The Canadian Breast Cancer Symposium 2025: Meeting Report
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.017 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".