Preventing Cardiac Damage in Patients Treated for Breast Cancer and Lymphoma
Bibliographic record
Abstract
Background: Cardiotoxicity is a concern for cancer survivors undergoing anthracycline chemotherapy. Enalapril has been explored for its potential to mitigate cardiotoxicity in cancer patients. The dose-dependent cardiotoxicity effects of anthracyclines can be detected early through the biomarker cardiac troponin. Objectives: The PROACT (Preventing Cardiac Damage in Patients Treated for Breast Cancer and Lymphoma) clinical trial assessed the effectiveness of enalapril in preventing cardiotoxicity, manifesting as myocardial injury and cardiac function impairment, in patients undergoing high-dose anthracycline-based chemotherapy for breast cancer or non-Hodgkin lymphoma. Methods: doxorubicin equivalents, were randomized to receive either enalapril (titrated up to 20 mg daily) or standard care without enalapril. Results: Myocardial injury, indicated by cardiac troponin T (≥14 ng/L), during and 1 month after chemotherapy, was observed in 42 (77.8%) of 54 patients in the enalapril group vs 45 (83.3%) of 54 patients in the standard care group (OR: 0.65; 95% CI: 0.23-1.78). Injury detected by cardiac troponin I (>26.2 ng/L) occurred in 25 (47.2%) of 53 patients on enalapril compared with 24 (45.3%) of 53 in standard care (OR: 1.10; 95% CI: 0.50-2.38). A relative decline of more than 15% from baseline in left ventricular global longitudinal strain was observed in 10 (21.3%) of 47 patients on enalapril and 9 (21.9%) of 41 in standard care (OR: 0.95; 95% CI: 0.33-2.74). An absolute decline of >10% to <50% in left ventricular ejection fraction was seen in 2 (4.1%) of 49 patients on enalapril vs none in patients in standard care. Conclusions: Adding enalapril to standard care during chemotherapy did not prevent cardiotoxicity in patients receiving high-dose anthracycline-based chemotherapy. (PROACT: Can we prevent Chemotherapy-related Heart Damage in Patients With Breast Cancer and Lymphoma?; NCT03265574).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".