Trastuzumab-mediated cardiotoxicity in the nontrial setting: Evaluation of patients receiving adjuvant trastuzumab at an academic centre
Bibliographic record
Abstract
e11550 Background: Trastuzumab is effective in the treatment of HER-2 positive breast cancer. Although clinical trials have shown an increased risk of cardiotoxicity associated with trastuzumab, this risk has not been well studied in the non-trial setting. This study aims to examine (1) the incidence of cardiotoxicity associated with trastuzumab in the clinical setting (2) the relationship, if any, between risk factors and incidence of cardiotoxicity and (3) cardiac monitoring practices. Methods: A retrospective chart review was conducted of all patients receiving adjuvant trastuzumab therapy between August 2005 and May 2008, at a Canadian academic centre. The incidence of cardiotoxicity, defined as a significant reduction in left ventricular ejection fraction (drop of >10% leading to an ejection fraction of <50%) and/or New York Heart Association class III-IV CHF symptoms requiring trastuzumab delay or discontinuation was evaluated. Medical charts and patient surveys provided demographics, risk factors and cardiac toxicity for each patient. Results: 183 patients were included in the study. The average age of participating patients was 54.8 years and 51% of participants had node positive cancer. 72% were treated sequentially with Trastuzumab and 88% received anthracyclines. The incidence of cardiotoxicity was 6.0% (n=11). Upon univariate analysis, patient age was found to be the only variable significantly associated with the occurrence of cardiotoxicity (OR: 3.55, 95% CI 1.76–90.0). Left ventricular function was monitored by serial MUGA scan every 3.35 ±1.89 months as compared to the 3 month gold standard in clinical trials. Conclusions: In this study the incidence of cardiotoxicity was 6.0%. Patient age was the only significant variable associated with cardiotoxicity, as expected from previous studies. Clinically, this suggests that older patients may need more frequent monitoring for cardiac dysfunction via MUGA and/or ECHO scans. Future research needs to address the relationship between treatment regimens and the incidence of cardiotoxicity. Furthermore, we need to better define cardiotoxicity and the clinical significance of cardiac related symptoms. No significant financial relationships to disclose.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".