Effect of Apabetalone on Major Adverse Cardiovascular Events in Patients with CKD, Diabetes, and Recent Acute Coronary Syndrome: Results from the BETonMACE Trial
Bibliographic record
Abstract
Background: Chronic kidney disease (CKD) in type 2 diabetes mellitus (T2DM) patients (pts) is associated with increased cardiovascular disease (CVD) and heart failure risk. We hypothesized that a maladaptive epigenetic response engaging the bromodomain and extraterminal (BET) protein transcription system contributes to excess CVD risk. Hence, the efficacy of BET inhibition (BETi) treatment with apabetalone (APB) was assessed according to presence of CKD in the phase 3 BETonMACE trial. Methods: BETonMACE compared APB with placebo in 2425 pts with T2DM and recent acute coronary syndrome. The primary outcome was CV death, non-fatal myocardial infarct or stroke (MACE). Hospitalization for congestive heart failure (HCHF) was a secondary endpoint. Both outcomes were evaluated according to the presence of CKD (estimated GFR <60 mL/min/1.73 m2 at baseline). Results: CKD pts were older (71 vs. 61 years), more likely female (42% vs. 23%) or non-white (18% vs. 12%), had longer duration of diabetes (mean 11.3 vs. 8.2 years) and higher serum alkaline phosphatase (91 vs. 81 U/L), and were less likely to receive metformin (69% vs. 84%) or SGLT2 inhibitors (6% vs. 13%) (P<0.05 for all). Under placebo, risk of endpoints was higher in CKD vs. non-CKD pts [MACE: 35/164 (21.3%) vs.114/1041 (11.0%), HR=2.40, 95% CI [1.67, 3.44]; HCHF: 14/164 (8.5%) vs. 34/1041 (3.3%), HR=3.19, 95% CI [1.66,6.12]; P<0.001 for both). Under APB treatment, pts with CKD had significant reductions in MACE (HR=0.50, 95% CI [0.26, 0.96], P=0.034) and HCHF (HR=0.26, 95% CI [0.07,0.94], P=0.028) vs. placebo, see Kaplan-Meier figures. Conclusions: CKD patients with T2DM and recent acute coronary syndrome have a high risk of MACE that was substantially reduced with APB BETi in the phase 3 BETonMACE trial.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".