Comparison of <scp>PCSK9</scp> Inhibitor Evolocumab vs Ezetimibe in Statin‐Intolerant Patients: Design of the Goal Achievement After Utilizing an Anti‐<scp>PCSK9</scp> Antibody in Statin‐Intolerant Subjects 3 (<scp>GAUSS</scp>‐3) Trial
Bibliographic record
Abstract
Statins are the accepted standard for lowering low-density lipoprotein cholesterol (LDL-C). However, 5% to 10% of statin-treated patients report intolerance, mostly due to muscle-related adverse effects. Challenges exist to objective identification of statin-intolerant patients. Evolocumab is a monoclonal antibody that binds proprotein convertase subtilisin/kexin type 9 (PCSK9), resulting in marked LDL-C reduction. We report the design of Goal Achievement After Utilizing an Anti-PCSK9 Antibody in Statin-Intolerant Subjects 3 (GAUSS-3), a phase 3, multicenter, randomized, double-blind, ezetimibe-controlled study to compare effectiveness of 24 weeks of evolocumab 420 mg monthly vs ezetimibe 10 mg daily in hypercholesterolemic patients unable to tolerate an effective statin dose. The study incorporates a novel atorvastatin-controlled, double-blind, crossover phase to objectively identify statin intolerance. Eligible patients had LDL-C above the National Cholesterol Education Project Adult Treatment Panel III target level for the appropriate coronary heart disease risk category and were unable to tolerate ≥3 statins or 2 statins (one of which was atorvastatin ≤10 mg/d) or had a history of marked creatine kinase elevation accompanied by muscle symptoms while on 1 statin. This trial has 2 co-primary endpoints: mean percent change from baseline in LDL-C at weeks 22 and 24 and percent change from baseline in LDL-C at week 24. Key secondary efficacy endpoints include change from baseline in LDL-C, percent of patients attaining LDL-C <70 mg/dL (1.81 mmol/L), and percent change from baseline in total cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B. Recruitment of 511 patients was completed on November 28, 2014.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".