Effect of Torcetrapib on the Progression of Coronary Atherosclerosis
Bibliographic record
Abstract
BACKGROUND: Levels of high-density lipoprotein (HDL) cholesterol are inversely related to cardiovascular risk. Torcetrapib, a cholesteryl ester transfer protein (CETP) inhibitor, increases HDL cholesterol levels, but the functional effects associated with this mechanism remain uncertain. METHODS: A total of 1188 patients with coronary disease underwent intravascular ultrasonography. After treatment with atorvastatin to reduce levels of low-density lipoprotein (LDL) cholesterol to less than 100 mg per deciliter (2.59 mmol per liter), patients were randomly assigned to receive either atorvastatin monotherapy or atorvastatin plus 60 mg of torcetrapib daily. After 24 months, disease progression was measured by repeated intravascular ultrasonography in 910 patients (77%). RESULTS: After 24 months, as compared with atorvastatin monotherapy, the effect of torcetrapib-atorvastatin therapy was an approximate 61% relative increase in HDL cholesterol and a 20% relative decrease in LDL cholesterol, reaching a ratio of LDL cholesterol to HDL cholesterol of less than 1.0. Torcetrapib was also associated with an increase in systolic blood pressure of 4.6 mm Hg. The percent atheroma volume (the primary efficacy measure) increased by 0.19% in the atorvastatin-only group and by 0.12% in the torcetrapib-atorvastatin group (P=0.72). A secondary measure, the change in normalized atheroma volume, showed a small favorable effect for torcetrapib (P=0.02), but there was no significant difference in the change in atheroma volume for the most diseased vessel segment. CONCLUSIONS: The CETP inhibitor torcetrapib was associated with a substantial increase in HDL cholesterol and decrease in LDL cholesterol. It was also associated with an increase in blood pressure, and there was no significant decrease in the progression of coronary atherosclerosis. The lack of efficacy may be related to the mechanism of action of this drug class or to molecule-specific adverse effects. (ClinicalTrials.gov number, NCT00134173 [ClinicalTrials.gov].).
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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 | 0.001 |
| 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".