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Record W7117517914 · doi:10.3390/curroncol33010015

The Canadian Breast Cancer Symposium 2025: Meeting Report

2025· article· en· W7117517914 on OpenAlexafffundvenueabout
Christine Brezden‐Masley, Katarzyna J. Jerzak, Nancy Nixon, Anne Koch, Amanda Roberts, Jean-François Boileau, May Lynn Quan, MJ DeCoteau, Tulin Cil

Bibliographic record

VenueCurrent Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsJewish General HospitalPrincess Margaret Cancer CentreUniversity of CalgaryUniversity of TorontoSunnybrook Health Science CentreMount Sinai Hospital
FundersUniversity of TorontoHologicMerck KGaAExact Sciences CorporationPfizerStrykerNovartis Pharmaceuticals CorporationMerit Medical SystemsF. Hoffmann-La Roche
KeywordsBreast cancerSurvivorship curveSystemic therapyRadiation therapyRadiation oncologyCancer survivorshipAlternative medicineClinical Practice

Abstract

fetched live from OpenAlex

The 2025 Canadian Breast Cancer Symposium (CBCS) brought together patients, clinicians and researchers from across Canada to discuss advances shaping personalized breast cancer care. Key updates in systemic therapy highlighted expanding treatment options, including CDK4/6 inhibitors, oral SERDs, PI3K/AKT-targeted therapies, and antibody-drug conjugates across early and metastatic settings. Radiation oncology sessions emphasized treatment de-escalation, featuring evidence for ultra-hypofractionation, selective omission of nodal irradiation, and stereotactic strategies to manage oligoprogression. Surgical presentations focused on reducing morbidity through tailored axillary management and emerging techniques to prevent lymphedema. Advances in the management of central nervous system metastases underscored the growing synergy between stereotactic radiotherapy and CNS-active systemic therapies. Informed by patient testimony and advocacy perspectives, experts reflected on persistent gaps in diagnosis, access, and survivorship that shape priorities for future improvements. Together, these insights outline key directions that help to refine clinical practice and guide future research.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.910
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

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

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 head0.047
GPT teacher head0.421
Teacher spread0.374 · 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.

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

Citations0
Published2025
Admission routes4
Has abstractyes

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