalosporins. However, nearly three-fold more strains had MIC values >16 mg/L for ceftazidime compared with cefepime. This observation was not evident from the comparison of ranges of MIC values nor MIC50 or MIC90 values between agents, and has been validated in other independent studies worldwide.18



View larger version (9K):
[in this window]
[in a new window]
 
Figure 1. P. aeruginosa MIC frequency distributions of cefepime ({blacksquare}) and ceftazidime ({square}) (n = 1530) (R. N. Jones, unpublished data).

 

    Use of pharmacodynamics in the prediction of outcome
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
In vitro measures of potency, such as MICs, are not reliable to predict clinical efficacy because they do not take into consideration the pharmacokinetic properties of antimicrobial agents. Moreover, susceptibility breakpoints are based primarily on distribution patterns of microorganisms, which denote subpopulations of organisms that possess some resistance factor. Resistance factors that divide a population into ‘susceptible' and ‘resistant' subpopulations often have no clinical relevance.19

The discipline of pharmacodynamics attempts to integrate MIC and pharmacokinetic data into clinically meaningful relationships because each parameter alone provides incomplete information for predicting therapeutic responses. Antibacterial activity in vitro and in vivo can be described as a function of drug concentration and the duration of time that the pathogen is exposed to the drug. Usually, the antibacterial effects in non-clinical models of infection and patients can be linked with one of three pharmacodynamic parameters: (1) duration of time the drug concentration remains above the MIC of the agent against the pathogen (t > MIC); (2) ratio of peak drug concentration to the MIC for the pathogen; (3) ratio of the 24 h area under the curve of the agent to the MIC for the pathogen.20–27

The antibacterial effects of ß-lactams, such as cefepime, are ‘time-dependent'. Once drug concentrations exceed a critical value (usually two to four times the MIC), the rate of bacterial killing is maximized; that is, further increases in drug concentration do not result in proportional increases in the rate or extent of bacterial killing.28,29 In vivo effects of cephalosporins in neutropenic murine models of infection against Staphylococcus aureus are observed when free-drug concentrations exceed the MIC (t > MIC) for as little as 25% of the dosing interval.30–32 Conversely, for Enterobacteriaceae and P. aeruginosa, antibacterial effects are observed when the t > MIC exceeds as little as 35% of the dosing interval and are maximized when the t > MIC exceeds 60–70% of the dosing interval (Table 2Go).30


View this table:
[in this window]
[in a new window]
 
Table 2. Time above the MIC required for static effect after 24 h of therapy with four cephalosporins30
 
Clinical verification of pharmacodynamic parameters established in non-clinical models of infection has been difficult for a number of reasons. First, clinical trials have not involved the collection of blood for drug concentration assay, or estimation of drug exposure; therefore, the extent of drug exposure in many patient populations remains largely unknown. Population pharmacokinetics has recently become more common in clinical trials and pharmacodynamic parameters have been verified for a number of compounds.20,25,26,33,34 This is a significant advance in characterizing dose–response relationships in humans. Secondly, the isolation of organisms with higher MIC values is generally rare in clinical trials; therefore, a statistically meaningful exposure–response evaluation is often impossible. This remains a challenge, and a significant limitation in clinical trials. In current double-blind, randomized controlled trials required by the United States Food and Drug Administration (US-FDA), the pathogen must be susceptible to both study agents. Therefore, pathogens with higher MIC values are seldom included for either of the studied antimicrobial regimens.35

Although the optimal t > MIC in the clinical setting is not known, it is likely to vary with the drug, pathogen and immunocompetence of the patient. In immunocompetent patients, a static effect t > MIC may be all that is required for efficacy, whereas a greater t > MIC may be required for efficacy in immunocompromised patients. It should be realized that for many antimicrobial agents and MICs at the margins of susceptibility, static pharmacodynamic parameters are achieved and may be sufficient for efficacy in less severely ill patient populations.


    Integration of in vitro and pharmacokinetic data
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
A commonly employed pharmacodynamic analysis for a time-dependent antibiotic consists of a mean drug concentration–time curve upon which an MIC value (usually an MIC90) is superimposed. Subsequently, calculations are made and t > MIC is determined. The problem with this ‘single-point' analytical approach is that the considerable variability in pharmacokinetic and MIC data are not considered. Ideally, pharmacodynamic calculations should include all possible drug exposures following standard doses administered to patients and all MIC values that are likely to be encountered in the clinic. This will provide more information as to whether a drug will be effective for a patient infected with a particular pathogen. Stochastic modelling, such as Monte Carlo simulation, is a better way to integrate pharmacokinetic and microbiological data.36–38

In order to estimate the probability of obtaining t > MIC of 40–70% for every dosing interval, an estimate of the variability in drug exposure in the target patient population is needed. This probability density function (PDF) may be estimated in a number of ways: (1) from mean vector parameters and covariance matrix from a population pharmacokinetic analysis; (2) from actual estimates of pharmacokinetic parameters from a large number of patients enrolled in clinical trials; or (3) from mean vector parameters from a number of patients in conjunction an appropriate structural model.36,39

Next, information on the susceptibility (MIC) of the target organism is required. One can use institutionally specific data, regional data, or incorporate information on the distribution of MICs using the probability mass function (PMF) from a large susceptibility surveillance programme, such as the SENTRY Antimicrobial Surveillance Programme.17 Finally, the aforementioned susceptibility PMF and pharmacokinetic PDFs are integrated via Monte Carlo simulation using Crystal Ball, ADAPT II or any one of the other available computer software programs.

Figure 2Go shows the results of a 1000 patient Monte Carlo Simulation based on the MIC PMF shown in Figure 1Go and multiple-dose, steady-state, pharmacokinetic PDFs from 20 adult patients treated with cefepime for serious bacterial infections, including pneumonia and sepsis. Of the 20 patients, 11 were male and nine female; their ages were between 26 and 98 years (70.4 ± 14.7 years); creatinine clearance 81.5 ± 38.2 mL/min; serum half-life 3.51 ± 1.3 h; and volume of distribution 22.55 ± 13.9 L. Pharmacodynamic analyses were made in conjunction with the following structural model:

where Vss is the volume of distribution at steady state, t1/2 is the serum elimination half-life and fu is the fraction of unbound drug. The model assumed that the fraction of unbound drug was 84%. It is reasonable to use pharmacokinetic data from this patient population in pharmacodynamic analyses because cefepime has US-FDA clinical indications and, more importantly, it is used extensively to treat these infections.



View larger version (21K):
[in this window]
[in a new window]
 
Figure 2. Results of a 1000 patient Monte Carlo simulation on PDFs derived from patient pharmacokinetic data (n = 20) and P. aeruginosa MIC PMF (n = 1530) from the SENTRY Surveillance Programme. The light bars represent the number of simulated patients with t > MIC of <70%. The dark bars represent the number of simulated patients with t > MIC of >=70%. The probability of attaining a t > MIC of >=70% is 79.4%.

 
Based upon the above pharmacokinetic PDFs and the entire MIC PMF for P. aeruginosa, there is a 93.8, 89.7, 84.4 and 79.4% probability of obtaining 40, 50, 60 and 70% t > MIC, respectively (Figure 2Go). In addition, 1000 patient simulations were related to specific MIC values (Figure 3Go). At a fixed MIC of 8 mg/L, there is a 96.9, 91.3, 83.2 and 74.0% probability of obtaining t > MIC of 40, 50, 60 and 70%, respectively.



View larger version (12K):
[in this window]
[in a new window]
 
Figure 3. Results of a 1000-patient Monte Carlo simulation based on PDFs derived from patient pharmacokinetic data (n = 20) and fixed MIC values. The probability of obtaining 40% t > MIC at an MIC of 8 mg/L is c. 97%, and 74% when the t > MIC target is 70%. {diamondsuit}, 40% t > MIC; {blacksquare}, 50% t > MIC; {blacktriangleup}, 60% t > MIC; x, 70% t > MIC.

 

    Clinical outcome data
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
Although pharmacodynamic modelling data are often very useful in clinical or formulary decision-making, supporting clinical outcome data are crucial. The most useful type of information may be obtained from non-interventional, naturalistic studies. The strength of this type of study design is derived by providing information on how an agent is actually used in clinical practice rather than in the strict confines of controlled clinical trials. The information gained from this approach can be crucial for decision-making, especially when the fiscal constraints of the modern healthcare system are considered.

Ambrose et al.11 compared the cost-effectiveness of cefepime and ceftazidime in intensive care unit patients with hospital-acquired pneumonia. The efficacy, safety and cost-effectiveness of each agent was evaluated in a prospective, non-interventional, investigator-blinded study involving 100 patients. Hospital-acquired pneumonia was defined using the Centers for Disease Control and Prevention criteria for nosocomial infection.38 The study evaluated both clinical and microbiological outcome. ‘Cure' was defined as the complete resolution of all signs and symptoms of pneumonia and improvement or lack of progression on chest radiograph. Demonstrable significant improvement of signs and symptoms of pneumonia, but with evidence of remaining pulmonary infection was classified as ‘improved'. ‘Failure' included any of the following: persistence or progression of signs and symptoms of pneumonia, development of new pulmonary or extrapulmonary clinical findings consistent with active infection, or death resulting from infection. Patients were classified as ‘improved' if they were improving but died as a result of a non-infectious process, or if they were withdrawn because of an adverse event. If a patient was not improving or if death was thought to be related to infection, the patient was classified as a ‘failure'. Clinical efficacy was determined by an infectious disease physician who was blinded to the study drug.

In the cefepime group, 30 of 50 (60%) patients received medication twice daily, and 20 of 50 (40%) received medication once daily, in accordance with the manufacturer's dosage recommendations for corresponding renal function. Additionally, 48 of the 50 (96%) patients received a 1 g dose, and two of 50 (4%) received a 2 g dose. Clinical success rates were 60% and 78% for patients treated with ceftazidime and cefepime, respectively (P = 0.05). Microbiological eradication rates were 55% for ceftazidime and 77% for cefepime (P = 0.04). In the subset of patients with documented pseudomonal pneumonia, the organism was eradicated in 14 of 20 (70%) cefepime-treated patients and seven of 14 (50%) ceftazidime-treated patients.

In a similar study, Grant et al.40 studied cefepime-treated patients with culture-documented hospital-acquired pneumonia involving P. aeruginosa. This multicentre, observational study consisted of 58 non-neutropenic patients treated with cefepime either every 12 or 24 h, depending on renal function. A positive clinical response (i.e. cured or improved) occurred in 46 of 58 (79%) and failure occurred in 12 of 58 (21%) patients. Of the 46 patients with a positive clinical response, only one (2.2%) had microbiologically documented persistence. Moreover, microbiologically documented persistence was observed in only three of the 12 patients classified as clinical failures.

The patient demographics of the aforementioned studies were comparable to those from prospective, randomized clinical trials (Table 3Go). These studies included a large proportion of seriously ill patients, as evidenced by the high mean APACHE II scores and by the percentage of patients with APACHE II scores > 20. Moreover, the percentages of patients requiring mechanical ventilation in these trials were comparable to observations from randomized clinical trials. The clinical and microbiological outcomes observed in these studies compare favourably with those of prospective, randomized clinical trials involving a variety of compounds, such as imipenem/cilastatin, ceftriaxone/tobramycin, ceftazidime, cefpirome and ciprofloxacin.12,41–44


View this table:
[in this window]
[in a new window]
 
Table 3. Patient demographics
 

    Combination therapy
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
The beneficial effects of combination therapy directed toward Gram-negative bacteria have been evaluated in several studies.45–49 Although combination therapy has not been noted to provide a benefit in terms of specific endpoints (i.e. reduced resistance potential and improved survival for most Gram-negative bacteria studied), P. aeruginosa appears to be an exception. Although not all studies are in agreement, some investigators have demonstrated a reduction in the emergence of Pseudomonas resistance during therapy when combination therapy was employed.4 In contrast, others were unable to demonstrate differences between monotherapy and combination therapy for systemic or invasive Pseudomonas infections.48,50–52

There are several combination therapy options available for the treatment of P. aeruginosa. Antipseudomonal ß-lactams (e.g. cefepime, ceftazidime, piperacillin, imipenem) in combination with an aminoglycoside (e.g. gentamicin, tobramycin, amikacin) have demonstrated the greatest frequency of enhanced in vitro synergy and have been well studied in humans.53–56 Antipseudomonal ß-lactams in combination with ciprofloxacin have infrequently demonstrated synergy against Gram-negative pathogens, but this may be of little consequence because they penetrate into tissues (including the lung) to a greater degree than aminoglycosides.57–59

Some investigators have attempted to correlate the impact of synergy determined in vitro between certain antibiotic combinations with outcome and/or the development of resistance, but have showed variable results.45 Nonetheless, this issue is one of great complexity, and the fact is that multiple variables exist that impact on the development of resistance and outcome, and they are difficult to control. These include the ability and accuracy of sampling at the site of infection, quantification of inoculum concentration, immunocompetence of the host, methods of synergy testing used (e.g. time–kill versus chequerboard) and new insight into pharmacodynamics and dose optimization (e.g. once-daily or infrequent dosing of aminoglycosides, continuous infusion of ß-lactams).

In view of these data, the emphasis should be for clinicians to select antimicrobial agents (alone or in combination) that demonstrate the greatest potency against the anticipated pathogens and reach sites of infection to the largest degree. In addition, pharmacodynamically sound dosing strategies should be employed to maximize drug exposure in relation to the MIC for the suspected pathogens.


    Summary
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
The pharmacodynamic profile of cefepime predicts acceptable levels of success against P. aeruginosa over a wide range of MIC values as well as over a variety of possible drug exposures, as observed in clinical practice. The success of cefepime dosed every 12 h in the treatment of pseudomonal lung infections is also supported by a number of published clinical trials as described above. The partner compound used in combination with cefepime is also particularly important in pseudomonal pulmonary infections, be it an aminoglycoside (dosed optimally on an infrequent, high-dose basis) or an antipseudomonal fluoroquinolone. If these agents provide either additive or synergic benefits in terms of bacterial killing, they may provide reduced opportunities for the development of resistance, and may improve patient survival. P. aeruginosa is the cause of several other types of serious extrapulmonary infections, including urinary tract infections, skin and skin structure infections, intra-abdominal infections, bacteraemias and infections in the febrile neutropenic patient. Clinical trial data involving cefepime (dosed every 12 h) for the treatment of these infections are also congruent with the pharmacodynamic modelling results in our study.60–66 Cefepime represents a potent antipseudomonal treatment option for empirical treatment or pathogen-directed therapy of moderate to severe pulmonary infections.


    Notes
 
* Corresponding author. Tel: +1-716-633-3463 ext 302; Fax: +1-716-633-7404; E-mail: paul.ambrose{at}cognigen.com Back


    References
 Top
 Abstract
 Introduction
 Population pharmacokinetic data
 In vitro susceptibility
 Use of pharmacodynamics in...
 Integration of in vitro...
 Clinical outcome data
 Combination therapy
 Summary
 References
 
1 . Jarvis, W. R. & Martone, W. J. (1992). Predominant pathogens in hospital infections. Journal of Antimicrobial Chemotherapy 29, 19–24.[Abstract]

2 . Bryan, C. S., Reynolds, K. L. & Brenner, E. R. (1983). Analysis of 1,186 episodes of gram-negative bacteremia in non-university hospitals: the effects of antimicrobial therapy. Reviews of Infectious Diseases 5, 629–38.[ISI][Medline]

3 . Bodey, G. P., Bolivar, R., Fainstein, V. & Jadeja, L. (1983). Infections caused by Pseudomonas aeruginosa. Reviews of Infectious Diseases 5, 279–313.[ISI][Medline]

4 . Gribble, M. J., Chow, A. W., Naiman, S. C., Smith, J. A., Bowie, W. R., Sacks, S. L. et al. (1983). Prospective randomized trial of piperacillin monotherapy versus carboxypenicillin–aminoglycoside combination regimens in the empirical treatment of serious bacterial infections. Antimicrobial Agents and Chemotherapy 24, 388–93.[ISI][Medline]

5 . Kollef, M. H., Ward, S., Sherman, G., Prentice, D., Schaiff, R., Huey, W. et al. (2000). Inadequate treatment of nosocomial infections is associated with certain empiric antibiotic choices. Critical Care Medicine 28, 3456–64.[ISI][Medline]

6 . Barbhaiya, R. H., Knupp, C. A., Forgue, S. T., Matzke, G. R., Guay, D. R. P. & Pittman, K. A. (1990). Pharmacokinetics of cefepime in subjects with renal insufficiency. Clinical Pharmacology and Therapeutics 48, 268–76.[ISI][Medline]

7 . Barbhaiya, R. H., Knupp, C. A., Forgue, S. T., Matzke, G. R., Halstenson, C. E., Opsahl, J. A. et al. (1991). Disposition of the cephalosporin cefepime in normal and renally impaired subjects. Drug Metabolism and Disposition 19, 68–70.[Abstract]

8 . Barbhaiya, R. H., Forgue, S. T., Gleason, C. R., Knupp, C. A., Pittman, K. A., Weidler, D. J. et al. (1992). Pharmacokinetics of cefepime after single and multiple intravenous administrations in healthy subjects. Antimicrobial Agents and Chemotherapy 36, 552–7.[Abstract]

9 . Barbhaiya, R. H., Knupp, C. A. & Pittman, K. A. (1992). Effects of age and gender on pharmacokinetics of cefepime. Antimicrobial Agents and Chemotherapy 36, 1181–5.[Abstract]

10 . Cronqvist, J., Nilsson-Ehle, I., Oqvist, B. & Norrby S. R. (1992). Pharmacokinetics of cefepime dihydrochloride arginine in subjects with renal impairment. Antimicrobial Agents and Chemotherapy 36, 2676–80.[Abstract]

11 . Ambrose, P. G., Richerson, M. A., Stanton, M. E., Bui, K. Q., Nicolau, D. P., Nightingale, C. H. et al. (1999). Cost-effective analysis of cefepime compared with ceftazidime in intensive care unit patients with hospital-acquired pneumonia. Infectious Diseases in Clinical Practice 8, 245–51.[ISI]

12 . Wolff, W. (1998). Comparison of strategies using cefpirome and ceftazidime for empiric treatment of pneumonia in intensive care unit patients. Antimicrobial Agents and Chemotherapy 42, 28–36.[Abstract/Free Full Text]

13 . Giamarellou, H. (1993). Low-dosage cefepime as treatment for serious bacterial infections. Journal of Antimicrobial Chemotherapy 32, Suppl. B, 123–32.[Abstract]

14 . Arguedas, A. G., Stutman, H. R., Zaleska, M., Knupp, C. A. & Marks, M. I. (1992). Cefepime pharmacokinetics and clinical response in patients with cystic fibrosis. American Journal of Diseases of Children 146, 797–802.[Abstract]

15 . Kieft, H., Hoepelman, A. I. M., Knupp, C. A., van Dijk, A. & Branger, J. M. (1993). Pharmacokinetics of cefepime in patients with sepsis syndrome. Journal of Antimicrobial Chemotherapy 32, Suppl. B, 117–22.[Abstract]

16 . Kovarik, J. M., ter Maaten, J. C., Rademaker, C. M. A., Deenstra, M. & Hoepelman, I. M. (1990). Pharmacokinetics of cefepime in patients with respiratory tract infections. Antimicrobial Agents and Chemotherapy 34, 1885–8.[ISI][Medline]

17 . Pfaller, M. A., Jones, R. N., Doern, G. V. & Kugler, K. (1998). Bacterial pathogens isolated from patients with blood stream infection: frequencies of occurrence and antimicrobial susceptibility patterns from the SENTRY Antimicrobial Surveillance Program. Antimicrobial Agents and Chemotherapy 42, 1762–70.[Abstract/Free Full Text]

18 . Jones, R. N. (1999). Summation: beta-lactam resistance surveillance in the Asia-Western Pacific region. Diagnostic Microbiology and Infectious Disease 35, 333–8.[ISI][Medline]

19 . Dudley, M. N. & Ambrose, P. G. (2000). Pharmacodynamics in the study of resistance and establishing in vitro susceptibility breakpoints: ready for prime time. Current Opinion in Microbiology 3, 515–21.[ISI][Medline]

20 . Moore, R. D., Lietman, P. S. & Smith, C. R. (1987). Clinical response to aminoglycoside therapy: importance of ratio of antibiotic peak concentration to MIC for bactericidal activity and emergence of resistance. Antimicrobial Agents and Chemotherapy 31, 1054–60.[ISI][Medline]

21 . Drusano, G. L., Johnson, D. E. & Rosen, M. (1993). Pharmacodynamics of a fluoroquinolone antimicrobial agent in a neutropenic animal model of pseudomonal sepsis. Antimicrobial Agents and Chemotherapy 37, 483–90.[Abstract]

22 . Fantin, B., Leggett, J., Ebert, S. & Craig, W. A. (1991). Correlation between in vitro and in vivo activity of antimicrobial agents against gram-negative bacilli in a murine infection model. Antimicrobial Agents and Chemotherapy 35, 1413–22.[ISI][Medline]

23 . Craig, W. A. (1998). Pharmacokinetic/pharmacodynamic parameters: rationale for dosing in mice and men. Clinical Infectious Diseases 26, 1–12.[ISI][Medline]

24 . Ambrose, P. G., Owens, R. C. & Grasela, D. M. (2000). Antimicrobial pharmacodynamics. Medical Clinics of North America 84, 1431–45.[ISI][Medline]

25 . Forrest, A., Nix, D. E., Ballow, C. H., Goss, T. F., Birmingham, M. C. & Schentag, J. J. (1993). Pharmacodynamics of intravenous ciprofloxacin in seriously ill patients. Antimicrobial Agents and Chemotherapy 37, 1073–81.[Abstract]

26 . Forrest, A., Chodash, S., Amantea, M. A., Collins, D. A. & Schentag, J. J. (1997). Pharmacokinetics and pharmacodynamics of oral grepafloxacin in patients with acute exacerbations of chronic bronchitis. Journal of Antimicrobial Chemotherapy 40, Suppl. A, 45–57.[Abstract/Free Full Text]

27 . Lacy, M. L., Lu, W., Xu, X., Nicolau, D. P., Quintiliani, R. & Nightingale, C. H. (1999). Pharmacodynamic comparisons of levofloxacin and ciprofloxacin against Streptococcus pneumoniae in an in vitro model of infection. Antimicrobial Agents and Chemotherapy 43, 79–86.

28 . Eagle, H., Fleischman, R. & Levy, M. (1953). Continuous vs. discontinuous therapy with penicillin. New England Journal of Medicine 238, 481–8.

29 . Nishida, M., Murakawa, T. & Kaminura, T. (1978). Bactericidal activity of cephalosporins in an in vitro model of simulating serum levels. Antimicrobial Agents and Chemotherapy 14, 6–12.[ISI][Medline]

30 . Craig, W. A. (1995). Interrelationship between pharmacokinetics and pharmacodynamics in determining dosage regimens for broad-spectrum cephalosporins. Diagnostic Microbiology and Infectious Disease 22, 89–96.[ISI][Medline]

31 . Griffith, D., Chan, S., Liu, C., Corcoran, E., Tembe, V., Huie, K. et al. (1999). The novel cephalosporin is active against vancomycin-intermediate S. aureus (VISA) in the neutropenic mouse thigh model. In Proceedings of the Thirty-ninth Interscience Conference on Antimicrobial Agents and Chemotherapy, San Francisco, CA, 1999. Abstract 1768, p. 41. American Society for Microbiology, Washington, DC.

32 . Griffith, D. & Dudley, M. N. (2000). Pharmacodynamics of RWI-333441 (MC-04546) when administered as the l-aspartyl prodrug RWJ-333442 (MC-04699). In Proceedings of the Fortieth Interscience Conference on Antimicrobial Agents and Chemotherapy, Toronto, Canada, 2000. Abstract 2248, p. 33. American Society for Microbiology, Washington, DC.

33 . Preston, S. L., Drusano, G. L., Berman, A. L., Fowler, C. L., Chow, A. T., Dornseif, B. et al. (1998). Pharmacodynamics of levofloxacin: a new paradigm for early clinical trials. Journal of the American Medical Association 279, 125–9.[Abstract/Free Full Text]

34 . Ambrose, P. G., Grasela, D. M., Grasela, T. H., Passarell, J., Mayer, H. B. & Pierce, P. F. (2001). Pharmacodynamics of fluoroquinolones against Streptococcus pneumoniae: analysis of phase-III clinical trials. Antimicrobial Agents and Chemotherapy 45, 2793–7.[Abstract/Free Full Text]

35 . Sanders, W. E., Tenney, J. H. & Kessler, R. E. (1996). Efficacy of cefepime in the treatment of infections due to multiply resistant Enterobacter spp. Clinical Infectious Diseases 23, 454–61.[ISI][Medline]

36 . Ambrose, P. G. & Grasela, D. M. (2000). The use of Monte Carlo simulation to examine the pharmacodynamic variance of drugs: fluoroquinolone pharmacodynamics against Streptococcus pneumoniae. Diagnostic Microbiology and Infectious Disease 38, 151–7.[ISI][Medline]

37 . Ambrose, P. G. & Quintiliani, R. (2000). Limitations of single-point pharmacodynamic analysis. Pediatric Infectious Disease Journal 19, 769.

38 . Garner, J. S., Jarvis, W. R. & Emori, T. G. (1988). CDC definitions for nosocomial infections. American Journal of Infection Control 16, 128–40.[ISI][Medline]

39 . Drusano, G. L., Preston, S. L., Hardalo, C., Hare, R., Banfield, C., Andes, D. et al. (2001). Use of preclinical data for selection of a phase II/III dose for evernimicin and identification of a preclinical MIC breakpoint. Antimicrobial Agents and Chemotherapy 45, 13–22.[Abstract/Free Full Text]

40 . Grant, E. M., Ambrose, P. G., Nicolau, D. P., Nightingale, C. H. & Quintiliani, R. (2000). Clinical efficacy of cefepime in pneumonia caused by Pseudomonas aeruginosa. In Proceedings of the Fortieth Interscience Conference on Antimicrobial Agents and Chemotherapy, Toronto, Canada, 2000. Abstract 742, p. 494. American Society for Microbiology, Washington, DC.

41 . Edelstein, H., Chirurgi, V. & Oster, S. (1991). A randomized trial of cefepime and ceftazidime for the treatment of pneumonia. Journal of Antimicrobial Chemotherapy 28, 569–75.[Abstract]

42 . Fink, M. P., Snydman, D. R. & Niederman, M. S. (1994). Treatment of severe pneumonia in hospitalized patients: results of a multicenter, randomized, double-blind trial comparing intravenous ciprofloxacin with imipenem–cilastatin. Antimicrobial Agents and Chemotherapy 38, 547–57.[Abstract]

43 . Norrby, S. R., Finch, R. G. & Glauser, M. (1993). Monotherapy in serious hospital-acquired infections: a clinical trial of ceftazidime vs. imipenem/cilastatin. Journal of Antimicrobial Chemotherapy 31, 927–37.[Abstract]

44 . Rubinstein, E., Lode, H. & Grassi, C. (1995). Ceftazidime monotherapy vs. ceftriaxone/tobramycin for serious hospital-acquired gram-negative infections. Clinical Infectious Diseases 20, 1217–28.[ISI][Medline]

45 . Hilf, M., Yu, V. L., Sharp, J., Zuravleff, J. J., Korvick, J. A. & Muder, R. R. (1989). Antibiotic therapy for Pseudomonas aeruginosa bacteremia: outcome correlations in a prospective study of 200 patients. American Journal of Medicine 87, 540–6.[ISI][Medline]

46 . Chow, J. W., Fine, M. J., Shlaes, D. M., Quinn, J. P., Hooper, D. C., Johnson, M. P. et al. (1991). Enterobacter bacteremia: clinical features and emergence of antibiotic resistance during therapy. Annals of Internal Medicine 115, 585–90.[ISI][Medline]

47 . Leibovici, L., Paul, M., Poznanski, O., Drucker, M., Samra, Z., Konigsberger, H. et al. (1997). Monotherapy versus ß-lactam–aminoglycoside combination treatment for gram-negative bacteremia: a prospective, observational study. Antimicrobial Agents and Chemotherapy 41, 1127–33.[Abstract]

48 . Cometta, A., Baumgartner, J. D., Lew, D., Zimmerli, W., Pittet, D., Chopart, P. et al. (1994). Prospective randomized comparison of imipenem monotherapy with imipenem plus netilmicin for treatment of severe infections in nonneutropenic patients. Antimicrobial Agents and Chemotherapy 38, 1309–13.[Abstract]

49 . Piccart, M., Klastersky, J., Meunier, F., Lagast, H., Van Laethem, Y. & Weerts, D. (1984). Single-drug versus combination empirical therapy for gram-negative bacillary infections in febrile cancer patients with and without granulocytopenia. Antimicrobial Agents and Chemotherapy 26, 870–5.[ISI][Medline]

50 . Bragman, S., Sage, R. & Booth, L. (1986). Ceftazidime in the treatment of serious Pseudomonas aeruginosa sepsis. Scandinavian Journal of Infectious Diseases 18, 425–9.[ISI][Medline]

51 . Pedersen, S. S., Koch, C., Hoiby, N. & Rosendal, K. (1986). An epidemic spread of multiresistant Pseudomonas aeruginosa in a cystic fibrosis center. Journal of Antimicrobial Chemotherapy 17, 505–16.[Abstract]

52 . Bach, M. C. & Cocchetto, D. M. (1987). Ceftazidime as single-agent therapy for gram-negative aerobic bacillary osteomyelitis. Antimicrobial Agents and Chemotherapy 31, 1605–8.[ISI][Medline]

53 . Owens, R. C., Jr, Banevicius, M. A., Nicolau, D. P., Nightingale, C. H. & Quintiliani, R. (1997). In vitro synergistic activities of tobramycin and selected beta-lactams against 75 gram-negative clinical isolates. Antimicrobial Agents and Chemotherapy 41, 2586–8.[Abstract]

54 . Bosso, J. A., Saxon, B. A. & Matsen, J. M. (1991). Comparative activity of cefepime, alone and in combination, against clinical isolates of Pseudomonas aeruginosa and Pseudomonas cepacia from cystic fibrosis patients. Antimicrobial Agents and Chemotherapy 35, 783–4.[ISI][Medline]

55 . Cappelletty, D. M. (1999). Evaluation of several dosing regimens of cefepime, with various simulations of renal function, against clinical isolates of Pseudomonas aeruginosa in a pharmacodynamic infection model. Antimicrobial Agents and Chemotherapy 43, 129–35.[Abstract/Free Full Text]

56 . Moody, J. A., Peterson, L. R. & Gerding, D. N. (1986). Comparative in vitro activity of BMY-28142 alone and in combination with amikacin against clinical strains of Pseudomonas aeruginosa, Staphylococcus aureus, and Enterobacteriaceae. Current Therapeutic Research, Clinical and Experimental 39, 230–8.[ISI]

57 . Neu, H. C. (1993). Synergy and antagonism of fluoroquinolones with other classes of antimicrobial agents. Drugs 45, Suppl. 3, 54–8.[Medline]

58 . Stratton, C. W., Franke, J. J., Weeks, L. S. & Manion, F. A. (1989). Comparison of the bactericidal activity of ciprofloxacin alone and in combination with selected antipseudomonal ß-lactam agents against clinical isolates of Pseudomonas aeruginosa. Diagnostic Microbiology and Infectious Disease 11, 41–52.[ISI]

59 . Eliopoulos, G. M. & Eliopoulos, C. T. (1989). Ciprofloxacin in combination with other antimicrobials. American Journal of Medicine 87, Suppl. 5A, 17s–22s.

60 . Schaad, U. B., Eskola, J., Kafetzis, D., Fishbach, M., Ashkenazi, S., Syriopoulou, V. et al. (1998). Cefepime vs. ceftazidime treatment of pyelonephritis: a European, randomized, controlled study of 300 pediatric cases. Pediatric Infectious Disease Journal 17, 639–44.[ISI][Medline]

61 . Willis, R., Gaines, J. & Nelson, M. (1998). Cefepime vs. cefotaxime in the treatment of pneumonia. Infections in Medicine 15, 636–43.[ISI]

62 . Barie, P. S., Vogel, S. B., Dellinger, E. P., Rotstein, O. D., Solomkin, J. S., Yang, J. Y. et al. (1997). A randomized, double-blind clinical trial comparing cefepime plus metronidazole with imipenem– cilastatin in the treatment of complicated intra-abdominal infections. Archives of Surgery 132, 1294–302.[Abstract]

63 . Gouin, F., Papazian, L., Martin, C., Albanese, J., Durbec, O., Domart, Y. et al. (1993). A non-comparative study of the efficacy and tolerance of cefepime in combination with amikacin in the treatment of severe infections in patients in intensive care. Journal of Antimicrobial Chemotherapy 32, Suppl. B, 205–14.[ISI][Medline]

64 . Hoepelman, A. I. M., Kieft, H., Aoun, M., Kosmidis, J., Strand, T., Verhoef, J. et al. (1993). International comparative study of cefepime and ceftazidime in the treatment of serious bacterial infections. Journal of Antimicrobial Chemotherapy 32, Suppl. B, 175–86.[ISI][Medline]

65 . Holloway, W. J. & Palmer, D. (1996). Clinical applications of a new parenteral antibiotic in the treatment of severe bacterial infections. American Journal of Medicine 100, Suppl. 6A, 52s–59s.

66 . Owens, R. C., Jr, Owens, C. A. & Holloway, W. J. (1999). Comparative evaluation of the cefepime Q12 h dosing schedule as empiric monotherapy in febrile neutropenic patients. Pharmacotherapy 19, 496–7.