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左氧氟沙星群体药代动力学及建立用于预测严重社区获得性感染患者个体药物清除率的人口统计学模型。

Levofloxacin population pharmacokinetics and creation of a demographic model for prediction of individual drug clearance in patients with serious community-acquired infection.

作者信息

Preston S L, Drusano G L, Berman A L, Fowler C L, Chow A T, Dornseif B, Reichl V, Natarajan J, Wong F A, Corrado M

机构信息

Department of Medicine, Albany Medical College, New York 12208, USA.

出版信息

Antimicrob Agents Chemother. 1998 May;42(5):1098-104. doi: 10.1128/AAC.42.5.1098.

Abstract

Population pharmacokinetic modeling is a useful approach to obtaining estimates of both population and individual pharmacokinetic parameter values. The potential for relating pharmacokinetic parameters to pharmacodynamic outcome variables, such as efficacy and toxicity, exists. A logistic regression relationship between the probability of a successful clinical and microbiological outcome and the peak concentration-to-MIC ratio (and also the area under the plasma concentration-time curve [AUC]/MIC ratio) has previously been developed for levofloxacin; however, levofloxacin assays for determination of the concentration in plasma are not readily available. We attempted to derive and validate demographic variable models to allow prediction of the peak concentration in plasma and clearance (CL) from plasma for levofloxacin. Two hundred seventy-two patients received levofloxacin intravenously for the treatment of community-acquired infection of the respiratory tract, skin or soft tissue, or urinary tract, and concentrations in plasma, guided by optimal sampling theory, were obtained. Patient data were analyzed by the Non-Parametric Expectation Maximization approach. Maximum a posteriori probability Bayesian estimation was used to generate individual parameter values, including CL. Peak concentrations were simulated from these estimates. The first 172 patients were used to produce demographic models for the prediction of CL and the peak concentration. The remaining 100 patients served as the validation group for the model. A median bias and median precision were calculated. A two-compartment model was used for the population pharmacokinetic analysis. The mean CL and the mean volume of distribution of the central compartment (V1) were 9.27 liters/h and 0.836 liter/kg, respectively. The mean values for the intercompartmental rate constants, the rate constant from the central compartment to the peripheral compartment (Kcp) and the rate constant from the peripheral compartment to the central compartment (Kpc), were 0.487 and 0.647 h(-1), respectively. The mean peak concentration and the mean AUC values normalized to a dosage of 500 mg every 24 h were 8.67 microg/ml and 72.53 microg x h/ml, respectively. The variables included in the final model for the prediction of CL were creatinine clearance (CLCR), race, and age. The median bias and median precision were 0.5 and 18.3%, respectively. Peak concentrations were predicted by using the demographic model-predicted parameters of CL, V1, Kcp and Kpc, in the simulation. The median bias and the median precision were 3.3 and 21.8%, respectively. A population model of the disposition of levofloxacin has been developed. Population demographic models for the prediction of peak concentration and CL from plasma have also been successfully developed. However, the performance of the model for the prediction of peak concentration was likely insufficient to be of adequate clinical utility. The model for the prediction of CL was relatively robust, with acceptable bias and precision, and explained a reasonable amount of the variance in the CL of levofloxacin from plasma in the population (r2 = 0.396). Estimated CLCR, age, and race were the final model covariates, with CLCR explaining most of the population variance in the CL of levofloxacin from plasma. This model can potentially optimize the benefit derived from the pharmacodynamic relationships previously developed for levofloxacin.

摘要

群体药代动力学建模是获取群体和个体药代动力学参数值估计的一种有用方法。存在将药代动力学参数与药效学结果变量(如疗效和毒性)相关联的可能性。先前已针对左氧氟沙星建立了成功的临床和微生物学结果概率与峰浓度与最低抑菌浓度之比(以及血浆浓度 - 时间曲线下面积[AUC]/最低抑菌浓度之比)之间的逻辑回归关系;然而,用于测定血浆中浓度的左氧氟沙星检测方法并不容易获得。我们试图推导并验证人口统计学变量模型,以便从血浆中预测左氧氟沙星的血浆峰浓度和清除率(CL)。272例患者接受静脉注射左氧氟沙星治疗社区获得性呼吸道、皮肤或软组织或泌尿道感染,并根据最佳采样理论获取血浆浓度。患者数据通过非参数期望最大化方法进行分析。使用最大后验概率贝叶斯估计来生成个体参数值,包括CL。从这些估计值模拟峰浓度。前172例患者用于生成预测CL和峰浓度的人口统计学模型。其余100例患者作为模型的验证组。计算了中位数偏差和中位数精密度。采用二室模型进行群体药代动力学分析。平均CL和中央室的平均分布容积(V1)分别为9.27升/小时和0.836升/千克。室间速率常数,即从中央室到周边室的速率常数(Kcp)和从周边室到中央室的速率常数(Kpc)的平均值分别为0.487和0.647小时^(-1)。每24小时给予500毫克剂量时的平均峰浓度和平均AUC值分别为8.67微克/毫升和72.53微克·小时/毫升。最终用于预测CL的模型中包含的变量有肌酐清除率(CLCR)、种族和年龄。中位数偏差和中位数精密度分别为0.5%和18.3%。在模拟中,通过使用人口统计学模型预测的CL、V1、Kcp和Kpc参数来预测峰浓度。中位数偏差和中位数精密度分别为3.3%和21.8%。已建立了左氧氟沙星处置的群体模型。也已成功开发出用于从血浆中预测峰浓度和CL的群体人口统计学模型。然而,该模型对峰浓度的预测性能可能不足以具有足够的临床实用性。CL预测模型相对稳健,具有可接受的偏差和精密度,并解释了群体中左氧氟沙星血浆CL的合理比例的方差(r2 = 0.396)。估计的CLCR、年龄和种族是最终模型协变量,其中CLCR解释了左氧氟沙星血浆CL群体方差的大部分。该模型有可能优化先前为左氧氟沙星建立的药效学关系所带来的益处。

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