Atorvastatin and Myocardial Extracellular Volume Expansion During Anthracycline-Based Chemotherapy
Bibliographic record
Abstract
BACKGROUND: In the STOP-CA (Statins to Prevent the Cardiotoxicity From Anthracyclines) trial, atorvastatin preserved the left ventricular ejection fraction among patients with lymphoma treated with anthracyclines. The protective mechanisms are currently unclear. OBJECTIVES: The aim of this study was to test the effect of atorvastatin on the anthracycline-associated increase in myocardial extracellular volume (ECV) using cardiac magnetic resonance imaging (MRI). METHODS: Cardiac MRI with mapping was performed at baseline and at 12-month follow-up. ECV was calculated, and the primary endpoint was a ≥3% increase. Increases of ≥1 SD in native T1 and T2 times and ECV were secondary endpoints. RESULTS: The subgroup included 171 participants with paired cardiac MRI scans, and 127 had contrast scans of appropriate quality (median age 52 years, 47% women). The proportion of participants with ≥3% increases in ECV was lower in the atorvastatin compared with the placebo group (8% vs 29%; P = 0.002; OR: 0.20; 95% CI: 0.06 to 0.59). A ≥3% increase in ECV was associated with an 8.4% decrease in left ventricular ejection fraction at follow-up (95% CI: -6.31 to -10.38; P < 0.001). The proportion of participants with ≥1-SD increases in T1 and T2 times was statistically similar between groups at 12 months. At 24 months, there were fewer heart failure events among those without ≥3% increases in ECV (8% vs 24%; P = 0.054), though not statistically significantly. CONCLUSIONS: Compared with placebo, atorvastatin limited ECV expansion among participants with lymphoma undergoing anthracycline chemotherapy. This study is the first to provide mechanistic insight into statins' cardioprotective effects with anthracyclines. (Statins to Prevent the Cardiotoxicity From Anthracyclines [STOP-CA]; NCT02943590).
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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) | 0.000 | 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 | 0.000 | 0.000 |
| 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".