Kristoffersson A N, Rognås V, Brill M J E, Dishon-Benattar Y, Durante-Mangoni E, Daitch V, Skiada A, Lellouche J, Nutman A, Kotsaki A, Andini R, Eliakim-Raz N, Bitterman R, Antoniadou A, Karlsson M O, Theuretzbacher U, Leibovici L, Daikos G L, Mouton J W, Carmeli Y, Paul M, Friberg L E
Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Institute of Infectious Diseases, Rambam Health Care Campus, Haifa, Israel; The Cheryl Spencer Institute for Nursing Research, University of Haifa, Israel.
Clin Microbiol Infect. 2020 Dec;26(12):1644-1650. doi: 10.1016/j.cmi.2020.03.016. Epub 2020 Mar 22.
The aim was to analyse the population pharmacokinetics of colistin and to explore the relationship between colistin exposure and time to death.
Patients included in the AIDA randomized controlled trial were treated with colistin for severe infections caused by carbapenem-resistant Gram-negative bacteria. All subjects received a 9 million units (MU) loading dose, followed by a 4.5 MU twice daily maintenance dose, with dose reduction if creatinine clearance (CrCL) < 50 mL/min. Individual colistin exposures were estimated from the developed population pharmacokinetic model and an optimized two-sample per patient sampling design. Time to death was evaluated in a parametric survival analysis.
Out of 406 randomized patients, 349 contributed pharmacokinetic data. The median (90% range) colistin plasma concentration was 0.44 (0.14-1.59) mg/L at 15 minutes after the end of first infusion. In samples drawn 10 hr after a maintenance dose, concentrations were >2 mg/L in 94% (195/208) and 44% (38/87) of patients with CrCL ≤120 mL/min, and >120 mL/min, respectively. Colistin methanesulfonate sodium (CMS) and colistin clearances were strongly dependent on CrCL. High colistin exposure to MIC ratio was associated with increased hazard of death in the multivariate analysis (adjusted hazard ratio (95% CI): 1.07 (1.03-1.12)). Other significant predictors included SOFA score at baseline (HR 1.24 (1.19-1.30) per score increase), age and Acinetobacter or Pseudomonas as index pathogen.
The population pharmacokinetic model predicted that >90% of the patients had colistin concentrations >2 mg/L at steady state, but only 66% at 4 hr after start of treatment. High colistin exposure was associated with poor kidney function, and was not related to a prolonged survival.
分析多黏菌素的群体药代动力学，并探讨多黏菌素暴露与死亡时间之间的关系。
纳入AIDA随机对照试验的患者接受多黏菌素治疗，用于治疗由耐碳青霉烯革兰阴性菌引起的严重感染。所有受试者均接受900万单位（MU）的负荷剂量，随后每日两次接受450万单位的维持剂量，若肌酐清除率（CrCL）<50 mL/min则减少剂量。根据建立的群体药代动力学模型和优化的每位患者两个样本的采样设计估算个体多黏菌素暴露量。在参数生存分析中评估死亡时间。
在406例随机分组的患者中，349例提供了药代动力学数据。首次输注结束后15分钟时，多黏菌素血浆浓度的中位数（90%范围）为0.44（0.14 - 1.59）mg/L。在维持剂量后10小时采集的样本中，CrCL≤120 mL/min和>120 mL/min的患者中，浓度>2 mg/L的分别占94%（195/208）和44%（38/87）。多黏菌素甲磺酸钠（CMS）和多黏菌素清除率强烈依赖于CrCL。在多变量分析中，高多黏菌素暴露与MIC比值与死亡风险增加相关（调整后的风险比（95% CI）：1.07（1.03 - 1.12））。其他显著预测因素包括基线时的SOFA评分（每增加一分，HR为1.24（1.19 - 1.30））、年龄以及以不动杆菌或假单胞菌作为指示病原体。
群体药代动力学模型预测，>90%的患者在稳态时多黏菌素浓度>2 mg/L，但在治疗开始后4小时仅为66%。高多黏菌素暴露与肾功能不佳相关，且与生存期延长无关。
