Evinacumab in severe hypertriglyceridemia with or without lipoprotein lipase pathway mutations: a phase 2 randomized trial
Bibliographic record
Abstract
Abstract Severe hypertriglyceridemia (sHTG) is an established risk factor for acute pancreatitis. Current therapeutic approaches for sHTG are often insufficient to reduce triglycerides and prevent acute pancreatitis. This phase 2 trial ( NCT03452228 ) evaluated evinacumab (angiopoietin-like 3 inhibitor) in three cohorts of patients with sHTG: cohort 1, familial chylomicronemia syndrome with bi-allelic loss-of-function lipoprotein lipase (LPL) pathway mutations ( n = 17); cohort 2, multifactorial chylomicronemia syndrome with heterozygous loss-of-function LPL pathway mutations ( n = 15); and cohort 3, multifactorial chylomicronemia syndrome without LPL pathway mutations ( n = 19). Fifty-one patients (males, n = 27; females, n = 24) with a history of hospitalization for acute pancreatitis were randomized 2:1 to intravenous evinacumab 15 mg kg −1 or placebo every 4 weeks over a 12-week double-blind treatment period, followed by a 12-week single-blind treatment period. The primary end point was the mean percent reduction in triglycerides from baseline after 12 weeks of evinacumab exposure in cohort 3. Evinacumab reduced triglycerides in cohort 3 by a mean (s.e.m.) of −27.1% (37.4) (95% confidence interval −71.2 to 84.6), but the prespecified primary end point was not met. No notable differences in adverse events between evinacumab and placebo treatment groups were seen during the double-blind treatment period. Although the primary end point of a reduction in triglycerides did not meet the prespecified significance level, the observed safety and changes in lipid and lipoprotein levels support the further evaluation of evinacumab in larger trials of patients with sHTG. Trial registration number: ClinicalTrials.gov NCT03452228 .
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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) | 0.002 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".