Kim Yong Kyun, Lee Jae Ha, Jang Hang-Jea, Zang Dae Young, Lee Dong-Hwan
Division of Infectious Diseases, Department of Internal Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang 14066, Korea.
Division of Pulmonology and Critical Care Medicine, Department of Internal Medicine, Inje University Haeundae Paik Hospital, Inje University College of Medicine, Busan 48108, Korea.
Antibiotics (Basel). 2022 May 31;11(6):743. doi: 10.3390/antibiotics11060743.
This study aimed to investigate the effect of a structural pharmacokinetic (PK) model with fewer compartments developed following sparse sampling on the PK parameter estimation and the probability of target attainment (PTA) prediction of vancomycin. Two- and three-compartment PK models of vancomycin were used for the virtual concentration-time profile simulation. Datasets with reduced blood sampling times were generated to support a model with a lesser number of compartments. Monte Carlo simulation was conducted to evaluate the PTA. For the two-compartment PK profile, the total clearance (CL) of the reduced one-compartment model showed a relative bias (RBias) and relative root mean square error (RRMSE) over 90%. For the three-compartment PK profile, the CL of the reduced one-compartment model represented the largest RBias and RRMSE, while the steady-state volume of distribution of the reduced two-compartment model represented the largest absolute RBias and RRMSE. A lesser number of compartments corresponded to a lower predicted area under the concentration-time curve of vancomycin. The estimated PK parameters and predicted PK/PD index from models built with sparse sampling designs that cannot support the PK profile can be significantly inaccurate and unprecise. This might lead to the misprediction of the PTA and selection of improper dosage regimens when clinicians prescribe antibiotics.
本研究旨在探讨基于稀疏采样构建的较少房室结构药代动力学（PK）模型对万古霉素PK参数估计及达标概率（PTA）预测的影响。采用万古霉素的二房室和三房室PK模型进行虚拟浓度-时间曲线模拟。生成减少血样采集时间的数据集以支持较少房室数的模型。进行蒙特卡洛模拟以评估PTA。对于二房室PK曲线，简化的一房室模型的总清除率（CL）显示相对偏差（RBias）和相对均方根误差（RRMSE）超过90%。对于三房室PK曲线，简化的一房室模型的CL表现出最大的RBias和RRMSE，而简化的二房室模型的稳态分布容积表现出最大的绝对RBias和RRMSE。较少的房室数对应较低的万古霉素浓度-时间曲线下预测面积。基于无法支持PK曲线的稀疏采样设计构建的模型所估计的PK参数和预测的PK/PD指数可能会显著不准确和不精确。这可能导致临床医生在开具抗生素处方时对PTA的错误预测以及选择不恰当的给药方案。
