Statins to prevent early cardiac dysfunction in cancer patients at increased cardiotoxicity risk receiving anthracyclines
Bibliographic record
Abstract
BACKGROUND AND AIMS: Anthracyclines can cause cancer therapy-related cardiac dysfunction (CTRCD). We aimed to assess whether statins prevent decline in left ventricular ejection fraction (LVEF) in anthracycline-treated patients at increased risk for CTRCD. METHODS: In this multicenter double-blinded, placebo-controlled trial, patients with cancer at increased risk of anthracycline-related CTRCD (per ASCO guidelines) were randomly assigned to atorvastatin 40 mg or placebo once-daily. Cardiovascular magnetic resonance (CMR) imaging was performed before and within 4 weeks after anthracyclines. Blood biomarkers were measured at every cycle. The primary outcome was post-anthracycline LVEF, adjusted for baseline. CTRCD was defined as a fall in LVEF by >10% to <53%. Secondary endpoints included left ventricular (LV) volumes, CTRCD, CMR tissue characterization, high sensitivity troponin I (hsTnI), and B-type natriuretic peptide (BNP). RESULTS: We randomized 112 patients (56.9 ± 13.6 years, 87 female, and 73 with breast cancer): 54 to atorvastatin and 58 to placebo. Post-anthracycline CMR was performed 22 (13-27) days from last anthracycline dose. Post-anthracycline LVEF did not differ between the atorvastatin and placebo groups (57.3 ± 5.8% and 55.9 ± 7.4%, respectively) when adjusted for baseline LVEF (P = 0.34). There were no significant between-group differences in post-anthracycline LV end-diastolic (P = 0.20) or end-systolic volume (P = 0.12), CMR myocardial edema and/or fibrosis (P = 0.06-0.47), or peak hsTnI (P ≥ 0.99) and BNP (P = 0.23). CTRCD incidence was similar (4% versus 4%, P ≥ 0.99). There was no difference in adverse events. CONCLUSIONS: In patients at increased risk of CTRCD, primary prevention with atorvastatin during anthracycline therapy did not ameliorate early LVEF decline, LV remodeling, CTRCD, change in serum cardiac biomarkers, or CMR myocardial tissue changes. TRIAL REGISTRATION: NCT03186404.
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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 | 0.001 |
| 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) | 0.001 | 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".