Real‐world effectiveness of monoclonal antibody inhibitors of <scp>PCSK</scp>9 in patients with heterozygous familial hypercholesterolemia: A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Heterozygous familial hypercholesterolemia (HeFH) is a genetic condition that is associated with a high risk of atherosclerotic cardiovascular disease (ASCVD) due to elevated lipid levels. Proprotein convertase subtilisin/kexin type 9 (PCSK9) monoclonal antibody inhibitors have been shown to reduce low-density lipoprotein cholesterol (LDL-C) substantially. This study aimed to assess the real-world effectiveness of PCSK9 inhibitor therapy among patients with HeFH. METHODS: Retrospective cohort study of patients with probable or definite HeFH on a PCSK9 inhibitor at a specialized lipid clinic between 2015 and 2022. The primary objective was the proportion of patients who attained a ≥50% reduction in LDL-C after 12 months of treatment. RESULTS: In total, 141 patients were screened and 95 were included. Mean age was 63 years, 51% were female, and mean baseline LDL-C level was 4.0 mmol/L (155 mg/dL). A majority of patients (60%) had statin intolerance, and 73% were on ezetimibe. The most common PCSK9 inhibitor was evolocumab (94%). Overall, 74% of patients achieved a ≥50% reduction in LDL-C after 12 months of therapy. Mean LDL-C concentration decreased to 1.7 mmol/L (66 mg/dL) (approximately 59% reduction from baseline) after 12 months of follow-up but increased to 1.9 mmol/L (73 mg/dL) after ≥24 months of follow-up. Similar trends were observed in non-high-density lipoprotein cholesterol and apolipoprotein B. Lipoprotein(a) was significantly reduced by 45% over 12 months. Twelve percent of patients permanently discontinued therapy. Barriers to PCSK9i use were mostly related to cost. CONCLUSIONS: In a real-world cohort of HeFH patients, most of which were intolerant to statins, a high majority were able to achieve a ≥50% reduction in LDL-C after 12 months of PCSK9 inhibitor therapy (mean reduction of approximately 59%), which is similar to clinical trial data of patients with ASCVD. A significant reduction in non-high-density lipoprotein cholesterol, apolipoprotein B, and lipoprotein(a) were also observed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".