Effects of semaglutide on risk of cardiovascular events across a continuum of cardiovascular risk: combined post hoc analysis of the SUSTAIN and PIONEER trials
Bibliographic record
Abstract
BACKGROUND: Semaglutide is a glucagon-like peptide-1 (GLP-1) analog treatment for type 2 diabetes (T2D) available in subcutaneous (s.c.) and oral formulations. Two cardiovascular (CV) outcomes trials showed that in subjects with T2D at high risk of CV events there were fewer major adverse CV events (MACE; defined as CV death, non-fatal stroke, non-fatal myocardial infarction) with semaglutide than with placebo (hazard ratio [95% CI]: 0.74 [0.58;0.95] for once-weekly s.c. semaglutide and 0.79 [0.57;1.11] for once-daily oral semaglutide). However, there is little evidence for an effect of semaglutide on MACE in subjects not at high risk of CV events. This post hoc analysis examined CV effects of semaglutide in subjects across a continuum of baseline CV risk. METHODS: Data from the s.c. (SUSTAIN) and oral (PIONEER) semaglutide phase 3a clinical trial programs were combined according to randomized treatment (semaglutide or comparators) and analyzed to assess time to first MACE and its individual components. A CV risk model was developed with independent data from the LEADER trial (liraglutide vs placebo), considering baseline variables common to all datasets. Semaglutide data were analyzed to assess effects of treatment as a function of CV risk predicted using the CV risk prediction model. RESULTS: The CV risk prediction model performed satisfactorily when applied to the semaglutide data set (area under the curve: 0.77). There was a reduced relative and absolute risk of MACE for semaglutide vs comparators across the entire continuum of CV risk. While the relative risk reduction tended to be largest with low CV risk score, the largest absolute risk reduction was for intermediate to high CV risk score. Similar results were seen for relative risk reduction of the individual MACE components and also when only placebo comparator data were included. CONCLUSION: Semaglutide reduced the risk of MACE vs comparators across the continuum of baseline CV risk in a broad T2D population. Trial registrations ClinicalTrials.gov identifiers: NCT02054897, NCT01930188, NCT01885208, NCT02128932, NCT02305381, NCT01720446, NCT02207374, NCT02254291, NCT02906930, NCT02863328, NCT02607865, NCT02863419, NCT02827708, NCT02692716, NCT02849080, NCT03021187, NCT03018028, NCT03015220.
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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 | 0.039 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.018 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| 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".