Effects of 12 weeks of treatment with intravenously administered bococizumab, a humanized monoclonal antibody blocking proprotein convertase subtilisin/kexin type 9, in hypercholesterolemic subjects on high‐dose statin
Bibliographic record
Abstract
AIMS: Two multiple-dose phase II studies were conducted in subjects with primary hypercholesterolemia to evaluate the LDL-C lowering efficacy, safety, and tolerability of bococizumab, a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor. METHODS: The results from the two phase II, double-blinded, randomized, placebo-controlled, multicenter studies conducted in the USA and Canada were combined. In Study 1, 90 subjects with LDL-C ≥100 mg/dL received intravenous (IV) placebo or bococizumab 0.25, 1, 3, or 6 mg/kg. In Study 2, 45 subjects with LDL-C ≥80 mg/dL received IV placebo or bococizumab 1 or 3 mg/kg. Subjects were treated every 4 weeks for 12 weeks. Dosing was interrupted if LDL-C dipped to ≤25 mg/dL and resumed if LDL-C returned to ≥40 mg/dL. The primary endpoint was percent LDL-C reduction from baseline at Week 12. RESULTS: At Week 12, the reductions from baseline in LDL-C vs placebo in the bococizumab 0.25, 1, 3, and 6 mg/kg groups were 9.3%, 10.2%, 41.6%, and 52.0%, respectively (P < .001 vs placebo for all). LDL-C reductions were greater (69.9%) in subjects who received all three doses of bococizumab 6 mg/kg (P < .001 vs placebo). Pharmacogenomic analysis revealed that 15% of hyperlipidemic subjects carried polymorphisms associated with familial hypercholesterolemia, with maximal LDL-C reductions being similar between carriers and noncarriers. Adverse events were mild, unrelated to bococizumab, and resolved by Week 12. CONCLUSIONS: These studies demonstrated that bococizumab safely and effectively lowered LDL-C in hypercholesterolemic subjects on high doses of statin.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 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".