Efficacy and Safety of Alirocumab 300 mg Every 4 Weeks in Individuals With Type 2 Diabetes on Maximally Tolerated Statin
Bibliographic record
Abstract
CONTEXT: In the ODYSSEY CHOICE I trial, alirocumab 300 mg every 4 weeks (Q4W) was assessed in patients with hypercholesterolemia. Alirocumab efficacy and safety were evaluated in a patient subgroup with type 2 diabetes mellitus (T2DM) and who were receiving maximally tolerated statins with or without other lipid-lowering therapies. METHODS: Participants received either alirocumab 300 mg Q4W (n = 458, including 96 with T2DM) or placebo (n = 230, including 50 with T2DM) for 48 weeks, with alirocumab dose adjustment to 150 mg every 2 weeks at Week (W) 12 if W8 low-density lipoprotein cholesterol (LDL-C) levels were ≥70 mg/dL or ≥ 100 mg/dL, depending on cardiovascular risk, or if LDL-C reduction was <30% from baseline. Efficacy end points included percentage change from baseline to W24 for lipids, and time-averaged LDL-C over W21 to W24. RESULTS: In individuals with T2DM, LDL-C reductions from baseline to W24 and the average of W21 to W24 were significantly greater with alirocumab (-61.6% and -68.8%, respectively) vs placebo. At W24, alirocumab significantly reduced levels of non-high-density lipoprotein cholesterol (HDL-C) and other lipids. At W24, 85.9% and 12.5% of individuals in the alirocumab and placebo groups, respectively, reached both non-HDL-C <100 mg/dL and LDL-C <70 mg/dL. At W12, In total, 18% of alirocumab-treated participants received dose adjustment. The most common treatment-emergent adverse events were upper respiratory tract infection and injection-site reaction. No clinically significant changes in fasting plasma glucose and glycated hemoglobin were observed. CONCLUSION: In individuals with T2DM, alirocumab 300 mg Q4W was generally well tolerated and efficacious in reducing atherogenic lipoproteins.
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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 | 0.001 | 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".