Pharmacokinetics and pharmacodynamics of meropenem in elderly chinese with lower respiratory tract infections: population pharmacokinetics analysis using nonlinear mixed-effects modelling and clinical pharmacodynamics study.

BACKGROUND: Meropenem is a broad-spectrum antibacterial that is usually used in the treatment of serious lower respiratory tract infections (LRTIs). However, there is a lack of published studies exploring the correlation between the population pharmacokinetics of meropenem, the clinical pharmacodynamics of the drug and the response to the drug in Chinese patients with LRTIs, especially in the elderly.
OBJECTIVE: The aim of this study was to develop a pharmacokinetic model of meropenem using patient data and use this to explore the clinical pharmacodynamics of meropenem in the treatment of LRTIs in elderly Chinese patients.
METHODS: We measured serum meropenem concentrations in patients who had received meropenem 0.5 or 1.0 g infused over 0.5 hours every 8 or 12 hours, respectively. The pharmacokinetic analysis of meropenem was performed using nonlinear mixed-effects modelling (NONMEM®) software. The minimum inhibitory concentration (MIC) of meropenem against Gram-negative bacilli was tested by the E-test method. The pharmacodynamic parameters of percentage of time above MIC (%T>MIC), the ratio of the drug area under the serum concentration-time curve to MIC (AUC/MIC), the ratio of the maximum serum concentration of the drug to MIC (Cmax/MIC) and the ratio of the minimum serum concentration of the drug to MIC (Cmin/MIC) were analysed for their association with clinical and bacteriological outcomes.
RESULTS: A total of 284 serum meropenem concentration measurements were obtained from 75 patients (aged 63-95 years). A two-compartment model fitted the concentration data best. The covariates creatinine clearance (CLCR) and Acute Physiology and Chronic Health Evaluation (APACHE) II score had the most significant effects on meropenem pharmacokinetics. Forty-five patients were enrolled in the pharmacodynamic study, including 25 clinical responders and 21 patients with bacteriological eradication. All of the 45 patients had Gram-negative bacilli isolated from tracheal aspirate or sputum. The %T>MIC, AUC/MIC, Cmax/MIC and Cmin/MIC values for the 25 clinical responders were significantly higher than those for the nonresponders (all p<0.05). However, logistic regression analysis showed that only %T>MIC independently influenced clinical outcome (p=0.001, odds ratio [OR]=1.065). The cut-off value for predicting clinical success using %T>MIC was 76%; the sensitivity and specificity of %T>MIC for predicting a successful response were 84% and 85%, respectively. The %T>MIC, AUC/MIC, Cmax/MIC and Cmin/MIC values, and the serum level of albumin, for the 21 patients with bacteriological eradication were significantly higher than those for patients with bacteriological treatment failure (all p<0.05). Logistic regression analysis showed that %T>MIC (p=0.008, OR=1.047) and serum level of albumin (p=0.033, OR=1.434) independently influenced bacteriological eradication.
CONCLUSIONS: To our knowledge, this is the first study to investigate the population pharmacokinetics and clinical pharmacodynamics of meropenem in elderly Chinese. CLCR and APACHE II score have significant influences on meropenem pharmacokinetics. In LRTI patients, the cut-off value of 76% for %T>MIC can be applied to optimize their meropenem dose regimen to achieve clinical success.