Trastuzumab-Induced Cardiotoxicity: Testing a Clinical Risk Score in a Real-World Cardio-Oncology Population
Bibliographic record
Abstract
BACKGROUND: Trastuzumab has improved survival for women with her2-positive breast cancer, but its use is associated with an increased risk of cardiotoxicity. With increased survivorship, the long-term effects of cancer treatment are an important consideration for clinicians and patients. We reviewed the current literature on predicting trastuzumab-related cardiotoxicity and tested a clinical risk score (crs) in a real-world breast cancer population to assess its utility in predicting permanent cardiotoxicity. METHODS: In this retrospective exploratory cohort study of breast cancer patients referred to a cardio-oncology clinic at a tertiary care centre between October 2008 and August 2014, a crs was calculated for each patient, and a sensitivity analysis was performed. RESULTS: Of the 143 patients included in the study, 62 (43%) experienced a cardiac event, and of those 62 patients, 43 (69%) experienced full recovery of cardiac function. In applying the crs, 119 patients (83%) would be considered at low risk, 14 (10%) at moderate risk, and 10 (7%) at high risk to develop heart failure or cardiomyopathy. When applied to the study population, the high-risk cut-off score had a sensitivity of 0.13 [95% confidence interval (ci): 0.08 to 0.20] and a specificity of 0.94 (95% ci: 0.87 to 0.97). The positive predictive value was 0.07 (95% ci: 0.03 to 0.13), and the negative predictive value was 0.93 (95% ci: 0.87 to 0.96). CONCLUSIONS: The crs demonstrated good specificity and negative predictive value for the development of permanent cardiotoxicity in a real-world population of breast cancer patients, suggesting that intensive cardiac monitoring might not be warranted in low-risk patients, but that high-risk patients might benefit from early referral to cardio-oncology for optimization. Further study using the crs in a larger breast cancer population is warranted to identify patients at low risk of long-term trastuzumab-related cardiotoxicity.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.002 |
| 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".