Schindler E, Amantea M A, Karlsson M O, Friberg L E
Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Pfizer Inc, La Jolla, California, USA.
CPT Pharmacometrics Syst Pharmacol. 2017 Jun;6(6):373-382. doi: 10.1002/psp4.12193. Epub 2017 May 26.
The relationships between exposure, biomarkers (vascular endothelial growth factor (VEGF), soluble VEGF receptors (sVEGFR)-1, -2, -3, and soluble stem cell factor receptor (sKIT)), tumor sum of longest diameters (SLD), diastolic blood pressure (dBP), and overall survival (OS) were investigated in a modeling framework. The dataset included 64 metastatic renal cell carcinoma patients (mRCC) treated with oral axitinib. Biomarker timecourses were described by indirect response (IDR) models where axitinib inhibits sVEGFR-1, -2, and -3 production, and VEGF degradation. No effect was identified on sKIT. A tumor model using sVEGFR-3 dynamics as driver predicted SLD data well. An IDR model, with axitinib exposure stimulating the response, characterized dBP increase. In a time-to-event model the SLD timecourse predicted OS better than exposure, biomarker- or dBP-related metrics. This type of framework can be used to relate pharmacokinetics, efficacy, and safety to long-term clinical outcome in mRCC patients treated with VEGFR inhibitors. (ClinicalTrial.gov identifier NCT00569946.).
在一个建模框架中研究了暴露、生物标志物(血管内皮生长因子(VEGF)、可溶性VEGF受体(sVEGFR)-1、-2、-3和可溶性干细胞因子受体(sKIT))、肿瘤最长径总和(SLD)、舒张压(dBP)与总生存期(OS)之间的关系。该数据集包括64例接受口服阿昔替尼治疗的转移性肾细胞癌患者(mRCC)。生物标志物的时间进程由间接反应(IDR)模型描述,其中阿昔替尼抑制sVEGFR-1、-2和-3的产生以及VEGF的降解。未发现对sKIT有影响。一个以sVEGFR-3动态变化为驱动因素的肿瘤模型对SLD数据预测良好。一个IDR模型,其中阿昔替尼暴露刺激反应,描述了dBP升高。在一个事件发生时间模型中,SLD时间进程比暴露、生物标志物或dBP相关指标能更好地预测OS。这种类型的框架可用于将接受VEGFR抑制剂治疗的mRCC患者的药代动力学、疗效和安全性与长期临床结局联系起来。(ClinicalTrial.gov标识符NCT00569946。)