Abstract 16672: Effects of Evinacumab on Atherogenic Lipoproteins in Children and Adolescents From Ages 5 to 17 Years With Homozygous Familial Hypercholesterolemia
Bibliographic record
Abstract
Background: Homozygous familial hypercholesterolemia (HoFH) is characterized by severely elevated LDL-C levels from birth. Diagnosis and aggressive LDL-lowering treatment (LLT) before adulthood are essential for optimal ASCVD prevention in HoFH; however, it is often undiagnosed and undertreated in pediatric patients. Specifically, HoFH children and adolescents routinely require advanced LLT, since few achieve LDL-C goal on standard LLT. Evinacumab, a novel angiopoietin-like-3 inhibitor and advanced LLT, has an established safety profile in younger and older pediatric HoFH patients, 5-11 and 12-17 years, respectively. For the first time, we compare its lipid efficacy in these two groups. Methods: Fourteen patients ages 5-11 years (Study 17100 part B; NCT04233918) and 14 patients ages 12-17 years (Study 1719; NCT03409744), all with HoFH on stable LLT, were treated with IV evinacumab 15 mg/kg Q4W. Notably, in Study 17100 part B, no patients were taking PCSK9 inhibitors at study entry, while in Study 1719, 42.9% of patients were receiving a PCSK9 inhibitor at baseline. Apheresis use differed little, 50.0% in the younger study vs 64.3% in the older. LDL-C and other atherogenic lipoproteins were tested at baseline and 24 weeks. Results: In patients ages 5-11 years, mean (SD) baseline LDL-C was 263.7 (91.0) mg/dL and was lowered 48.3% (131.9 mg/dL) by evinacumab ( Table ). In patients ages 12-17 years, baseline LDL-C was 300.4 (100.5) mg/dL and was lowered 55.4% (180.5 mg/dL), with similar baseline and changes to those of the younger patients. In both groups, evinacumab markedly reduced ApoB, non-HDL-C, and Lp(a) ( Table ). Conclusions: Evinacumab strikingly and comparably reduces atherogenic lipids in younger and older pediatric HoFH patients. Since standard LLT rarely lowers LDL-C levels to treatment goals in pediatric HoFH, evinacumab should be strongly and urgently considered in these patients whenever further LDL-lowering is needed after optimizing standard LLT.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".