Alirocumab vs usual lipid‐lowering care as add‐on to statin therapy in individuals with type 2 diabetes and mixed dyslipidaemia: The ODYSSEY DM‐DYSLIPIDEMIA randomized trial
Bibliographic record
Abstract
AIM: To compare alirocumab, a proprotein convertase subtilisin-kexin type 9 inhibitor, with usual care (UC) in individuals with type 2 diabetes (T2DM) and mixed dyslipidaemia not optimally managed by maximally tolerated statins in the ODYSSEY DM-DYSLIPIDEMIA trial (NCT02642159). MATERIALS AND METHODS: The UC options (no additional lipid-lowering therapy; fenofibrate; ezetimibe; omega-3 fatty acid; nicotinic acid) were selected prior to stratified randomization to open-label alirocumab 75 mg every 2 weeks (with increase to 150 mg every 2 weeks at week 12 if week 8 non-HDL cholesterol concentration was ≥2.59 mmol/L [100 mg/dL]) or UC for 24 weeks. The primary efficacy endpoint was percentage change in non-HDL cholesterol from baseline to week 24. RESULTS: The randomized population comprised 413 individuals (intention-to-treat population, n = 409; safety population, n = 412). At week 24, the mean non-HDL cholesterol reductions were superior with alirocumab (-32.5% difference vs UC, 97.5% confidence interval -38.1 to -27.0; P < .0001). Overall, 63.6% of alirocumab-treated individuals were maintained on 75 mg every 2 weeks. Alirocumab also reduced LDL cholesterol (-43.0%), apolipoprotein B (-32.3%), total cholesterol (-24.6%) and LDL particle number (-37.8%) at week 24 vs UC (all P < .0001). Consistent with the overall trial comparison, alirocumab reduced non-HDL cholesterol to a greater degree within each UC stratum at week 24. The incidence of treatment-emergent adverse events was 68.4% (alirocumab) and 66.4% (UC). No clinically meaningful effect on glycated haemoglobin, or change in number of glucose-lowering agents, was seen. CONCLUSIONS: In individuals with T2DM and mixed dyslipidaemia on maximally tolerated statin, alirocumab showed superiority to UC in non-HDL cholesterol reduction and was generally well tolerated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".