Efficacy and safety of bempedoic acid in patients not receiving statins in phase 3 clinical trials
Bibliographic record
Abstract
BACKGROUND: Despite the high incidence of patients with statin tolerance problems, randomized evaluations of nonstatin oral treatment options for lowering of low-density lipoprotein cholesterol (LDL-C) in this population are sparse. OBJECTIVE: To assess the LDL-C lowering effect of bempedoic acid in patients not taking statins. METHODS: This was a pooled analysis of data from patients enrolled in four phase 3 bempedoic acid studies (12 to 52 weeks in duration) who were not taking concomitant statins (Phase 3 No Statin Cohort) and a phase 3 bempedoic acid plus ezetimibe fixed-dose combination study (BA+EZE FDC No Statin Cohort). The primary endpoint for all studies was the percent change from baseline to week 12 in LDL-C levels. Safety and tolerability were assessed by laboratory values and adverse events. RESULTS: In the Phase 3 No Statin Cohort, bempedoic acid (n = 394) lowered LDL-C levels at week 12 significantly more than placebo (n = 192; -26.5% [95% CI, -29.7%, -23.2%]; P<0.001). The fixed-dose combination of bempedoic acid with ezetimibe lowered LDL-C by 39.2% (95% CI, -51.7% to -26.7%; P<0.001). Muscle-related disorders occurred at a rate of 26.4 and 28.6 per 100 person-years with bempedoic acid and placebo, respectively. CONCLUSIONS: In patients with hypercholesterolemia unable to take statins, bempedoic acid lowered LDL-C levels by a mean of 26.5% vs placebo and bempedoic acid + ezetimibe fixed-dose combination lowered LDL-C by 39.2%. The treatments were generally well tolerated, suggesting that bempedoic acid may be efficacious and well tolerated in this challenging-to-treat patient population.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".