Abstract 11174: Effect of APOCIII-L <sub>Rx</sub> on Lipoprotein Size and Particle Numbers Measured by NMR in Patients with Hypertriglyceridemia: Results of the AKCEA-APOCIII-L <sub>Rx</sub> Trial
Bibliographic record
Abstract
Background: APOCIII-L Rx is a hepatocyte-targeted, GalNAc-modified antisense oligonucleotide that decreases plasma levels of apoC-III and triglyceride-rich lipoproteins (TRLs). We examined the effect of APOCIII-L Rx on a variety of lipoprotein fractions measured by nuclear magnetic resonance (NMR) spectroscopy. Methods: The AKCEA-APOCIII-L Rx trial was a dose-ranging study in 114 patients with, or at risk for, ASCVD and fasting serum triglycerides 200-500 mg/dL. Patients (n=114) received AKCEA-APOCIII-L Rx (10 or 50 mg every 4 weeks, 15 mg every 2 weeks, or 10 mg every week) or saline placebo subcutaneously for 6-12 months. Comprehensive NMR LipoProfile ® analysis was performed by LipoScience/LabCorp in frozen EDTA plasma samples collected at baseline and at the primary analysis timepoint (PAT) at 6 months. Results: Results are reported as change from baseline to PAT for the 50 mg every 4 weeks dose versus placebo. APOCIII-L Rx resulted in a significant reduction in total TRL particle (TRLP) concentration by 51% (P<0.0001) with largest reductions in large-size (by 68%, P<0.0001) and medium-size (by 63%, P<0.0001) TRLPs. Total LDL particle (LDLP) concentration was not changed, small LDLP numerically decreased by 39% (P= 0.0713) while medium LDLP increased by 187% (P=0.0119), accompanied by an increase in average LDL size by xx 2% (p=0.0039xx). Total HDL particle (HDLP) concentration increased by 15% (P=0.0006), represented primarily by an increase in small HDL subspecies (particle diameters <8.3 mm) of 32% (P=0.0008). Lower cumulative doses of APOCIII-L Rx generally reflected a dose-dependent relationship in the above parameters. Conclusion: APOCIII-L Rx results in favorable changes in lipoprotein concentration and particle size, primarily manifested by reduction in TRLs, remodeling to larger LDL particles, and increase in small HDLP. These findings suggest an improvement in overall atherogenic risk profile.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".