Abstract 2223: Carotid Intima Media Thickness Progression is Modest in Statin-Treated Familial Hypercholesterolemia Patients - Results from a Patient Level Meta-Analysis of 1257 Patients
Bibliographic record
Abstract
In the past, patients with heterozygous familial hypercholesterolemia (HeFH) were believed to be an ideal population to study changes in carotid intima media thickness (cIMT) based on their aggressive lipid disorder and high incidence of atherosclerotic events. However, following publication of recent cIMT trials in this population, the feasibility of demonstrating a reduction of cIMT progression in statin-treated HeFH patients has come under scrutiny. To inform future study designs, we evaluated cIMT progression and baseline predictors of cIMT progression (change in mean cIMT for all segments and common carotid artery (CCA) cIMT over 1 and 2 years), in merged data of 1257 patients from the statin arms of the ASAP, RADIANCE 1, CAPTIVATE and ENHANCE studies and performed backward regression analyses with prespecified co-variates. Based on this analysis, bootstrap analyses were performed to estimate cIMT progression for various hypothetical in- and exclusion criteria. For all studies combined, 2-year mean cIMT progression was 0.0102 ± 0.1348 mm. Positive predictors of this progression were prior use of high dose statins and use of other lipid-modifying therapy. Positive predictors of 1-year mean cIMT progression and 1 & 2 year CCA cIMT progression were age, history of hypertension, Framingham risk score, female gender, high dose statin use and history of CAD; negative predictors were screening LDL-C and ApoA-I. In simulations, HeFH patients previously taking statin and over 50 years of age had an estimated 2-year mean cIMT progression of 0.0216 ± 0.155 mm (based on n = 380). Two year progression for patients with a history of CAD or a Framingham risk score ≥ 10 would be estimated at 0.0197 ± 0.158 mm (based on n = 334). This study shows that cIMT progression in a contemporary HeFH patient population is substantially lower than anticipated, limiting the usefulness of cIMT studies to test new therapies in this population. While focus on individual subgroups characterized by population-specific predictors of cIMT progression results in slightly higher cIMT progression, the current analysis suggests that other patient populations should be considered for future cIMT studies.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.029 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".