Safety and efficacy of zodasiran, a hepatic sirna targeting angptl3, in mixed hyperlipidemia patients: 2 year open label extension (OLE) results from ARCHES-2
Bibliographic record
Abstract
Abstract Background Despite effective LDL-C lowering treatments, patients with mixed hyperlipidemia remain at high ASCVD residual risk attributed to cholesterol transported by LDL and triglyceride (TG)-rich lipoproteins (TRLs). Angiopoietin-like protein 3 (ANGPTL3) regulates lipoprotein metabolism in both the exogenous and endogenous pathways by inhibiting lipoprotein lipase, endothelial lipase and cellular lipoprotein uptake. Naturally-occuring ANGPTL3 loss-of-function variant carriers have lower levels of LDL-C, non-HDL-C, and TGs and reduced ASCVD risk. Zodasiran, an investigational RNAi therapeutic, inhibits hepatic ANGPTL3 expression. Aim To report the long-term efficacy and safety of zodasiran in adults with mixed hyperlipidemia (fasting TG 2-5.64 mmol/L and LDL-C ≥1.8-mmol/L or non-HDL-C ≥2.59-mmol/L. Methods 156 patients entering the OLE, of 204 originally randomized 3:1 to zodasiran 50/100/200mg or placebo subcutaneously on Day1 and Week12, received zodasiran 200mg quarterly during the extension period. Results Zodasiran reduced ANGPTL3, TG, non-HDL-C, apoB, and Remnant-cholesterol from baseline in a dose-dependent manner compared with placebo. By Month1 of the OLE, % change from baseline of TG attained levels were comparable to those in the main study, including among subjects previously on placebo. Durable and sustained reductions in mean % (SD) levels from baseline were -57.9% (22.9) for ANGPTL3; -55.9% (16.3) for TG, -30.1% (21.6) for non-HDL-C, -61.8% (21.2) for Remnant-cholesterol, -9.9% (30.6) for LDL-C, -15.8% (20.8) for apoB, -28.5% (17.9) for total cholesterol, and -19.9% (22.4) for HDL-C occurred in the extension from 1-month post-dose through 24 months. TEAEs occurred in 77.8%; serious AEs were reported in 13.5% of patients; 3.2% discontinued due to an AE. The most common AEs were COVID-19, upper respiratory tract infection, urinary tract infection, headache, Type 2 Diabetes Mellitus, sinusitis, and arthralgia. Conclusions Zodasiran delivered substantial and sustained reductions in ANGPTL3, TG, and atherogenic lipoproteins in patients with mixed hyperlipidemia, with a favorable safety profile, consistent with observations from the blinded portion of the study. The cardiovascular effects remain to be determined.
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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 | 0.002 | 0.001 |
| 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) | 0.003 | 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".