Long‐Term Efficacy, Safety, and Tolerability of Alirocumab in 8242 Patients Eligible for 3 to 5 Years of Placebo‐Controlled Observation in the ODYSSEY OUTCOMES Trial
Bibliographic record
Abstract
ipid-lowering therapy is ordinarily a long-term intervention to reduce cardiovascular risk.Yet, evaluation of long-term efficacy and safety of lipidlowering therapies is often limited by the duration of randomized clinical trials.The ODYSSEY OUTCOMES trial compared alirocumab, a monoclonal antibody to PCSK9 (proprotein convertase subtilisin/kexin type 9), with placebo in 18 924 patients with a recent acute coronary syndrome followed up for up to 5 years.Over a median follow-up of 2.8 years, alirocumab lowered low-density lipoprotein cholesterol from a median 2.3 to 1.0 mmol/L at 4 months, reduced major adverse cardiovascular events (MACEs), 1 was associated with fewer deaths, 2 and had no excess of adverse events (AEs) except for mild-to-moderate local injection-site reactions.1 However, the efficacy and safety of alirocumab among patients eligible for longer follow-up have not been fully explored.The current post hoc analyses describe the efficacy, safety, and tolerability of alirocumab versus placebo in a prespecified subgroup 2 of patients eligible for ≥3 years of follow-up (ie, randomized ≥3 years before the common study end date).At each participating site, the study was approved by the responsible institutional review committee, and subjects gave informed consent.Hazard ratios (HRs) were calculated using Cox regression models, and P values were obtained using log-rank tests.Analyses were stratified by geographic region.Two assessments were performed for both the MACE and cardiovascular death end points to ensure that the proportional hazards model assumptions over time were met: log{-log[S(t)]} versus log[time] (identifying parallel curves) and interaction treatment×time (P interaction =0.19 for MACE, and P interaction =0.43 for cardiovascular death).Data that support the findings of
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".