Efficacy and safety of inclisiran in patients with cerebrovascular disease: ORION-9, ORION-10, and ORION-11
Bibliographic record
Abstract
Patients with cerebrovascular disease (CeVD) have been shown to benefit from lipid-lowering therapies, but guideline-recommended levels of low-density lipoprotein cholesterol (LDL-C) are often not attained with statin treatment alone. The ORION-9, ORION-10, and ORION-11 trials evaluated the efficacy and safety of inclisiran in 3660 primary and secondary prevention patients with hyperlipidemia despite maximum tolerated statin treatment. This pooled post hoc analysis comprised 202 randomized patients from those trials with established CeVD who had received either 284 mg inclisiran (equivalent to 300 mg inclisiran sodium, n = 110) or placebo (n = 92) on Days 1, 90, and 6-monthly thereafter up to Day 540. At baseline, mean (SD) LDL-C was 108.4 (34.3) mg/dL and 110.5 (35.3) mg/dL in inclisiran and placebo arms, respectively. Inclisiran produced a mean (95% CI) placebo-corrected percentage change in LDL-C from baseline to Day 510 of –55.2 (–64.5 to –45.9; p < 0.0001); the corresponding time-adjusted percentage change from baseline after Day 90 and up to Day 540 was –55.2 (–62.4 to –47.9; p < 0.0001). Treatment-emergent adverse events (TEAEs) and TEAEs at the injection site, mostly mild, were more frequent with inclisiran versus placebo (82.7% vs 70.7% and 3.6% vs 0%, respectively). In patients with CeVD, twice-yearly dosing with inclisiran (after the initial and 3-month doses) in combination with maximally tolerated statins provided effective and consistent LDL-C reductions and was well tolerated.
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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 | 0.003 | 0.003 |
| 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 | 0.000 |
| 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".