Advances in Adjuvant Therapy for High-Risk Breast Cancer: A Canadian Clinical Approach
Bibliographic record
Abstract
Breast cancer remains the second leading cause of cancer-related death among women in Canada. In early-stage disease, the purpose of adjuvant therapies following surgical resection is to reduce the risk of recurrence. The advent of adjuvant endocrine therapy (ET) significantly reduced breast cancer recurrence and mortality; however, some patients have disease recurrence even 20 years after initial diagnosis. Therefore, several advancements have been made to optimize cure rates and improve outcomes. As a heterogeneous disease, breast cancer outcomes are impacted by clinical, histological, and genomic features, which guide prognosis and selection of adjuvant therapy. This review focuses on recent and emerging adjuvant therapies, specifically for high-risk patients across breast cancer subtypes: hormone receptor‑positive (HR‑positive), human epidermal growth factor receptor 2-positive (HER2-positive), and triple‑negative breast cancer (TNBC).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".