Abstract
IntroductionAt tamoxifen standard dosing, ∼20% of breast cancer patients do not reach proposed target endoxifen concentrations >5.97 ng/mL. Thus, better understanding the large interindividual variability in tamoxifen pharmacokinetics (PK) is crucial. By applying non-linear mixed-effects (NLME) modeling to a pooled ‘real-world’ clinical PK database, we aimed to (i) dissect several levels of variability and identify factors predictive for endoxifen exposure and (ii) assess different tamoxifen dosing strategies for their potential to increase the number of patients reaching target endoxifen concentrations.MethodsTamoxifen and endoxifen concentrations with genetic and demographic data of 468 breast cancer patients from six reported studies were used to develop a NLME parent-metabolite PK model. Different levels of variability on model parameters or measurements were investigated and the impact of covariates thereupon explored. The model was subsequently applied in a simulation-based comparison of three dosing strategies with increasing degree of dose individualization for a large virtual breast cancer population. Interindividual variability of endoxifen concentrations and the fraction of patients at risk for not reaching target concentrations were assessed for each dosing strategy.Results and ConclusionsThe integrated NLME model enabled to differentiate and quantify four levels of variability (interstudy, interindividual, interoccasion, and intraindividual). Strong influential factors, i.e., CYP2D6 activity score, drug–drug interactions with CYP3A and CYP2D6 inducers/inhibitors and age, were reliably identified, reducing interoccasion variability to <20% CV. Yet, unexplained interindividual variability in endoxifen formation remained large (47.2% CV). Hence, therapeutic drug monitoring seems promising for achieving endoxifen target concentrations. Three tamoxifen dosing strategies [standard dosing (20 mg QD), CYP2D6-guided dosing (20, 40, and 60 mg QD) and individual model-informed precision dosing (MIPD)] using three therapeutic drug monitoring samples (5–120 mg QD) were compared, leveraging the model. The proportion of patients at risk for not reaching target concentrations was 22.2% in standard dosing, 16.0% in CYP2D6-guided dosing and 7.19% in MIPD. While in CYP2D6-guided- and standard dosing interindividual variability in endoxifen concentrations was high (64.0% CV and 68.1% CV, respectively), it was considerably reduced in MIPD (24.0% CV). Hence, MIPD demonstrated to be the most promising strategy for achieving target endoxifen concentrations.
Highlights
At tamoxifen standard dosing, ∼20% of breast cancer patients do not reach proposed target endoxifen concentrations >5.97 ng/mL
High interindividual variability is observed in the PK of tamoxifen – and especially its active metabolite endoxifen – after standard doses of 20 mg tamoxifen once daily (QD)
The in silico approach further allows to study scenarios which would be challenging and/or time consuming to observe in ‘reallife,’ due to the rareness of subpopulations (i.e., CYP2D6 poor metabolizer) or ethical concerns. Based on this status quo, the aim of this work was (i) to enhance the quantitative understanding of the highly variable pharmacokinetics and pharmacogenetics of tamoxifen and its major active metabolite endoxifen and (ii) to investigate intrinsic and extrinsic factors causing subtarget endoxifen plasma concentrations in order (iii) to propose a possible clinical trial design [i.e., how many therapeutic drug monitoring (TDM) samples should be taken and when] to evaluate the clinical benefit of model-informed precision dosing of tamoxifen
Summary
At tamoxifen standard dosing, ∼20% of breast cancer patients do not reach proposed target endoxifen concentrations >5.97 ng/mL. High interindividual variability is observed in the PK of tamoxifen – and especially its active metabolite endoxifen – after standard doses of 20 mg tamoxifen once daily (QD). This variability has been partly attributed to genetic variations in the metabolizing enzyme CYP2D6 (Schroth et al, 2007; Mürdter et al, 2011; Ratain et al, 2013; Ter Heine et al, 2014). Several clinical studies on tamoxifen treatment individualization have shown controversial results (Goetz et al, 2005; Barginear et al, 2011; Irvin et al, 2011; Regan et al, 2012; Martinez et al, 2014; Dezentjé et al, 2015; Welzen et al, 2015; Hertz et al, 2016; DeCensi et al, 2019; Khalaj et al, 2019) and caused intensive debates (Hoskins et al, 2009; Lash et al, 2009; Brauch et al, 2013; Binkhorst et al, 2015b)
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