Nonlinear Mixed‐Effects Model of Z‐Endoxifen Concentrations in Tamoxifen‐Treated Patients from the CEPAM Cohort

Abstract

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.