University of Groningen, University Medical Center Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands.
University of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases and Tuberculosis, Groningen, The Netherlands.
Antimicrob Agents Chemother. 2019 Jun 24;63(7). doi: 10.1128/AAC.00384-19. Print 2019 Jul.
Therapeutic drug monitoring (TDM) of moxifloxacin is recommended to improve the response to tuberculosis treatment and reduce acquired drug resistance. Limited sampling strategies (LSSs) are able to reduce the burden of TDM by using a small number of appropriately timed samples to estimate the parameter of interest, the area under the concentration-time curve. This study aimed to develop LSSs for moxifloxacin alone (MFX) and together with rifampin (MFX+RIF) in tuberculosis (TB) patients. Population pharmacokinetic (popPK) models were developed for MFX ( = 77) and MFX+RIF ( = 24). In addition, LSSs using Bayesian approach and multiple linear regression were developed. Jackknife analysis was used for internal validation of the popPK models and multiple linear regression LSSs. Clinically feasible LSSs (one to three samples, 6-h timespan postdose, and 1-h interval) were tested. Moxifloxacin exposure was slightly underestimated in the one-compartment models of MFX (mean -5.1%, standard error [SE] 0.8%) and MFX+RIF (mean -10%, SE 2.5%). The Bayesian LSSs for MFX and MFX+RIF (both 0 and 6 h) slightly underestimated drug exposure (MFX mean -4.8%, SE 1.3%; MFX+RIF mean -5.5%, SE 3.1%). The multiple linear regression LSS for MFX (0 and 4 h) and MFX+RIF (1 and 6 h), showed mean overestimations of 0.2% (SE 1.3%) and 0.9% (SE 2.1%), respectively. LSSs were successfully developed using the Bayesian approach (MFX and MFX+RIF; 0 and 6 h) and multiple linear regression (MFX, 0 and 4 h; MFX+RIF, 1 and 6 h). These LSSs can be implemented in clinical practice to facilitate TDM of moxifloxacin in TB patients.
治疗药物监测（TDM）推荐用于莫西沙星，以提高结核病治疗反应并降低获得性耐药性。有限采样策略（LSS）能够通过使用少量适当时间的样本来估计感兴趣的参数，即浓度-时间曲线下面积，从而减少 TDM 的负担。本研究旨在为结核病患者中的莫西沙星（MFX）单药治疗（MFX）和莫西沙星联合利福平（MFX+RIF）治疗开发 LSS。建立了 MFX（ = 77）和 MFX+RIF（ = 24）的群体药代动力学（popPK）模型。此外，还开发了贝叶斯方法和多元线性回归的 LSS。Jackknife 分析用于内部验证 popPK 模型和多元线性回归 LSS。测试了具有临床可行性的 LSS（一个至三个样本，给药后 6 小时时间窗，1 小时间隔）。在 MFX（平均 -5.1%，标准误差 [SE] 0.8%）和 MFX+RIF（平均 -10%，SE 2.5%）的单室模型中，莫西沙星的暴露量略有低估。MFX 和 MFX+RIF（均为 0 和 6 小时）的贝叶斯 LSS 对药物暴露量略有低估（MFX 平均 -4.8%，SE 1.3%；MFX+RIF 平均 -5.5%，SE 3.1%）。MFX（0 和 4 小时）和 MFX+RIF（1 和 6 小时）的多元线性回归 LSS 显示，平均高估了 0.2%（SE 1.3%）和 0.9%（SE 2.1%）。成功使用贝叶斯方法（MFX 和 MFX+RIF；0 和 6 小时）和多元线性回归（MFX，0 和 4 小时；MFX+RIF，1 和 6 小时）开发了 LSS。这些 LSS 可在临床实践中实施，以促进结核病患者中莫西沙星的 TDM。
