Effects of Liraglutide on Cardiovascular Outcomes in Type 2 Diabetes Patients With and Without Baseline Metformin Use: Post Hoc Analyses of the LEADER Trial
Bibliographic record
Abstract
Glucagon-like peptide 1 receptor agonists (GLP-1RAs) reduce cardiovascular (CV) events among patients with type 2 diabetes and high CV risk. Because consensus professional society recommendations endorse metformin as the first-line medication for type 2 diabetes, the CV efficacy of GLP-1RAs has primarily been studied with background metformin therapy (1). However, the European Society of Cardiology now recommends GLP-1RAs as a first-line type 2 diabetes treatment for patients at high CV risk (2). These discordant recommendations raise the question of how background metformin might influence the CV benefits of GLP-1RAs. Using data from the LEADER trial, we sought to answer this question by exploring possible heterogeneity in the CV efficacy of liraglutide related to baseline metformin treatment (3). The Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial (NCT01179048, ClinicalTrials.gov) has been described elsewhere (3). Patients with type 2 diabetes and high CV risk underwent double-blind randomization to daily liraglutide versus placebo in addition to existing care. Each patient contributed data from randomization until censoring. The primary outcome was time from randomization to first occurrence of a composite of CV death, myocardial infarction, or stroke. Prespecified secondary outcomes included an expanded composite (primary plus coronary revascularization or hospitalization for unstable angina or heart failure), the composite components, and all-cause death. All outcomes were centrally adjudicated. Metformin treatment was identified at the baseline trial visit and each visit thereafter. Within each baseline metformin treatment subgroup, effect estimates for liraglutide versus placebo (hazard ratio [HR], 95% CI) were derived using Cox proportional hazards regression models; multivariable adjustment for baseline demographic and clinical factors was performed. Inverse probability for treatment weighting (IPTW) was used to account for imbalances in covariates between baseline metformin treatment subgroups (4). For multivariable analyses with IPTW, heterogeneity in the association between baseline metformin …
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".