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Hemorrhage Risk Among Patients With Breast Cancer Receiving Concurrent Direct Oral Anticoagulants With Tamoxifen vs Aromatase Inhibitors

2022· article· en· W4283694425 on OpenAlexafffundabout
Tzu‐Fei Wang, Anna E. Clarke, Arif Awan, Peter Tanuseputro, Marc Carrier, Manish M. Sood

Bibliographic record

VenueJAMA Network Open · 2022
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsBruyèreUniversity of OttawaOttawa Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineTamoxifenBreast cancerInternal medicineApixabanRivaroxabanRetrospective cohort studyPopulationCancerAromatase inhibitorOncologyWarfarinAtrial fibrillation

Abstract

fetched live from OpenAlex

Importance: Tamoxifen is commonly used as adjuvant therapy in breast cancer and is proposed to interfere with cytochrome P450 enzyme and P-glycoprotein pathways. Concurrent use with direct oral anticoagulants (DOACs) poses the threat of a potentially dangerous drug-drug interaction by leading to an increase in hemorrhage risk. Objective: To assess the risk of hemorrhage in patients with breast cancer coprescribed a DOAC and tamoxifen compared with a DOAC and an aromatase inhibitor (AI). Design, Setting, and Participants: This population-based, retrospective cohort study was conducted among adults aged 66 years or older who were prescribed tamoxifen (compared with an AI) concurrently with a DOAC in Ontario, Canada, between June 23, 2009, and November 30, 2020, and followed up until December 31, 2020. Interventions: Concurrent prescription of a DOAC and tamoxifen compared with a DOAC and an AI. Main Outcomes and Measures: The primary outcome was major hemorrhage requiring an emergency department visit or hospitalization after prescription. Overlap weighted Cox proportional hazards models, accounting for multiple covariates, were used to assess the association between hemorrhage and tamoxifen or AI use with a DOAC. Results: Among a total of 4753 patients (4679 [98.4%] women; mean [SD] age, 77.4 [7.4] years), 1179 (24.8%) were prescribed tamoxifen, and 3574 (75.2%) were prescribed an AI. Rivaroxaban (2530 [53.2%]) and apixaban (1665 [35.0%]) were the most frequently used DOACs. Patients taking AIs were younger than patients taking tamoxifen (mean [SD] age, 77.1 [7.3] vs 78.3 [7.6] years), with higher Charlson Comorbidity Index (mean [SD], 1.8 [2.4] vs 1.5 [2.2]) and more advanced cancer stage (stages III and IV, 569 [15.9%] vs 127 [10.8%]). During a median follow-up of 166 days (IQR, 111-527 days), tamoxifen was not associated with a higher risk of major hemorrhage (29 of 1179 [2.5%]) compared with an AI (119 of 3574 [3.3%]) when combined with a DOAC (absolute risk difference, -0.8%; weighted hazard ratio, 0.68 [95% CI, 0.44-1.06]). These results were similar in additional analyses using a more liberal definition of hemorrhage, accounting for kidney function, limiting follow-up to 90 days, stratifying by incident and prevalent DOAC users, and accounting for cancer duration and the competing risk of death. Conclusions and Relevance: In this cohort study, findings suggest that among DOAC users, the concurrent use of tamoxifen was not associated with a higher risk of hemorrhage compared with the concurrent use of an AI. These findings should directly inform prescribers regarding the apparent safety of concurrent DOAC and tamoxifen use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.246
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2022
Admission routes3
Has abstractyes

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