Tamoxifen is widely used in patients with hormone receptor-positive breast cancer. The polymorphic enzyme CYP2D6 is primarily responsible for metabolic activation of tamoxifen, resulting in substantial interindividual variability of plasma concentrations of its most important metabolite, Z-endoxifen. The Z-endoxifen concentration thresholds below which tamoxifen treatment is less efficacious have been proposed but not validated, and prospective trials of individualized tamoxifen treatment to achieve Z-endoxifen concentration thresholds are considered infeasible. Therefore, we aim to validate the association between Z-endoxifen concentration and tamoxifen treatment outcomes, and identify a Z-endoxifen concentration threshold of tamoxifen efficacy, using pharmacometric modeling and simulation. As a first step, the CYP2D6 Endoxifen Percentage Activity Model (CEPAM) cohort was created by pooling data from 28 clinical studies (> 7,000 patients) with measured endoxifen plasma concentrations. After cleaning, data from 6,083 patients were used to develop a nonlinear mixed-effect (NLME) model for tamoxifen and Z-endoxifen pharmacokinetics that includes a conversion factor to allow inclusion of studies that measured total endoxifen but not Z-endoxifen. The final parent-metabolite NLME model confirmed the primary role of CYP2D6, and contributions from body weight, CYP2C9 phenotype, and co-medication with CYP2D6 inhibitors, on Z-endoxifen pharmacokinetics. Future work will use the model to simulate Z-endoxifen concentrations in patients receiving single agent tamoxifen treatment within large prospective clinical trials with long-term survival to identify the Z-endoxifen concentration threshold below which tamoxifen is less efficacious. Identification of this concentration threshold would allow personalized tamoxifen treatment to improve outcomes in patients with hormone receptor-positive breast cancer.

中文翻译：

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CEPAM 队列中他莫昔芬治疗患者 Z-Endoxifen 浓度的非线性混合效应模型

他莫昔芬广泛用于激素受体阳性乳腺癌患者。多态性酶 CYP2D6 主要负责他莫昔芬的代谢激活，导致其最重要的代谢物 Z-内多昔芬血浆浓度存在显着的个体差异。已经提出了 Z-内多昔芬浓度阈值，低于该阈值，他莫昔芬治疗效果较差，但尚未得到验证，并且为达到 Z-内多昔芬浓度阈值而进行个体化他莫昔芬治疗的前瞻性试验被认为是不可行的。因此，我们的目的是使用药理学模型和模拟来验证 Z-内多昔芬浓度与他莫昔芬治疗结果之间的关联，并确定他莫昔芬疗效的 Z-内多昔芬浓度阈值。第一步，CYP2D6 内多昔芬百分比活性模型 (CEPAM) 队列是通过汇集 28 项临床研究（> 7,000 名患者）的数据并测量内多昔芬血浆浓度而创建的。清理后，来自 6,083 名患者的数据被用来开发他莫昔芬和 Z-endoxifen 药代动力学的非线性混合效应 (NLME) 模型，其中包括一个转换因子，以允许纳入测量总 endoxifen 但不测量 Z-endoxifen 的研究。最终的母体代谢物 NLME 模型证实了 CYP2D6 的主要作用，以及体重、CYP2C9 表型和 CYP2D6 抑制剂联合用药对 Z-endoxifen 药代动力学的贡献。未来的工作将使用该模型来模拟在大型前瞻性临床试验中接受单药他莫昔芬治疗的患者的 Z-内多昔芬浓度，并具有长期生存期，以确定 Z-内多昔芬浓度阈值，低于该阈值，他莫昔芬的疗效较差。确定该浓度阈值将使个性化他莫昔芬治疗能够改善激素受体阳性乳腺癌患者的预后。