Open-label therapy with alirocumab in patients with heterozygous familial hypercholesterolemia: Results from three years of treatment
Bibliographic record
Abstract
BACKGROUND: PCSK9 inhibition with alirocumab significantly reduced LDL-C levels in trials of up to 78weeks' duration in patients with heterozygous familial hypercholesterolemia (HeFH). We report results from 3years of an ongoing open-label treatment extension (NCT01576484) to a 12-week double-blind trial in HeFH patients (NCT01266876). METHODS: Patients who completed the parent study and were receiving stable daily statin±ezetimibe could enter the open-label extension, where they received alirocumab 150mg every 2 weeks (Q2W) subcutaneously (n=58). The primary endpoint was safety (treatment-emergent adverse events, TEAEs). Efficacy endpoints included the percentage change in LDL-C from baseline at Week 24. Safety and efficacy data were available up to Weeks 156 and 148, respectively. RESULTS: Mean baseline LDL-C was 150.7mg/dL (3.9mmol/L), despite all patients being on a statin (76% on high-intensity statin; 72% also receiving ezetimibe). Over 156weeks, 54 (93.1%) patients experienced a TEAE, 12 (20.7%) experienced a serious TEAE, and two (3.4%) discontinued due to a TEAE. Injection site reactions occurred in 21 (36.2%) patients. Mean (SD) reduction in LDL-C from baseline to Week 24 was 65.4 (21.1)%, with reductions maintained through 148weeks (Week 148 reduction: 56.0 [23.8]%). Mean apolipoprotein B reduction was 50.9% and median lipoprotein (a) reduction was 22.5% at Week 24 (46.1% and 25.6% at Week 148, respectively). CONCLUSIONS: Open-label treatment for 3years with alirocumab 150mg Q2W, administered with background statin±ezetimibe, was generally well-tolerated and had a safety profile comparable with that seen in the overall alirocumab clinical trial program. Alirocumab provided significant, sustained LDL-C reductions.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".