Alirocumab in high-risk patients: Observations from the open-label expanded use program
Bibliographic record
Abstract
BACKGROUND: The alirocumab expanded use program provided open-label access to alirocumab before its commercial availability to patients with severe hypercholesterolemia not controlled with maximally tolerated doses of standard-of-care lipid-lowering therapy. OBJECTIVE: To describe the safety and lipid-lowering efficacy of alirocumab in high-risk patients who were likely to be early users of proprotein convertase subtilisin/kexin type 9 inhibitors after approval. METHODS: Patients with heterozygous familial hypercholesterolemia (HeFH) and/or coronary heart disease (CHD) and baseline low-density lipoprotein cholesterol (LDL-C) of ≥160 mg/dL on maximally tolerated lipid-lowering therapy were enrolled and received alirocumab 150 mg every 2 weeks for 24 weeks. Patients were permitted use of all available statins; those not taking any dose of statin could also be enrolled. RESULTS: Of 100 enrolled patients, 93 were white, 62 were women, and overall mean age was 58 years; 61 had HeFH, 3 had unknown type of familial hypercholesterolemia, 66 had CHD, and 30 had both familial hypercholesterolemia and CHD. Sixty-four patients were identified by their providers to have some level of statin intolerance; of these, 47 were not on statin. Alirocumab reduced LDL-C on average from 221 mg/dL at baseline to 102 mg/dL by week 24 (-55%). Treatment-emergent adverse events were experienced in 61% of patients and treatment-emergent adverse events leading to permanent treatment discontinuation in 3% of patients; no deaths occurred. CONCLUSIONS: Safety and efficacy observations from the open-label alirocumab expanded use program of very high-risk patients with HeFH and/or CHD and baseline LDL-C of ≥160 mg/dL uncontrolled by maximally tolerated lipid-lowering therapy were consistent with those in the placebo/ezetimibe-controlled ODYSSEY trials.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".