Drug Interactions With Tamoxifen and Treatment Effectiveness in Premenopausal Breast Cancer Patients: A Bayesian Joint Modeling Approach
ABSTRACT Purpose Tamoxifen is guideline treatment for premenopausal women with estrogen receptor‐positive (ER+) breast cancer. Therapeutic efficacy relies partly on tamoxifen biotransformation by CYP2D6, CYP2C19, and CYP3A4 enzymes. We conducted a cohort study to evaluate whether concomitant prescri...
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Published in | Pharmacoepidemiology and drug safety Vol. 34; no. 5; pp. e70157 - n/a |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Inc
01.05.2025
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1053-8569 1099-1557 1099-1557 |
DOI | 10.1002/pds.70157 |
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Summary: | ABSTRACT
Purpose
Tamoxifen is guideline treatment for premenopausal women with estrogen receptor‐positive (ER+) breast cancer. Therapeutic efficacy relies partly on tamoxifen biotransformation by CYP2D6, CYP2C19, and CYP3A4 enzymes. We conducted a cohort study to evaluate whether concomitant prescription of drugs that inhibit these enzymes impacted breast cancer recurrence.
Methods
We enrolled 4493 premenopausal women with stage I–III ER+ breast cancer (2002–2011) treated with tamoxifen. We defined time‐varying CYP‐inhibiting drug exposures as the proportion of overlapping days during the tamoxifen treatment period. We estimated associations of concomitant medication use with recurrence using: (1) Bayesian joint modeling (hazard ratio [HR] and 95% credible intervals [95% CrI]), (2) traditional Cox regression (HR and 95% confidence intervals [95% CI]).
Results
During tamoxifen therapy, 13% of the cohort used strong CYP2D6 inhibitors, 31% weak CYP2D6 inhibitors, 37% CYP2C19 inhibitors, and 12% CYP3A4/5 inhibitors. Bayesian joint models showed that women with ≥ 50% overlap between tamoxifen and CYP2D6 inhibitors had increased recurrence risk compared with 0% overlap (HR: 1.24, 95% CrI: 0.96, 1.58). No recurrence association was seen for CYP2C19 inhibitors (≥ 50% vs. 0%, HR = 1.0, 95% CrI: 0.69, 1.40), but traditional Cox models yielded positive associations for CYP2C19 overlap (≥ 50% vs. 0%, HR = 1.45, 95% CI: 1.07, 1.96). With Bayesian joint models, we observed no association between ≥ 50% versus 0% overlap with CYP3A4/5 inhibitors (HR: 0.84, 95% CrI: 0.32, 1.93).
Conclusions
With Bayesian joint modeling, we saw a slight increase in recurrence among CYP2D6‐inhibitor users, but no increase among CYP2C19‐ or CYP3A4‐inhibitor users. Results from Cox regression models were less plausible. |
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Bibliography: | Funding This work was supported by an award from the US National Cancer Institute (R01 CA166825; PI: Lash), the Program for Clinical Research Infrastructure (PROCRIN), established by the Lundbeck Foundation and the Novo Nordisk Foundation (HTS), the Lundbeck Foundation (R167‐2013‐15861) (DCF), and the Independent Research Fund Denmark, Medicine (DFF‐1030‐00052B) (DCF). Thomas Ahern was supported by a Career Catalyst Award from Susan G. Komen for the Cure (CCR13264024), by the Mary Kay Foundation (003‐14), and by the US National Institute for General Medical Sciences (P20GM103644). Lindsay J. Collin was supported by K99CA277580 from the National Cancer Institute of the National Institutes of Health. Findings from this study were presented, in part, at the International Congress for Pharmacoepidemiology 2022 annual meeting in Copenhagen, Denmark. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Funding: This work was supported by an award from the US National Cancer Institute (R01 CA166825; PI: Lash), the Program for Clinical Research Infrastructure (PROCRIN), established by the Lundbeck Foundation and the Novo Nordisk Foundation (HTS), the Lundbeck Foundation (R167‐2013‐15861) (DCF), and the Independent Research Fund Denmark, Medicine (DFF‐1030‐00052B) (DCF). Thomas Ahern was supported by a Career Catalyst Award from Susan G. Komen for the Cure (CCR13264024), by the Mary Kay Foundation (003‐14), and by the US National Institute for General Medical Sciences (P20GM103644). Lindsay J. Collin was supported by K99CA277580 from the National Cancer Institute of the National Institutes of Health. Findings from this study were presented, in part, at the International Congress for Pharmacoepidemiology 2022 annual meeting in Copenhagen, Denmark. |
ISSN: | 1053-8569 1099-1557 1099-1557 |
DOI: | 10.1002/pds.70157 |