Inclisiran and cardiovascular events: a patient-level analysis of phase III trials
Bibliographic record
Abstract
BACKGROUND: Inclisiran, an siRNA administered twice-yearly, significantly reduced LDL cholesterol (LDL-C) in Phase III trials. Whether lowering LDL-C with inclisiran translates into a lower risk of cardiovascular (CV) events is not yet established. METHODS AND RESULTS: Patient-level, pooled analysis of ORION-9, -10 and -11, included patients with heterozygous familial hypercholesterolaemia, atherosclerotic CV disease (ASCVD), or ASCVD risk equivalent on maximally tolerated statin-therapy, randomized 1:1 to receive 284 mg inclisiran or placebo on Days 1, 90, and 6-monthly thereafter for 18 months. Prespecified exploratory endpoint of major cardiovascular events (MACEs) included non-adjudicated CV death, cardiac arrest, non-fatal myocardial infarction (MI), and fatal and non-fatal stroke, evaluated as part of safety assessments using a standard Medical Dictionary for Regulatory Activities basket. Although not prespecified, total fatal and non-fatal MI, and stroke were also evaluated. Mean LDL-C at baseline was 2.88 mmol/L. At Day 90, the placebo-corrected percentage reduction in LDL-C with inclisiran was 50.6%, corresponding to an absolute reduction of 1.37 mmol/L (both P < 0.0001). Among 3655 patients over 18 months, 303 (8.3%) experienced MACE, including 74 (2.0%) fatal and non-fatal MIs, and 28 (0.8%) fatal and non-fatal strokes. Inclisiran significantly reduced composite MACE [OR (95% CI): 0.74 (0.58-0.94)], but not fatal and non-fatal MIs [OR (95% CI): 0.80 (0.50-1.27)] or fatal and non-fatal stroke [OR (95% CI): 0.86 (0.41-1.81)]. CONCLUSION: This analysis offers early insights into the potential CV benefits of lowering LDL-C with inclisiran and suggests potential benefits for MACE reduction. These findings await confirmation in the larger CV outcomes trials of longer duration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".