Aztreonam (AZM) is a monobactam antibiotic with a high level of activity against gram-negative microorganisms, including Pseudomonas aeruginosa. We evaluated AZM pharmacokinetics and pharmacokinetic-pharmacodynamic relationships in patients with cystic fibrosis (CF) and healthy subjects. Pharmacokinetic data in eight CF patients and healthy subjects that were matched for age, gender, weight, and height were obtained and analyzed by using the nonparametric adaptive grid algorithm. Probabilities of target attainment using percentages of time of unbound concentration above the MIC (fT> MIC) were obtained by using a Monte Carlo simulation. AZM total body clearance was significantly higher in CF patients (100.1 ± 17.1 versus 76.2 ± 7.4 ml/min in healthy subjects; P < 0.01). The pharmacokinetic parameter estimates for terminal half-life (1.54 ± 0.17 h [mean ± the standard deviation]) and volume of distribution (0.20 ± 0.02 liters/kg in patients with CF patients were not different from those in healthy subjects. Monte Carlo simulations with a target of a fT> MIC of 50 to 60% at a dose of 1,000 mg every 8 h indicated a clinical breakpoint of 4 mg/liter and 1 to 2 mg/liter for healthy subjects and CF patients, respectively. This study using matched controls showed that AZM total body clearance and not the volume of distribution is higher in CF patients as a result of increased renal clearance. Pharmacokinetic parameter estimates in healthy subjects resulted in a clinical susceptibility breakpoint of ≤4 mg/liter for a dose of 1,000 mg every 8 h. Patients suspected of having high clearance rates, such as CF patients, should be monitored closely, with dosing regimens adjusted accordingly. Copyright

doi.org/10.1128/AAC.01522-06, hdl.handle.net/1765/35211
Antimicrobial Agents and Chemotherapy
Erasmus MC: University Medical Center Rotterdam

Vinks, A., van Rossem, R., Mathot, R., Heijerman, H., & Mouton, J. (2007). Pharmacokinetics of aztreonam in healthy subjects and patients with cystic fibrosis and evaluation of dose-exposure relationships using Monte Carlo simulation. Antimicrobial Agents and Chemotherapy, 51(9), 3049–3055. doi:10.1128/AAC.01522-06