Trastuzumab cardiotoxicity: biological hypotheses and clinical open issues
Bibliographic record
Abstract
BACKGROUND: Trastuzumab has significantly improved the prognosis of breast cancer patients overexpressing the human epidermal growth factor receptor 2 (HER2). This result has been achieved in all disease settings, by increasing overall survival in early stage and advanced disease and by increasing pathological complete responses in neoadjuvant disease. OBJECTIVE: Although the greatest impact of this monoclonal antibody has been seen in the adjuvant setting, by increasing disease-free survival and overall survival rates an increased rate of both symptomatic and non-symptomatic cardiac toxicity has also been observed. METHODS: In the following review, the different mechanisms of trastuzumab cardiac toxicity are described and, in addition, the clinical data coming from both trials and meta-analyses is discussed. RESULTS: While there is strong evidence for the incidence of trastuzumab-related cardiac toxicity, there is still little known on the exact pathogenesis of this toxicity. Interestingly, both experimental and clinical data suggest that trastuzumab may sensitize cardiomyocytes to injuries and stress from administration of anthracyclines. This has led to a proposed novel mechanism of cardiotoxicity that appears to be quite different from the anthracycline-associated cardiotoxicity. Trastuzumab does not seem to cause any overt ultrastructural abnormality; it does, however, lead to myocardial dysfunction. CONCLUSION: Most of the proposed hypotheses seems to be related to the activity of trastuzumab in interfering with the ERBB-2 receptor. Indeed, data from clinical trials in the adjuvant setting report increased cardiac toxicity in those patients who previously received anthracyclines.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".