Cardiac Management during Adjuvant Trastuzumab Therapy: Recommendations of the Canadian Trastuzumab Working Group
Bibliographic record
Abstract
Trastuzumab has been shown to be an effective therapy for women with breast cancer that overexpresses the human epidermal growth factor receptor 2 (her2) protein. In the pivotal metastatic breast cancer trials, cardiac dysfunction was observed in women treated with trastuzumab and chemotherapy. The incidence and severity of cardiac dysfunction was greatest among patients who received trastuzumab in combination with anthracycline-based therapy. Those findings influenced the design of subsequent trastuzumab trials to include prospective evaluations of cardiac effects and protocols for cardiac monitoring and management. The risk of cardiotoxicity has also driven efforts to develop non-anthracycline-based regimens for women with her2-positive breast cancers.With the increasing use of trastuzumab, particularly in the curative adjuvant setting, the need for a rational approach to the treatment and cardiac management of the relevant patient population is clear. The mandate of the Canadian Trastuzumab Working Group was to formulate recommendations, based on available data, for the assessment and management of cardiac complications during adjuvant trastuzumab therapy. The panel formulated recommendations in four areas: Risk factors for cardiotoxicity, Effects of various regimens, Monitoring, Management. The recommendations published here are expected to evolve as more data become available and experience with trastuzumab in the adjuvant setting grows.
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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 | 0.018 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".