Efficacy of alirocumab in high cardiovascular risk populations with or without heterozygous familial hypercholesterolemia: Pooled analysis of eight ODYSSEY Phase 3 clinical program trials
Bibliographic record
Abstract
OBJECTIVES: Despite maximally tolerated statin therapy, many patients with high cardiovascular risk, with or without heterozygous familial hypercholesterolemia may require additional low-density lipoprotein cholesterol (LDL-C) reduction. We report pooled alirocumab (ALI) efficacy and safety data from eight Phase 3 trials in 4629 hypercholesterolemia patients, receiving background statin therapy. MATERIAL AND METHODS: Studies were pooled by ALI dose and control: ALI 75/150mg every 2weeks (Q2W; dose increased to 150mg Q2W at Week 12 based on Week 8 LDL-C) versus ezetimibe (EZE; Pool 1) or placebo (PBO; Pool 2), and ALI 150mg Q2W versus PBO (Pool 3). RESULTS: Mean baseline LDL-C was 109 vs. 105mg/dL (Pool 1), 129 vs. 130mg/dL (Pool 2) and 126 vs. 125mg/dL (Pool 3). ALI 75/150mg Q2W reduced LDL-C by 48.9% (vs. -19.3% EZE) and 48.6% (vs. +4.2% PBO) from baseline to Week 24, and ALI 150mg Q2W reduced LDL-C by 60.4% (vs. +0.5% PBO; all p<0.0001). LDL-C reductions were sustained to Week 104. Risk-based LDL-C goals (<70mg/dL or <100mg/dL) were achieved by 78.0%, 75.2%, and 79.0% (Pool 1-3) of ALI-treated patients (vs. 52.4%, 6.4%, and 8.4%, respectively, for controls) at Week 24. Consistent reductions were observed in apolipoprotein B, non-high-density lipoprotein cholesterol, and lipoprotein (a) (p<0.0001 vs. control). Common adverse events in ALI-treated patients were nasopharyngitis, injection-site reactions, upper respiratory tract infections, and influenza. CONCLUSIONS: Alirocumab treatment significantly reduced LDL-C in high cardiovascular risk patients, enabling most to achieve risk-based LDL-C goals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".