MRSA Micro Scan Pos Combo 6J DADE BEHRING VCM

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1 PKPD MRSA vancomycinvcm methicillin-resistant Staphylococcus aureusmrsa 31 pharmacokineticpkparameter retrospective VCM PK parameter Mann- Whitney U-test Cmax 37.1 µ gml µ gml p µ gml µ gml p0.25ke 0.17hr hr p0.67AUC 410 µ gmlhr µ gmlhr p0.01auc AUC Receiver Operating CharacteristicROC 330 µ gmlhr MRSA 373 MIC MIC90 1 µ gml AUC 1,000 AUCMIC330 µ gmlhr 56.8 VCM AUC AUCMIC330 µ gmlhr VCM 1 AUC MIC Key words: MRSAvancomycinAUCMICMonte Carlo simulationpneumonia Staphylococcus aureus MRSA MRSA MRSA vancomycinvcm TDM pharmacokineticpharmacodinamicpkpd VCM 24 AUC MIC AUCMIC 1,2 VCM TDM MRSA PK parameter PD VCM MIC PKPD I VCM TDM MRSA 63 MRSA VCM 31 PKPD MRSA MRSA WBC CRP 4 VCM VCM CRP 70 2 VCM arbekacinabk teicoplaninteic MRSA Micro Scan Pos Combo 6J DADE BEHRING VCM

2 Sensitivity% AUC specificity% Fig. 1. Dots show AUC sensitivity and specificity of AUC used to predict clinical efficacy. Dots in the leftupper quadrant indicate high sensitivity and high specificity. AUC330 showed the best performance. II PK parameter VCM-TDM on Excel Ver. 2.0 AUC AUC mgkevd Dr. SPSS II for Windows JSPSS Inc. Mann-Whitney Fisher P0.01 VCM PKPD Receiver Operating CharacteristicROC PKPD VCM VCM PK parameter MRSA VCM MIC 1, MRSA VCM MIC MIC 0.5 µ gml µ gml µ gml µ gml Crystal Ball 2000 Professional EditionDecisioneering Inc. II TDM Table 1

3 MRSA VCM PKPD 1,000 trials Certainty is 58.60% from to infinity Probability Frequency ,000.0 AUC/MIC Fig. 2. Results of 1,000-patient Monte Carlo simulation on AUCMIC from patient pharmacokinetic data reflective of a good outcomen21and MRSA MICn373from a hospital survey. Light-colored bars represent numbers of patients with AUCMIC 330. Dark-colored bars represent numbers of patients with AUCMIC 330. The probability of attaining AUCMIC 330 is PK parameter CmaxKe Vd AUCµ gmlhr 410 µ gmlhr µ gmlhr p0.01 AUC ROC µ gmlhr 10 µ gmlhr 330 µ gmlhr Fig MRSA 373 MIC VCM AUC 1,000 AUCMIC 330 µ g mlhr 56.8 Fig. 2 III PKPD CmaxMICtime above MIC AUCMIC PKPD 1 TDM VCM 10 µ gml Cmax 2540 µ gml 6 VCM VCM MIC post antibiotic effectpae AUCMIC 7 Knudsen AUCMIC CmaxMIC 8 Moise MRSA 53 VCM AUCMIC AUCMIC 345 µ gmlhr 24 9 ROC VCM AUC 330 µ gmlhr AUC VCM VCM MIC ABK TEIC MIC 1 µ gml MIC 1 µ gml 83 VCM MRSA VCM MIC 1 µ gml VCM MIC AUC TDM AUC MIC PKPD 35 AUCMIC 330 µ gmlhr

4 1, AUCMIC330 µ gmlhr TDM Cmax AUCMIC 330 µ gmlhr 31 TDM Cmax VCM AUC AUC TDM AUC MIC 1 Craig W A: Basic pharmacodynamics of antibacterials with clinical applications to the use of β -lactams, glycopeptides, and linezolid. Infect Dis Clin N Am 17: , Schentag J J: Antimicrobial management strategies for Gram-positive bacterial resistance in the intensive care unit. Crit Care Med 29: N100N107, Ambrose P G, Grasela D M: The use of Monte Carlo simulation to examine pharmacodynamic variance of drugs : fluoroquinolone pharmacodynamics against Streptococcus pneumoniae. Diagn Microbiol Infect Dis 38: , Kuti J L, Nightingale C H, Quintiliani R, et al: Pharmacodynamic profiling of continuously infused piperacillintazobactam against Pseudomonas aeruginosa using Monte Carlo analysis. Diagn Microbiol Infect Dis 44: 5157, Ambrose P G, Owens R C, Garvey M J, et al: Pharmacodynamic considerations in the treatment of moderate to severe pseudomonal infections with Cefepime. J Antimicrob Chemother 49: , Matzke G R, Zhanel G G, Guay D R P: Clinical pharmacokinetics of Vancomycin. Clin Pharmacokinet 11: , Craig W A, Gudmundsson S: Postantibiotic Effect. In Antibiotics in Laboratory Medicine 4th ed.victor L ed, p , Williams and Wilkins, Baltimore, Knudsen J D, Fuursted K, Raber S, et al: Pharmacodynamics of Glycopeptides in the mouse peritonitis model of Streptococcus pneumoniae or Staphylococcus aureus infection. Antimicrob Agent Chemother 44: , Moise P A, Forrest A, Bhavnavi S M, et al: Area under the inhibitory curve and a pneumonia scoring system for predicting outcomes of Vancomycin therapy for respiratory infections by Staphylococcus aureus. Am J Health-Syst Pharm 57: S4S9, Fluit A C, Wielders C L C, Verhoef J, et al: Epidemiology and susceptibility of 3,051 Staphylococcus aureus isolates from 25 university hospitals participating in the European SENTRY Study. J Clin Microbiol 39 : , Diekema D J, Pfaller M A, Schmitz F J, et al: Survey of infectious due to Staphylococcus Species: Frequency of occurrence and antimicrobial susceptibility of isolates collected in the United States, Canada, Latin America, Europe, and the Western Pacific region for the SENTRY Antimicrobial Surveillance Program, Clin Infect Dis 32Suppl 2: S114S132, Jpn J Antibiot 57: , 2004

5 MRSA VCM PKPD Clinical significance of pharmacokineticpharmacodinamic variables using Monte Carlo simulation in vancomycin treatment of pulmonary methicillin-resistant Staphylococcus aureus infection Yusuke Inagaki 1, Masaru Komatsu 1, Ikuyoshi Yamamoto 2 and Shuji Matsuo 1 1 Departments of Clinical Pathology and 2 Pharmacy, Tenri Hospital, 200 Mishima, Tenri, Nara, Japan In studying the relationship between pharmacokinetic variables for serum vancomycinvcmand therapeutic outcome, we analyzed data from 31 patients with pneumonia caused by methicillin-resistant Staphylococcus aureusmrsa. VCM was effective in 21. Comparing pharmacokinetic variables between the 21 responders and 10 nonresponders yielded the following medianinterquartile rangewithin 1-2 hours after VCM administration was stopped: Cmax, 37.1 µ gml vs µ gml p0.32; trough, 10.5 µ gml8-12.4vs. 8.7 µ gml P0.25; elimination constantke,0.17h vs. 0.15hr P0.67; and area-under-the-concentration curveauc, 410 µ ghml vs. 318 µ gmlhr p0.01. AUC was the only statistically significant pharmacokinetic variable. Receiver operating characteristic curve analysis showed AUC cutoff of 330 µ gmlhrsensitivity, 76.2; specificity, AUCdistribution for the 21 responders and MIC distribution for VCM of 373 MRSA strains isolated at Tenri Hospital were integrated over 1,000 Monte Carlo simulation trials. The probability of attaining an AUCMIC of 330 was These results indicate that AUC reflected VCM clinical efficacy for MRSA pneumonia, and the AUC cutoff was 330 µ gmlhr. Monte Carlo simulation also indicated a low probability of attaining an AUCMIC ratio 330. We therefore suggest that the AUCMIC ratio be adopted as an index for VCM treatment.