Evidence map›Paper›PMID 40364655›Full record

ArticlePharmacoepidemiology and drug safety2025

Drug Interactions With Tamoxifen and Treatment Effectiveness in Premenopausal Breast Cancer Patients: A Bayesian Joint Modeling Approach.

Kirsten M Woolpert, Deirdre P Cronin-Fenton, Per Damkier, Anders Kjærsgaard, Stephen Hamilton-Dutoit, Bent Ejlertsen, Richard F MacLehose, Peer Christiansen, Rebecca A Silliman, Timothy L Lash and 2 more

Abstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Kirsten M WoolpertDepartment of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.
Deirdre P Cronin-FentonDepartment of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.
Per DamkierDepartment of Clinical Pharmacology, Odense University Hospital, Odense, Denmark.ORCID https://orcid.org/0000-0003-0591-7187
Anders KjærsgaardDepartment of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.
Stephen Hamilton-DutoitDepartment of Pathology, Aarhus University Hospital, Aarhus, Denmark.
Bent EjlertsenDanish Breast Cancer Group, Department of Oncology, Rigshospitalet, Copenhagen, Denmark.
Richard F MacLehoseDivision of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA.
Peer ChristiansenDanish Breast Cancer Group, Department of Oncology, Rigshospitalet, Copenhagen, Denmark.
Rebecca A SillimanSection of Geriatrics, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA.
Timothy L LashDepartment of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.
Thomas P AhernDepartment of Surgery, The Robert Larner, M.D., College of Medicine at the University of Vermont, Burlington, Vermont, USA.
Lindsay J CollinDepartment of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.

Funding

Identifying factors associated with ovarian cancer recurrence using a population-based approachR00CA277580 · NCI · EMORY UNIVERSITY · PI Lindsay Jane Collin · 2025 to 2026
$457k
Danmarks Frie ForskningsfondLundbeck FoundationMary Kay Ash FoundationNCI NIH HHS R00 CA277580Susan G. Komen for the CureUS National Institute for General Medical Sciences
6 · The paper itself

Abstract

purposeTamoxifen 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.

methodsWe 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]).

resultsDuring 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).

conclusionsWith 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.

Indexed as

Antineoplastic Agents, HormonalBreast NeoplasmsTamoxifenAdultBayes TheoremCohort StudiesDrug InteractionsFemaleHumansMiddle AgedNeoplasm Recurrence, LocalPremenopauseTreatment OutcomeAntineoplastic Agents, HormonalTamoxifenbreast neoplasmsdrug interactionsjoint modelingpharmacoepidemiologytamoxifen

Identifiers

PMID40364655
PMCPMC12076038

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.