Department of Clinical Pharmacokinetics and Pharmacodynamics, Keio University School of Medicine, Tokyo, Japan.
Division of Thoracic Oncology, Shizuoka Cancer Center, Shizuoka, Japan.
Cancer Sci. 2018 Sep;109(9):2822-2829. doi: 10.1111/cas.13708. Epub 2018 Jul 23.
Postmarketing surveillance is useful to collect safety data in real-world clinical settings. In this study, we applied postmarketing real-world data on a mechanistic model analysis for neutropenic profiles of eribulin in patients with recurrent or metastatic breast cancer. Demographic and safety data were collected using an active surveillance method from eribulin-treated recurrent or metastatic breast cancer patients. Changes in neutrophil counts over time were analyzed using a mechanistic pharmacodynamic model. Pathophysiological factors that might affect the severity of neutropenia were investigated, and neutropenic patterns were simulated for different treatment schedules. Clinical and laboratory data were collected from 401 patients (5199 neutrophil count measurements) who had not received granulocyte colony-stimulating factor and were eligible for pharmacodynamic analysis. The estimated mean parameters were as follows: mean transit time = 104.5 h, neutrophil proliferation rate constant = 0.0377 h , neutrophil elimination rate constant = 0.0295 h , and linear coefficient of drug effect = 0.0413 mL/ng. Low serum albumin levels and low baseline neutrophil counts were associated with severe neutropenia. The probability of grade ≥3 neutropenia was predicted to be 69%, 27%, and 27% for patients on standard, biweekly, and triweekly treatment scenarios, respectively, based on virtual simulations using the developed pharmacodynamic model. In conclusion, this is the first application of postmarketing surveillance data to a model-based safety analysis. This analysis of safety data reflecting authentic clinical settings will provide useful information on the safe use and potential risk factors of eribulin.
上市后监测有助于在真实临床环境中收集安全性数据。在这项研究中,我们应用上市后真实世界数据,对在接受艾日布林治疗的复发性或转移性乳腺癌患者中进行中性粒细胞减少症的机制模型分析。使用主动监测方法收集了来自接受艾日布林治疗的复发性或转移性乳腺癌患者的人口统计学和安全性数据。使用机制药效动力学模型分析了中性粒细胞计数随时间的变化。研究了可能影响中性粒细胞减少症严重程度的生理病理因素,并对不同治疗方案的中性粒细胞减少模式进行了模拟。对未接受粒细胞集落刺激因子治疗且符合药效学分析条件的 401 名患者(5199 次中性粒细胞计数测量值)的临床和实验室数据进行了收集。估计的平均参数如下:平均转运时间=104.5 小时,中性粒细胞增殖速率常数=0.0377 小时,中性粒细胞消除速率常数=0.0295 小时,药物效应线性系数=0.0413 毫升/ng。低血清白蛋白水平和低基线中性粒细胞计数与严重中性粒细胞减少症相关。基于使用开发的药效动力学模型进行的虚拟模拟,预测标准、每两周和每三周治疗方案的患者发生 3 级及以上中性粒细胞减少症的概率分别为 69%、27%和 27%。总之,这是首次将上市后监测数据应用于基于模型的安全性分析。对反映真实临床环境的安全性数据进行分析,将为艾日布林的安全使用和潜在风险因素提供有用信息。