Toward model-informed precision dosing for tamoxifen: A population-pharmacokinetic model with a continuous CYP2D6 activity scale

Effects of tamoxifen on cognitive function in patients with primary breast cancer

INTRODUCTION

Tamoxifen may adversely affect cognitive function by interfering with estrogen action in the brain. Despite growing evidence for a relationship between tamoxifen and cognitive problems, findings remain inconclusive. While some tamoxifen-related side effects seem exposure-dependent with concentrations of tamoxifen or its main metabolite, endoxifen, this has never been investigated for cognitive function. We investigated cognitive function after two years of tamoxifen and its association with tamoxifen and endoxifen exposure.

METHODS

135 women with breast cancer completed the Amsterdam Cognition Scan (ACS), an online neuropsychological test battery, after two years of tamoxifen. Test scores were converted to standardized Z-scores based on a matched 'no-cancer' control group. Tamoxifen and endoxifen concentrations and tamoxifen dose were regressed separately on cognitive functioning.

RESULTS

Patients reported mild cognitive complaints and had worse verbal learning, processing speed, executive functioning, and motor functioning compared to matched controls. After correcting for age, mean tamoxifen and endoxifen levels, as well as tamoxifen dose, were associated with worse performance on several cognitive domains.

CONCLUSION

Tamoxifen is adversely associated with objective as well as self-reported cognitive function, which may depend on the level of exposure to tamoxifen and endoxifen. Further research is warranted to confirm this hypothesis.

Implementation of model-informed precision dosing for tamoxifen therapy in patients with breast cancer: A prospective intervention study

Tamoxifen is an estrogen-receptor (ER) antagonist, used as adjuvant treatment of ER-positive breast cancer. It is converted by CYP2D6 into endoxifen, its most active metabolite. Patients with endoxifen plasma concentrations <16 nM face a higher risk of recurrence. The use of a priori model-informed precision dosing (MIPD) may lead to faster target attainment and thus potentially improve patient outcomes. In total, 106 evaluable patients were prospectively included in this single-arm MIPD-intervention study. Patients received a model-predicted tamoxifen dose when starting tamoxifen-treatment (65.1 % of patients received 20 mg, 16.0 % received 30 mg and 18.9 % received 40 mg). Seventy-five percent of the 40 mg group was predicted to be unable to reach the threshold of 16 nM despite receiving the highest registered dose. After attaining steady-state, 84.0 % of patients reached endoxifen levels ≥16 nM, which was not significantly higher compared to a historical control cohort (77.9 %, p = 0.17). The model showed adequate performance and correctly identified patients requiring 40 mg tamoxifen. Endoxifen samples that were acquired 4-6 weeks after treatment initiation, are informative of steady-state endoxifen levels and can be used to inform MIPD and adjust tamoxifen dosing prior to steady-state attainment. In this first MIPD implementation study for patients treated with tamoxifen, MIPD did lead to more patients achieving endoxifen levels ≥16 nM as compared to the one-dose-fits-all strategy, albeit insignificant. This may partly be explained by a larger proportion of patients who were recommended to switch to an aromatase inhibitor (AI) in the intervention cohort. In conclusion, MIPD seems beneficial compared to one-size-fits-all-dosing, but TDM still remains an important addition.

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

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.

Pharmacogenetic Testing or Therapeutic Drug Monitoring: A Quantitative Framework

BACKGROUND

Pharmacogenetic profiling and therapeutic drug monitoring (TDM) have both been proposed to manage inter-individual variability (IIV) in drug exposure. However, determining the most effective approach for estimating exposure for a particular drug remains a challenge. This study aimed to quantitatively assess the circumstances in which pharmacogenetic profiling may outperform TDM in estimating drug exposure, under three sources of variability (IIV, inter-occasion variability [IOV], and residual unexplained variability [RUV]).

METHODS

Pharmacokinetic models were selected from the literature corresponding to drugs for which pharmacogenetic profiling and TDM are both clinically considered approaches for dose individualization. The models were used to simulate relevant drug exposures (trough concentration or area under the curve [AUC]) under varying degrees of IIV, IOV, and RUV.

RESULTS

Six drug cases were selected from the literature. Model-based simulations demonstrated that the percentage of patients for whom pharmacogenetic exposure prediction is superior to TDM differs for each drug case: tacrolimus (11.0%), tamoxifen (12.7%), efavirenz (49.2%), vincristine (49.6%), risperidone (48.1%), and 5-fluorouracil (5-FU) (100%). Generally, in the presence of higher unexplained IIV in combination with lower RUV and IOV, exposure was best estimated by TDM, whereas, under lower unexplained IIV in combination with higher IOV or RUV, pharmacogenetic profiling was preferred.

CONCLUSIONS

For the drugs with relatively low RUV and IOV (e.g., tamoxifen and tacrolimus), TDM estimated true exposure the best. Conversely, for drugs with similar or lower unexplained IIV (e.g., efavirenz or 5-FU, respectively) combined with relatively high RUV, pharmacogenetic profiling provided the most accurate estimate for most patients. However, genotype prevalence and the relative influence of genotypes on the PK, as well as the ability of TDM to accurately estimate AUC with a limited number of samples, had an impact. The results could be used to support clinical decision making when considering other factors, such as the probability for severe side effects.

The interplay between tamoxifen and endoxifen plasma concentrations and coagulation parameters in patients with primary breast cancer

BACKGROUND

Tamoxifen is an effective treatment for primary breast cancer but increases the risk for venous thromboembolism. Tamoxifen decreases anticoagulant proteins, including antithrombin (AT), protein C (PC) and tissue factor (TF) pathway inhibitor, and enhances thrombin generation (TG). However, the relation between plasma concentrations of both tamoxifen and its active metabolite endoxifen and coagulation remains unknown.

METHODS

Tamoxifen and endoxifen were measured in 141 patients from the prospective open-label intervention TOTAM-study after 3 months (m) and 6 m of tamoxifen treatment. Levels of AT and PC, the procoagulant TF, and TG parameters were determined at both timepoints if samples were available (n = 53-135 per analysis). Levels of coagulation proteins and TG parameters were correlated and compared between: 1) quartiles of tamoxifen and endoxifen levels, and 2) 3 m and 6 m of treatment.

RESULTS

At 3 m, levels of AT, PC, TF and TG parameters were not associated with tamoxifen nor endoxifen levels. At 6 m, median TF levels were lower in patients in the 3rd (56.6 [33] pg/mL), and 4th (50.1 [19] pg/mL) endoxifen quartiles compared to the 1st (lowest) quartile (76 [69] pg/mL) (P=0.027 and P=0.018, respectively), but no differences in anticoagulant proteins or TG parameters were observed. An increase in circulating TF levels (3 m: 46.0 [15] versus 6 m: 54.4 [39] pg/mL, P < 0.001) and TG parameters was observed at the 6 m treatment timepoint, while AT and PC levels remained stable.

CONCLUSIONS

Our results indicate that higher tamoxifen and endoxifen levels are not correlated with an increased procoagulant state, suggesting tamoxifen dose escalation does not further promote hypercoagulability.