Efficacy of Evolocumab in Monogenic vs Polygenic Hypercholesterolemia
Bibliographic record
Abstract
Background Inhibitors of proprotein convertase subtilisin kexin 9 are indicated in Canada for treatment of patients with familial hypercholesterolemia (FH). Classically, FH is considered to be a monogenic condition caused by rare pathogenic mutations; however, some patients have hypercholesterolemia on a polygenic basis. Whether the effect of proprotein convertase subtilisin kexin 9 inhibitor treatment differs between patients with monogenic hypercholesterolemia and patients with polygenic hypercholesterolemia is unclear. Methods We performed retrospective chart reviews on patients treated with evolocumab 140 mg subcutaneously biweekly from the Lipid Genetics Clinic, London Health Sciences Centre. Evolocumab-treated patients with hypercholesterolemia were grouped into monogenic or polygenic categories on the basis of their genotype determined by targeted next-generation sequencing. Absolute and relative changes in low-density lipoprotein cholesterol (LDL-C) levels before and after evolocumab treatment were studied. Results In 32 patients with monogenic heterozygous FH and 7 patients with polygenic hypercholesterolemia treated with evolocumab, absolute incremental reductions in LDL-C were 2.94 ± 1.22 mmol/L and 3.15 ± 0.90 mmol/L, respectively ( P = not significant), whereas percent reductions in LDL-C were 63.9% ± 16.0% and 67.7% ± 20.7%, respectively ( P = not significant). Conclusion Although the sample size is small, the findings suggest comparable biochemical responsiveness to evolocumab in both monogenic (heterozygous) and polygenic hypercholesterolemia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".