Individualized low-density lipoprotein cholesterol reduction with alirocumab titration strategy in heterozygous familial hypercholesterolemia: Results from an open-label extension of the ODYSSEY LONG TERM trial
Bibliographic record
Abstract
BACKGROUND: Patients with heterozygous familial hypercholesterolemia (HeFH) who completed the double-blind ODYSSEY LONG TERM parent trial and subsequently enrolled in the open-label extension (OLE) study, ODYSSEY OLE (NCT01954394), provide a unique opportunity to investigate effects of 2 doses of alirocumab, a proprotein convertase subtilisin/kexin type 9 inhibitor, within the same patient cohort. OBJECTIVE: The aim of the study was to characterize long-term efficacy and safety of 2 alirocumab dosages and utility of a dose titration strategy in patients with HeFH. METHODS: After an 8-week washout period, patients with HeFH who completed the LONG TERM study (receiving alirocumab 150 mg every 2 weeks [Q2W]) were eligible to enroll in OLE (n = 214) for up to 40 months' treatment duration. In OLE, patients started on alirocumab 75 mg Q2W. From Week 12, dose adjustment from 75 to 150 mg Q2W or vice versa was possible based on physician's clinical judgment. RESULTS: During the LONG TERM trial, alirocumab 150 mg Q2W reduced mean low-density lipoprotein cholesterol (LDL-C) from baseline (162.3 mg/dL) to Week 8 by 63.1%; during OLE, alirocumab 75 mg Q2W reduced mean LDL-C from baseline (166.6 mg/dL) by 47.3% within the same patient cohort. At Week 96, mean LDL-C reduction from OLE baseline was 55.4% vs 46.8% for patients with or without alirocumab dose increase, respectively. Treatment-emergent adverse events leading to permanent treatment discontinuation were observed in 4 patients (1.9%). CONCLUSIONS: In patients with HeFH, both alirocumab dosages provided consistent LDL-C reductions over a treatment duration of up to 4 years (including 1.5 years of the LONG TERM trial), allowing an individualized approach to LDL-C lowering, depending on baseline LDL-C levels.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".