A phase III randomized trial evaluating alirocumab 300 mg every 4 weeks as monotherapy or add-on to statin: ODYSSEY CHOICE I
Bibliographic record
Abstract
BACKGROUND AND AIMS: In previous phase III studies, the PCSK9 monoclonal antibody alirocumab was administered at doses of 75 or 150 mg every 2 weeks (Q2W). CHOICE I (NCT01926782) evaluated 300 mg every 4 weeks (Q4W) in patients on either maximally tolerated statin or no statin, both ± other lipid-lowering therapies. METHODS: CHOICE I included patients with hypercholesterolemia at moderate-to-very-high cardiovascular risk. Patients were randomized to alirocumab 300 mg Q4W, 75 mg Q2W (calibrator arm), or placebo for 48 weeks, with dose adjustment for either alirocumab arm to 150 mg Q2W at Week (W) 12 if at W8 LDL-C levels were >70/100 mg/dL (1.8/2.6 mmol/L) depending on cardiovascular risk or LDL-C reduction was <30% from baseline. Co-primary endpoints were percent LDL-C change from baseline to W24, and to time-averaged LDL-C over W21-24. RESULTS: Approximately two-thirds of randomized patients were receiving statins. At W12, 14.7% (no statin) and 19.3% (statin) of patients receiving alirocumab 300 mg Q4W required dose adjustment. At W24, significant LDL-C reductions from baseline were observed with alirocumab 300 mg Q4W: mean differences were -52.7% (no statin; placebo: -0.3%) and -58.8% (statin; placebo: -0.1%). Average LDL-C reductions from baseline to W21-24 were also significantly greater with alirocumab 300 mg Q4W vs. placebo in patients not receiving (-56.9% vs. -1.6%) and receiving statin (-65.8% vs. -0.8%). Treatment-emergent adverse event rates ranged from 61.1 to 75.0% (placebo) and 71.5 to 78.1% (alirocumab 300 mg Q4W). CONCLUSIONS: Alirocumab 300 mg Q4W is a viable additional treatment option in patients requiring LDL-C-lowering.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".