The FGF21 analog pegozafermin in severe hypertriglyceridemia: a randomized phase 2 trial
Bibliographic record
Abstract
Abstract Pegozafermin, a long-acting glycopegylated analog of human fibroblast growth factor 21, is in development for the treatment of severe hypertriglyceridemia (SHTG) and nonalcoholic steatohepatitis. Here we report the results of a phase 2, double-blind, randomized, five-arm trial testing pegozafermin at four different doses ( n = 67; 52 male) versus placebo ( n = 18; 12 male) for 8 weeks in patients with SHTG (triglycerides (TGs), ≥500 mg dl −1 and ≤2,000 mg dl −1 ). Treated patients showed a significant reduction in median TGs for the pooled pegozafermin group versus placebo (57.3% versus 11.9%, difference versus placebo −43.7%, 95% confidence interval (CI): −57.1%, −30.3%; P < 0.001), meeting the primary endpoint of the trial. Reductions in median TGs ranged from 36.4% to 63.4% across all treatment arms and were consistent regardless of background lipid-lowering therapy. Results for secondary endpoints included significant decreases in mean apolipoprotein B and non-high-density lipoprotein cholesterol concentrations (−10.5% and −18.3% for pooled doses compared to 1.1% and −0.6% for placebo (95% CI: −21.5%, −2.0%; P = 0.019 and 95% CI: −30.7%, −5.1%; P = 0.007, respectively), as well as a significant decrease in liver fat fraction for pooled treatment ( n = 17) versus placebo ( n = 6; −42.2% pooled pegozafermin, −8.3% placebo; 95% CI: −60.9%, −8.7%; P = 0.012), as assessed in a magnetic resonance imaging sub-study. No serious adverse events were observed to be related to the study drug. If these results are confirmed in a phase 3 trial, pegozafermin could be a promising treatment for SHTG (ClinicalTrials.gov registration: NCT0441186).
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".