Prediction of inclisiran efficacy in patients with established atherosclerotic cardiovascular disease: the SIRIUS <i>in-silico</i> modelling of cardiovascular outcomes
Bibliographic record
Abstract
Abstract Aims Inclisiran, an siRNA-targeting hepatic PCSK9 mRNA, reduces low-density lipoprotein cholesterol (LDL-C), but its effect on major adverse cardiovascular event (MACE) remains unconfirmed. The SIRIUS in-silico modelling programme aimed to predict the efficacy of inclisiran on MACE in virtual patients with atherosclerotic cardiovascular disease (ASCVD). Methods and results The SIRIUS simulation (NCT05974345) used a validated mechanistic model of ASCVD and lipid-lowering therapy (LLT) effects in a virtual population with established ASCVD and LDL-C ≥ 70 mg/dL. Each virtual patient served as their own control to compare inclisiran vs. placebo as an adjunct to high-intensity statin therapy, alone or with ezetimibe over 5 years. The model did not account for non-adherence, recurrent events, or adverse effects. Among 204 691 virtual patients, inclisiran was predicted to reduce LDL-C by 49.7% vs. placebo (from 91.1 to 48.3 mg/dL). Relative to placebo, inclisiran was predicted to lower 5 years risk of 3-point MACE by 25.2% (11.3% vs. 14.9%), myocardial infarction by 34.8% [5.7% vs. 8.6%; hazard ratio (HR) 0.65], ischaemic stroke by 26% (2.6% vs. 3.4%; HR 0.74), and major adverse limb event by 34.1% (0.5% vs. 0.8%; HR 0.66). A 7.1% relative reduction of cardiovascular death was predicted (4.2% vs. 4.5%; HR 0.93). Conclusion SIRIUS is the first in-silico simulation using a knowledge-based mechanistic model to predict the efficacy of LLT on cardiovascular outcomes in ASCVD. These findings offer an early model-based prediction of inclisiran’s potential cardiovascular benefit ahead of Phase 3 outcome trials. Lay summary The SIRIUS in-silico simulation used a validated knowledge-based mechanistic computational model to computationally simulate inclisiran efficacy on 5-year MACE in 204 691 virtual patients with atherosclerotic cardiovascular disease (ASCVD).Mean predicted percentage reduction in LDL-C with inclisiran vs. placebo was 49.7% at 5 years, with a 25.2% reduction in 3-point MACE.This simulation provides early insights into the potential effect of inclisiran on cardiovascular event reduction in advance of results from ongoing Phase 3 trial.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".