Zimmerman Kanecia O, Wu Huali, Greenberg Rachel, Guptill Jeffrey T, Hill Kevin, Patel Uptal D, Ku Lawrence, Gonzalez Daniel, Hornik Christoph, Jiang Wenlei, Zheng Nan, Melloni Chiara, Cohen-Wolkowiez Michael
*Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina; Departments of †Pediatrics and ‡Medicine, Duke University School of Medicine, Durham, North Carolina; §Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina; and ¶Office of Generic Drugs, US Food and Drug Administration, Silver Spring, Maryland.
Ther Drug Monit. 2016 Oct;38(5):600-6. doi: 10.1097/FTD.0000000000000313.
Sirolimus, an immunosuppressive agent used in renal transplantation, can prevent allograft rejection. Identification of the therapeutic index (the ratio of minimum toxic concentration to minimum therapeutic concentration) for immunosuppresants is necessary to optimize the care of patients and set standards for bioequivalence evaluation of sirolimus products. However, the therapeutic index for sirolimus has been inconsistently defined, potentially because of inconsistencies in sirolimus exposure-response relationships.
The authors used retrospective therapeutic drug monitoring data from the electronic health records of patients treated in a tertiary health care system from 2008 to 2014 to (1) develop a population pharmacokinetic (PK) model, (2) use the model to simulate sirolimus concentrations, and (3) characterize the exposure-response relationship. Using Wilcoxon rank-sum and Fisher exact tests, the authors determined relationships between sirolimus exposure and adverse events (AEs) (anemia, leukopenia, thrombocytopenia, hyperlipidemia, and decline in renal function) and the composite efficacy end point of graft loss or rejection.
The developed 2-compartment population PK model showed appropriate goodness of fit. In a late-phase (>12 months), postrenal transplant population of 27 inpatients, the authors identified statistically significant relationships between 83 simulated peak and trough sirolimus concentrations and outcomes: graft loss or rejection (P = 0.018) and decline in renal function (P = 0.006), respectively.
Use of therapeutic drug monitoring results and PK modeling permitted correlation of sirolimus concentrations with graft loss or rejection and decline in renal function. However, the method was limited in its assessment of other AEs. To better evaluate sirolimus exposure-response relationships, the method should be applied to a larger sample of newly transplanted patients with a higher propensity toward AEs or efficacy failure.
西罗莫司是一种用于肾移植的免疫抑制剂，可预防同种异体移植排斥反应。确定免疫抑制剂的治疗指数（最低中毒浓度与最低治疗浓度之比）对于优化患者护理和制定西罗莫司产品生物等效性评估标准至关重要。然而，西罗莫司的治疗指数定义并不一致，这可能是由于西罗莫司暴露-反应关系存在不一致性。
作者使用了2008年至2014年在三级医疗保健系统接受治疗的患者电子健康记录中的回顾性治疗药物监测数据，以（1）建立群体药代动力学（PK）模型，（2）使用该模型模拟西罗莫司浓度，以及（3）描述暴露-反应关系。作者使用Wilcoxon秩和检验和Fisher精确检验，确定了西罗莫司暴露与不良事件（贫血、白细胞减少、血小板减少、高脂血症和肾功能下降）以及移植失败或排斥反应的复合疗效终点之间的关系。
所建立的二室群体PK模型显示出良好的拟合度。在27名肾移植后期（>12个月）住院患者中，作者确定了83次模拟的西罗莫司峰浓度和谷浓度与结局之间具有统计学意义的关系：分别为移植失败或排斥反应（P = 0.018）和肾功能下降（P = 0.006）。
使用治疗药物监测结果和PK建模可使西罗莫司浓度与移植失败或排斥反应以及肾功能下降相关联。然而，该方法在评估其他不良事件方面存在局限性。为了更好地评估西罗莫司暴露-反应关系，该方法应应用于更大样本的新移植患者，这些患者发生不良事件或疗效失败的倾向更高。
