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 &lt; 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.</p

Defective Connective Tissue Remodeling in Smad3 Mice Leads to Accelerated Aneurysmal Growth Through Disturbed Downstream TGF-β Signaling

Aneurysm-osteoarthritis syndrome characterized by unpredictable aortic aneurysm formation, is caused by SMAD3 mutations. SMAD3 is part of the SMAD2/3/4 transcription factor, essential for TGF-β-activated transcription. Although TGF-β-related gene mutations result in aneurysms, the underlying mechanism is unknown. Here, we examined aneurysm formation and progression in Smad3−/− animals. Smad3−/− animals developed aortic aneurysms rapidly, resulting in premature death. Aortic wall immunohistochemistry showed no increase in extracellular matrix and collagen accumulation, nor loss of vascular smooth muscle cells (VSMCs) but instead revealed medial elastin disruption and adventitial inflammation. Remarkably, matrix metalloproteases (MMPs) were not activated in VSMCs, but rather specifically in inflammatory areas. Although Smad3−/− aortas showed increased nuclear pSmad2 and pErk, indicating TGF-β receptor activation, downstream TGF-β-activated target genes were not upregulated. Increased pSmad2 and pErk staining in pre-aneurysmal Smad3−/− aortas implied that aortic damage and TGF-β receptor-activated signaling precede aortic inflammation. Finally, impaired downstream TGF-β activated transcription resulted in increased Smad3−/− VSMC proliferation. Smad3 deficiency leads to imbalanced activation of downstream genes, no activation of MMPs in VSMCs, and immune responses resulting in rapid aortic wall dilatation and rupture. Our findings uncover new possibil

Cost-Effectiveness Analysis of MammaPrint® to Guide the Use of Endocrine Therapy in Patients with Early-Stage Breast Cancer

Background: Gene expression profiling tests can predict the risk of disease recurrence and select patients who are expected to benefit from therapy, while allowing other patients to forgo therapy. For breast cancers, these tests were initially designed to tailor chemotherapy decisions, but recent evidence suggests that they may also guide the use of endocrine therapy. This study evaluated the cost effectiveness of a prognostic test, MammaPrint®, to guide the use of adjuvant endocrine therapy in patients eligible according to Dutch treatment guidelines. Methods: We constructed a Markov decision model to calculate the lifetime costs (in 2020 Euros) and effects (survival and quality-adjusted life-years) of MammaPrint® testing versus usual care (endocrine therapy for all patients) in a simulated cohort of patients. The population of interest includes patients for whom MammaPrint® testing is currently not indicated, but for whom it may be possible to safely omit endocrine therapy. We applied both a health care perspective and a societal perspective and discounted costs (4%) and effects (1.5%). Model inputs were obtained from published research (including randomized controlled trials), nationwide cancer registry data, cohort data and publicly available data sources. Scenario and sensitivity analyses were conducted to explore the impact of uncertainty around input parameters. Additionally, threshold analyses were performed to identify under which circumstances MammaPrint® testing would be cost effective. Results: Adjuvant endocrine therapy guided by MammaPrint® resulted in fewer side effects, more (quality-adjusted) life-years (0.10 and 0.07 incremental QALYS and LYs, respectively) and higher costs (€18,323 incremental costs) compared with the usual care strategy in which all patients receive endocrine therapy. While costs for hospital visits, medication costs and productivity costs were somewhat higher in the usual care strategy, these did not outweigh costs of testing in the MammaPrint® strategy. The incremental cost-effectiveness ratio was €185,644 per QALY gained from a healthcare perspective and €180,617 from a societal perspective. Sensitivity and scenario analyses showed that the conclusions remained the same under changed input parameters and assumptions. Our results show that MammaPrint® can become a cost-effective strategy when either the price of the test is reduced (> 50%), or the proportion of patients for which treatment is altered (i.e. those with ultra-low risk) increases to > 26%. Conclusion: Standard MammaPrint® testing to guide the use of endocrine therapy in our simulated patient population appears not to be a cost-effective strategy compared with usual care. The cost effectiveness of the test can be improved by reducing the price or preselecting a population more likely to benefit from the test

Factors affecting inter-individual variability in endoxifen concentrations in patients with breast cancer: results from the prospective TOTAM trial

Introduction: Endoxifen—the principal metabolite of tamoxifen—is subject to a high inter-individual variability in serum concentration. Numerous attempts have been made to explain this, but thus far only with limited success. By applying predictive modeling, we aimed to identify factors that determine the inter-individual variability. Our purpose was to develop a prediction model for endoxifen concentrations, as a strategy to individualize tamoxifen treatment by model-informed dosing in order to prevent subtherapeutic exposure (endoxifen < 16 nmol/L) and thus potential failure of therapy. Methods: Tamoxifen pharmacokinetics with demographic and pharmacogenetic data of 303 participants of the prospective TOTAM study were used. The inter-individual variability in endoxifen was analyzed according to multiple regression techniques in combination with multiple imputations to adjust for missing data and bootstrapping to adjust for the over-optimism of parameter estimates used for internal model validation. Results: Key predictors of endoxifen concentration were CYP2D6 genotype, age and weight, explaining altogether an average-based optimism corrected 57% (95% CI 0.49–0.64) of the inter-individual variability. CYP2D6 genotype explained 54% of the variability. The remaining 3% could be explained by age and weight. Predictors of risk for subtherapeutic endoxifen (< 16 nmol/L) were CYP2D6 genotype and age. The model showed an optimism-corrected discrimination of 90% (95% CI 0.86–0.95) and sensitivity and specificity of 66% and 98%, respectively. Consecutively, there is a high probability of misclassifying patients with subtherapeutic endoxifen concentrations based on the prediction rule. Conclusion: The inter-individual variability of endoxifen concentration could largely be explained by CYP2D6 genotype and for a small proportion by age and weight. The model showed a sensitivity and specificity of 66 and 98%, respectively, indicating a high probability of (misclassification) error for the patients with subtherapeutic endoxifen concentrations (< 16 nmol/L). The remaining unexplained inter-individual variability is still high and therefore model-informed tamoxifen dosing should be accompanied by therapeutic drug monitoring

A neonate with a unique non-Down syndrome transient proliferative megakaryoblastic disease

Transient myeloproliferative disorder (TMD) is a leukemia type that occurs typically in newborns. In Down syndrome, TMD is referred to as transient abnormal myelopoiesis (TAM).(32) Recently, transientness has also been reported in acute myeloid leukemia patients with germline trisomy 21 mosaicism, and even in cases with somatic trisomy 21, with or without GATA1 mutations. TMD cases without trisomy 21 are rare, and recurrent genetic aberrations that aid in clinical decision-making are scarcely described. We describe here a TMD patient without trisomy 21 or GATA1 mutation in whom single-nucleotide polymorphism analysis of leukemic blasts revealed a novel combined submicroscopic deletion (5q31.1-5q31.3 and 8q23.2q24)

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

BACKGROUND: Tamoxifen is important in the adjuvant treatment of breast cancer. A plasma concentration of the active metabolite endoxifen of > 16 nM is associated with a lower risk of breast cancer-recurrence. Since inter-individual variability is high and > 20 % of patients do not reach endoxifen levels > 16 nM with the standard dose tamoxifen, therapeutic drug monitoring is advised. However, ideally, the correct tamoxifen dose should be known prior to start of therapy. Our aim is to develop a population pharmacokinetic (POP-PK) model incorporating a continuous CYP2D6 activity scale to support model informed precision dosing (MIPD) of tamoxifen to determine the optimal tamoxifen starting dose. METHODS: Data from eight different clinical studies were pooled (539 patients, 3661 samples) and used to develop a POP-PK model. In this model, CYP2D6 activity per allele was estimated on a continuous scale. After inclusion of covariates, the model was subsequently validated using an independent external dataset (378 patients). Thereafter, dosing cut-off values for MIPD were determined. RESULTS: A joint tamoxifen/endoxifen POP-PK model was developed describing the endoxifen formation rate. Using a continuous CYP2D6 activity scale, variability in predicting endoxifen levels was decreased by 37 % compared to using standard CYP2D6 genotype predicted phenotyping. After external validation and determination of dosing cut-off points, MIPD could reduce the proportion of patients with subtherapeutic endoxifen levels at from 22.1 % toward 4.8 %. CONCLUSION: Implementing MIPD from the start of tamoxifen treatment with this POP-PK model can reduce the proportion of patients with subtherapeutic endoxifen levels at steady-state to less than 5 %