Recent advances in treating hypertriglyceridemia in patients at high risk of cardiovascular disease with apolipoprotein C-III inhibitors
Bibliographic record
Abstract
INTRODUCTION: Mild-to-moderate hypertriglyceridemia (HTG) is commonly encountered and is associated with atherosclerotic cardiovascular disease (ASCVD). Elevated plasma triglyceride (TG) levels reflect high levels of triglyceride-rich lipoproteins, against which lipid-lowering therapies that reduce low-density lipoprotein cholesterol are relatively ineffective. Apolipoprotein (apo) C-III is a new pharmacological target to reduce triglycerides and potentially also cardiovascular disease risk. AREAS COVERED: Here, we evaluate current lipid-lowering therapies and their effect on TG levels; genetic, pre-clinical, cellular, molecular biology, and translational studies that emphasize the importance of apo C-III in the metabolism of TG-rich lipoproteins and ASCVD risk; and clinical trials of pharmacotherapies that reduce TG levels via apo C-III inhibition. The PubMed database was searched using terms: apolipoprotein C-III, ARO-APOC3, atherosclerotic cardiovascular disease, olezarsen, triglycerides, and volanesorsen; study types: clinical trials, systematic reviews, and meta-analyses; and time criterion 2005 to present. EXPERT OPINION: Apo C-III inhibition is a promising treatment approach for adults with mild-to-moderate HTG and either established atherosclerotic cardiovascular disease or its risk factors. Biologic agents such as volanesorsen, olezarsen, and ARO-APOC3 significantly reduce plasma levels of apo C-III and TG, although data on cardiovascular outcomes are lacking. Volanesorsen is associated with thrombocytopenia in patients with severe HTG, but other agents appear to be better tolerated. Clinical trials with long-term follow-up of cardiovascular outcomes will establish the validity of apo C-III inhibition.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".