Rates of trastuzumab-associated cardiotoxicity in patients with HER2-positive breast cancer at a tertiary cancer centre.
Bibliographic record
Abstract
e12030 Background: Human epidermal growth factor receptor 2 ( HER2) is overexpressed in 15-25% of breast cancers and associated with decreased rates of survival. Trastuzumab (TZ) is a humanized monoclonal antibody that binds against HER-2 and improves both disease free and overall survival in the adjuvant setting. A side effect of TZ is reversible cardiotoxicity(CT), which can lead to early termination of TZ. The rates of TZ associated CT seen in trials range between 1-16%. These rates may not be representative of clinical practice. Our aim is to identify the rate of TZ-associated CT and the rate of early discontinuation of TZ associated CT at the Juravinski Cancer Centre (JCC), in Hamilton, Ontario. Methods: Patients treated with adjuvant TZ between 2006-2013 at JCC were identified using JCC pharmacy data and included in this audit. We examined patient charts for relevant clinical-pathologic variables, cardiac Results: Results are shown in the table below. Conclusions: In conclusion, we found that rates of CT were higher at JCC than in clinical trials. This is not unexpected as patients with known cardiac risk factors and history of cardiac disease were excluded from most clinical trials. Strategies to optimize cardiac risk factors and management of CT are needed. We have opened a cardio-oncology clinic at JCC and initiated a clinical trial examining the feasibility of ongoing TZ therapy in the setting of mild DLVEF. [Table: see text]
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".