Multinational Patterns of Second-line Anti-hyperglycemic Drug Initiation Across Cardiovascular Risk Groups: A Federated Pharmacoepidemiologic Evaluation in LEGEND-T2DM
Bibliographic record
Abstract
ABSTRACT Objectives To assess the uptake of second-line antihyperglycemic agents among patients with type-2 diabetes mellitus (T2DM) receiving metformin. Design Serial cross-sectional study (2011-2021). Setting Ten US and seven non-US electronic health record and administrative claims databases in the Observational Health Data Sciences and Informatics network. Participants 4.8 million patients with T2DM receiving metformin. Main Outcomes Measures Calendar-year trends in the proportional initiation of second-line antihyperglycemic agents, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), sodium-glucose cotransporter 2 inhibitors (SGLT2is), dipeptidyl peptidase-4 inhibitors, and sulfonylureas, for each database. We also evaluated the relative drug class-level uptake across cardiovascular risk groups. Results We identified 4.6 million patients with T2DM in US databases, 61,382 from Spain, 32,442 from Germany, 25,173 from the UK, 13,270 from France, 5,580 from Scotland, 4,614 from Hong Kong, and 2,322 from Australia. During 2011-2021, the combined proportional initiation of cardioprotective antihyperglycemic agents, GLP-1 RAs and SGLT2is, increased across all data sources, with the combined initiation of these drugs as second-line agents in 2021 ranging from 35.2% to 68.2% in the US databases, 15.4% in France, 34.7% in Spain, 50.1% in Germany, and 54.8% in Scotland. From 2016 to 2021, in some US and non-US databases, uptake of GLP-1 RAs and SGLT2is increased more significantly among populations without cardiovascular disease compared to those with established cardiovascular disease, without any data source providing evidence of a greater increase in their uptake in the populations with cardiovascular disease. Conclusions Despite the increase in overall uptake of cardioprotective antihyperglycemic agents as second-line treatment for T2DM, their uptake was lower in patients with cardiovascular disease over the last decade. A strategy to ensure medication use concordant with guideline recommendations is essential to improve outcomes of patients with T2DM.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".