A Case Series Assessing the Effects of Lomitapide on Carotid Intima-Media Thickness in Adult Patients with Homozygous Familial Hypercholesterolaemia in a Real-World Setting
Bibliographic record
Abstract
INTRODUCTION: Homozygous familial hypercholesterolaemia (HoFH) is characterised by extremely elevated levels of low-density lipoprotein cholesterol (LDL-C) and results from multiple mutations in genes affecting the LDL receptor pathway. Patients are at risk of premature atherosclerotic cardiovascular disease (ASCVD) and premature death. Lomitapide is a microsomal triglyceride transfer protein inhibitor developed to treat HoFH, but cardiovascular outcome data are lacking. METHODS: We evaluated detailed data from five HoFH patients and one patient with heterozygous FH (HeFH) and a very severe phenotype. We also analysed confirmatory data from a further 8 HoFH cases. In total, we analysed data from patients in seven global centres in six countries who were all treated with lomitapide with long-term follow-up. Carotid intima-media thickness (CIMT) imaging was recorded on an ad hoc basis to monitor ASCVD in HoFH. RESULTS: Lomitapide resulted in marked decreases in LDL-C of 56.8-93.9% [77.7-93.9% in the 6 initial cases (mean nadir 64.8 ± 30.1 mg/dL); 56.8-86.0% in the 8 confirmatory cases (mean nadir 131.4 ± 38.2 mg/dL)]. CIMT regressed in 50% of cases (mean follow-up 5.0 ± 3.1 years in initial six cases, and 4.4 ± 1.4 years in confirmatory cases). In the remaining patients, CIMT showed little further change. In patients where assessments of plaque area were available, regression or stabilisation in CIMT was accompanied by clinically significant regression of plaque area. CONCLUSIONS: Lomitapide reduces LDL-C levels in patients with HoFH and severe LDL-C phenotypes, and results in stabilisation and/or regression of CIMT, which is an established marker of ASCVD risk. Additional data are needed to determine if this confers a survival benefit in these very high-risk patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".