Evidence mapPaperPMID 42236281Full record

Observational studyDiabetes, obesity & metabolism2026

Heterogeneity of Treatment Effects Across Nine Glucose-Lowering Drug Classes in Type 2 Diabetes: Extension of the LEGEND-T2DM Network Study.

Hsin Yi Chen, Thomas Falconer, Anna Ostropolets, Tara V Anand, Xinzhuo Jiang, David Dávila-García, Linying Zhang, Ruochong Fan, Hannah Morgan-Cooper, Marc A Suchard and 1 more

Abstract readObservational Study
In one paragraph

Observational study in Diabetes, obesity & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Hsin Yi ChenDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.ORCID https://orcid.org/0000-0002-7907-2335
Thomas FalconerDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.
Anna OstropoletsDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.
Tara V AnandDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.
Xinzhuo JiangDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.
David Dávila-GarcíaInstitute for Informatics, Data Science and Biostatistics, Washington University in St. Louis, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-9951-2270
Linying ZhangInstitute for Informatics, Data Science and Biostatistics, Washington University in St. Louis, St. Louis, Missouri, USA.
Ruochong FanInstitute for Informatics, Data Science and Biostatistics, Washington University in St. Louis, St. Louis, Missouri, USA.
Hannah Morgan-CooperStanford School of Medicine and Stanford Health Care, Palo Alto, California, USA.
Marc A SuchardDepartment of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, USA.
George HripcsakDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · COLUMBIA UNIV NEW YORK MORNINGSIDE · 1992 to 2025
$8.3M
DISCOVERING AND APPLYING KNOWLEDGE IN CLINICAL DATABASESR01LM006910 · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2000 to 2005
$2.4M
Real-world Evidence to Inform Decisions for Hypertension Treatment EscalationR01HL169954 · YALE UNIVERSITY · 2025 to 2025
$644k
Advanced Research Projects Agency for Health D24AC00345-00NHLBI NIH HHS R01 HL169954NHLBI NIH HHS R01HL169954NLM NIH HHS R01 LM006910NLM NIH HHS T15 LM007079U.S. National Library of Medicine R01LM006910U.S. National Library of Medicine T15LM007079
6 · The paper itself

Abstract

aimsUnderstanding heterogeneous responses to glucose-lowering therapies is crucial for advancing personalized treatment and optimizing outcomes in type 2 diabetes mellitus (T2DM). While average treatment effects are established for many drug classes, responses may vary by clinical and demographic factors. Here, we evaluated whether major glucose-lowering drug classes exhibit heterogeneous treatment effects (HTE) across key patient characteristics. MATERIALS AND

methodsThis large-scale observational cohort study was replicated in six data-sources across the Observational Health Data Sciences and Informatics network. New-user, active-comparator cohorts were constructed for patients with T2DM initiating one of the nine antihyperglycemic drug classes. Large-scale propensity score adjustment, empirical calibration using negative controls, and random-effects meta-analysis were used to estimate calibrated hazard ratios (HRs). HTE was assessed by comparing differences in log HRs across clinical and demographic subgroups.

resultsNominal signals of HTE were observed in the hyperlipidemia, hypertension, obesity, and sex subgroups: Biguanides (vs. DPP-4 inhibitors) were associated with lower risk of acute myocardial infarction in hyperlipidemia and heart failure hospitalization in obesity. SGLT-2 inhibitors (vs. GLP-1 receptor agonists) were associated with reduced stroke risk only in non-obese patients. Sex-specific patterns included higher risk of diarrhoea with GLP-1 receptor agonists and lower risk of stroke with SGLT-2 inhibitors (both vs. DPP-4 inhibitors) in women. None of the signals demonstrated statistical significance after multiple testing correction. Several subgroups (e.g., diabetic ketoacidosis and retinopathy) did not meet diagnostic criteria for clinical reliability and were not evaluated.

conclusionsThis hypothesis-generating study identified limited signals of HTE. These findings are exploratory and require cautious interpretation and validation.

Indexed as

Diabetes Mellitus, Type 2Hypoglycemic AgentsAgedBiguanidesBlood GlucoseCohort StudiesDipeptidyl-Peptidase IV InhibitorsFemaleGlucagon-Like Peptide-1 Receptor AgonistsHumansInsulin SecretagoguesMaleMiddle AgedSodium-Glucose Transporter 2 InhibitorsSulfonylurea CompoundsThiazolidinedionesBiguanidesBlood GlucoseDipeptidyl-Peptidase IV InhibitorsGlucagon-Like Peptide-1 Receptor AgonistsHypoglycemic AgentsInsulin SecretagoguesSodium-Glucose Transporter 2 InhibitorsSulfonylurea CompoundsThiazolidinedionescomparative effectivenessglucose‐lowering drugsheterogeneity of treatment effectobservational studypersonalized medicinereal‐world evidence

Identifiers

PMID42236281
PMCPMC13310412

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.