Rationale and design of a randomized study to assess the efficacy and safety of evolocumab in patients with diabetes and dyslipidemia: The BERSON clinical trial
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) is a major independent risk factor for cardiovascular disease, and diabetic dyslipidemia is a major contributor to cardiovascular risk in these patients. Here we report the rationale and design of a phase 3, double-blind study specifically designed to evaluate the lipid-lowering efficacy of the proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor evolocumab in patients with T2DM and hyperlipidemia or mixed dyslipidemia who are on background statin therapy. In the BERSON (evolocumaB Efficacy for LDL-C Reduction in subjectS with T2DM On background statiN) trial, patients with T2DM, a screening low-density lipoprotein cholesterol (LDL-C) level of ≥ 2.6 mmol/L (≥100 mg/dL) or ≥ 3.4 mmol/L (≥130 mg/dL), and with or without statin treatment at screening, respectively, were enrolled and started on atorvastatin 20 mg/day for a lipid stabilization period of at least 4 weeks. Then, patients were randomly assigned in a 2:2:1:1 ratio to receive atorvastatin 20 mg once daily plus either evolocumab 140 mg every 2 weeks (Q2W), evolocumab 420 mg every month (QM), placebo Q2W, or placebo QM. The co-primary outcome measures were the percentage change from baseline in LDL-C at week 12 and the percentage change from baseline in LDL-C at the mean of weeks 10 and 12. The BERSON trial has completed enrollment. The study completed in the first half of 2018, and will provide information on the efficacy and safety of evolocumab in patients with T2DM and dyslipidemia.
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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 | 0.061 | 0.038 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".