Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Kelchstr. 31, 12169, Berlin, Germany.
Department of Medical Oncology and Haematology, Cantonal Hospital, St. Gallen, Switzerland.
Clin Pharmacokinet. 2018 Feb;57(2):229-242. doi: 10.1007/s40262-017-0555-z.
A better understanding of the highly variable pharmacokinetics (PK) of tamoxifen and its active metabolite endoxifen in breast cancer patients is crucial to support individualised treatment. This study used a modelling and simulation approach to quantitatively assess the influence of cytochrome P450 (CYP) 2D6 activity and other relevant factors on tamoxifen and endoxifen PK to identify subgroups at risk for subtherapeutic endoxifen concentrations.
Simulations were performed using two previously published PK models jointly describing tamoxifen and endoxifen with CYP2D6 and CYP3A4/5 enzyme activities implemented as covariates. Steady-state predictions were compared between models and with the literature values. Factors potentially causing between-model discrepancies were explored. A previously published threshold (6 ng/mL) was used to identify patients with subtherapeutic endoxifen concentrations and to perform a dose adaptation study.
Steady-state predictions of tamoxifen and endoxifen were considerably different between the models. The factors, differences in sampling time, adherence and bioavailability, were not able to fully capture between-model variability. Endoxifen steady-state fluctuations within a dosing interval were minimal (<6%). Poor (97%) and intermediate (54%) CYP2D6 metabolisers failed to achieve therapeutic endoxifen concentrations, suggesting adapted doses of tamoxifen 80 and 40 mg, respectively, achieving therapeutic endoxifen concentrations in 89.7% of patients (standard dosing 45.2%). However, interindividual variability remained.
To achieve therapeutic endoxifen concentrations early in treatment, it is advisable to initiate treatment by CYP2D6 genotype/phenotype-guided dosing, followed by therapeutic drug monitoring at steady-state. We strongly advocate to adequately measure, report and prospectively investigate influential factors (i.e. adherence, bioavailability, time to PK steady-state) in clinical trials.
更好地了解乳腺癌患者中他莫昔芬及其活性代谢物依西美坦的高度可变药代动力学（PK）对于支持个体化治疗至关重要。本研究采用建模和模拟方法定量评估细胞色素 P450（CYP）2D6 活性和其他相关因素对他莫昔芬和依西美坦 PK 的影响，以确定治疗效果不佳的依西美坦浓度的风险亚组。
使用两个先前发表的 PK 模型联合描述他莫昔芬和依西美坦，将 CYP2D6 和 CYP3A4/5 酶活性作为协变量进行模拟。比较了模型之间和文献值的稳态预测。探讨了导致模型之间差异的潜在因素。使用先前发表的阈值（6ng/mL）来识别治疗效果不佳的依西美坦浓度的患者，并进行剂量调整研究。
模型之间的稳态预测他莫昔芬和依西美坦的差异很大。采样时间、依从性和生物利用度等因素无法完全捕捉模型之间的变异性。在一个给药间隔内依西美坦的稳态波动很小（<6%）。不良（97%）和中间（54%）CYP2D6 代谢物患者未能达到治疗性依西美坦浓度，分别建议调整他莫昔芬剂量为 80mg 和 40mg，分别有 89.7%的患者（标准剂量 45.2%）达到治疗性依西美坦浓度。然而，个体间的变异性仍然存在。
为了在治疗早期达到治疗性依西美坦浓度，建议根据 CYP2D6 基因型/表型指导剂量开始治疗，然后在稳态时进行治疗药物监测。我们强烈主张在临床试验中充分测量、报告和前瞻性研究有影响的因素（即依从性、生物利用度、达到 PK 稳态的时间）。
