Efficacy and Safety of Ezetimibe Coadministered With Atorvastatin or Simvastatin in Patients With Homozygous Familial Hypercholesterolemia
Bibliographic record
Abstract
BACKGROUND: Patients with homozygous familial hypercholesterolemia (HoFH) have a high incidence of cardiovascular morbidity and mortality from premature atherosclerosis, and the efficacy of pharmacological therapy has been limited. We evaluated the efficacy, safety, and tolerability of ezetimibe, a novel cholesterol absorption inhibitor, in a multicenter, double-blind, randomized trial of HoFH patients receiving atorvastatin or simvastatin. Methods and Results- Fifty patients with a diagnosis of HoFH on the National Cholesterol Education Program Step 1 or stricter diet and taking open-label atorvastatin 40 mg/d or simvastatin 40 mg/d (statin-40) with (n=25) or without (n=25) concomitant LDL apheresis were randomized to 1 of 3 double-blind treatments: atorvastatin or simvastatin 80 mg/d (statin-80, n=17); ezetimibe 10 mg/d plus atorvastatin or simvastatin 40 mg/d (n=16); or ezetimibe 10 mg/d plus atorvastatin or simvastatin 80 mg/d (n=17) for 12 weeks. The primary end point was mean percentage change in LDL cholesterol (LDL-C) from statin-40 baseline to the end point for patients receiving statins alone (statin-80) versus patients receiving ezetimibe plus atorvastatin or simvastatin at either dose (ezetimibe plus statin-40/80). Ezetimibe plus statin-40/80 significantly reduced LDL-C levels compared with statin-80 (-20.7% versus -6.7%, P=0.007). In the high-dose statin cohorts, ezetimibe plus statin-80 reduced LDL-C by an additional 20.5% (P=0.0001) versus statin-80. Similar significant reductions in LDL-C concentrations were observed for patients with genotype-confirmed HoFH (n=35). Ezetimibe was safe and well tolerated. CONCLUSIONS: Ezetimibe coadministered with atorvastatin or simvastatin in patients with HoFH produced clinically important LDL-C reductions compared with best current therapy. Ezetimibe provides a new, complementary pharmacological approach for this high-risk population.
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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 | 0.002 |
| 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 | 0.001 |
| 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".