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Record W4407188092 · doi:10.3324/haematol.2024.286973

Multinational cohort study of intracranial hemorrhage in patients with brain metastases receiving anticoagulation

2025· article· en· W4407188092 on OpenAlexaff
Eva N. Hamulyák, Tzu‐Fei Wang, Lisa Baumann Kreuziger, Varun Iyengar, Brian J. Carney, Ann Hoeben, Berna C. Özdemir, Kristen M. Sanfilippo, Shira Rozenblatt, Ludo F.M. Beenen, Shlomit Yust‐Katz, Erez Halperin, Ariela Arad, Aharon Lubetsky, Marc Carrier, Benjamin Massat, Harry R. Büller, Galia Spectre, Jeffrey I. Zwicker, Avi Leader

Bibliographic record

VenueHaematologica · 2025
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Cancer InstituteNational Institutes of Health
KeywordsMedicineIntracranial HemorrhagesCohortBrain hemorrhageInternal medicineSurgeryNeurosurgerySubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

Multinational cohort study of intracranial hemorrhage in patients with brain metastases receiving anticoagulationSpontaneous intracranial hemorrhage (ICH) represents a common complication in patients with brain metastases.1,2 As cardiovascular complications, including venous thromboembolism (VTE), are prevalent in cancer patients, many patients with brain metastases have an indication for therapeutic anticoagulation.The incidence rate of ICH with anticoagulation is approximately 15% in patients with metastatic brain cancer.2 Although anticoagulation increases the risk of any bleeding event, prior cohort studies suggest that the risk of ICH in patients with brain metastases is similar with or without anticoagulation.1,2,3 While two small retrospective cohort studies suggest safety of direct oral anticoagulants (DOAC) compared to low-molecular-weight heparin (LMWH) in this population, 4,5 due to the limited sample sizes and wide Confidence Intervals (CI) of point estimates, the ICH profile of DOAC versus LWMH in patients with metastatic brain tumors remains uncertain.Data are also lacking regarding risk factors for ICH and clinical and radiological presentation of ICH, as well as outcomes following ICH including recurrent thrombosis and recurrent hemorrhage after re-initiation of anticoagulation.To address these knowledge gaps, we conducted a multinational cohort study to compare rates of hemorrhage among patients with brain metastases treated with DOAC or LMWH and evaluate outcomes including mortality, recurrent thrombosis, and hemorrhage.The Anticoagulation in Brain Cancer (ABC) Study was a retrospective cohort study involving 12 academic and non-academic hospitals in Canada, Israel, Mexico, Switzerland, the Netherlands, and the United States.The study protocol was approved by local medical ethics committees.Informed consent was waived and the study was conducted in line with local regulations.We screened the records of all patients in the hemato-oncology or medical oncology departments at the study centers between January 1 st , 2014 and January 1 st , 2022 for eligibility.The study included adult patients with systemic solid cancer and brain metastases confirmed through pathology and imaging, respectively.Eligibility criteria were active cancer, defined as newly diagnosed or undergoing treatment, and therapeutic anticoagulation (both full dose and indicated dose reductions prescribed with therapeutic intent) with either DOAC or LMWH.Patients with ICH before the initiation of anticoagulation and those lacking any follow-up data were excluded.Repeat brain imaging during follow-up was not a prerequisite for inclusion.Study index was defined as the first day of concurrent anticoagulation and brain metastases diagnosis, and patients were followed for 12 months.An additional 90-day follow-up was conducted for patients who experienced anticoagulation-related ICH to

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.277
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2025
Admission routes1
Has abstractyes

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