title: Antimicrobial breakpoints for gram-negative aerobic bacteria based on pharmacokinetic-pharmacodynamic models with Monte Carlo simulation.
abstract: OBJECTIVE
  This study describes a comprehensive programme designed to develop pharmacokinetic-pharmacodynamic (PK-PD) breakpoints for numerous antimicrobial classes against key gram-negative aerobic bacteria.
  
  
  METHODS
  A 10,000 subject Monte Carlo simulation was constructed for 13 antimicrobials (21 dosing regimens). Published pharmacokinetic data and protein binding were varied according to log-normal and uniform distributions. MICs were fixed at single values from 0.03 to 64 mg/L. The PK-PD susceptible breakpoint was defined as the MIC at which the probability of target attainment was > or = 90%. PK-PD, CLSI and European Committee on Antimicrobial Susceptibility Testing breakpoints were applied to MICs from the 2005 worldwide Meropenem Yearly Susceptibility Test Information Collection database to evaluate the impact of breakpoint discrepancies.
  
  
  RESULTS
  PK-PD breakpoints were within one dilution of the CLSI and European breakpoints for all antimicrobials tested--with a few exceptions. When discrepancies were noted, the PK-PD breakpoint was lower than the CLSI breakpoint [ceftriaxone (0.5 versus 8 mg/L), ertapenem (0.25 versus 2 mg/L), ciprofloxacin (0.125 versus 1 mg/L) and levofloxacin (0.25-0.5 versus 2 mg/L)] and higher than the European breakpoint [ceftazidime (4-8 versus 1 mg/L), aztreonam (4-8 versus 1 mg/L), although ciprofloxacin was an exception to this pattern (0.125 versus 0.5-1 mg/L)]. For Enterobacteriaceae, breakpoint discrepancies resulted in modest (< or = 10%) differences in the percentages susceptible. In contrast, large (> 15%) discrepancies were noted for Pseudomonas aeruginosa and Acinetobacter baumannii.
  
  
  CONCLUSIONS
  Breakpoint agreement exists for imipenem, meropenem and the aminoglycosides. In contrast, discrepancies exist for piperacillin/tazobactam, cephalosporins, ertapenem, aztreonam and the fluoroquinolones. These discrepancies are most pronounced for P. aeruginosa and A. baumannii.
authors.affiliation: Center for Advancement of Research and Education in Infectious Diseases, The University of Texas at Austin, Austin, TX, USA. freic@uthscsa.edu
authors.forename: Christopher R
authors.initials: CR
authors.lastname: Frei
authors.forename: Nathan P
authors.initials: NP
authors.lastname: Wiederhold
authors.forename: David S
authors.initials: DS
authors.lastname: Burgess
mesh_terms: D000890:Anti-Infective Agents / Q000493:pharmacokinetics* / Q000494:pharmacology; D006088:Gram-Negative Aerobic Bacteria / Q000187:drug effects* / Q000378:metabolism*; D006801:Humans; D008954:Models, Biological; D009010:Monte Carlo Method; D010599:Pharmacokinetics
chemical_list: D000890:Anti-Infective Agents