Evidence map›Paper›PMID 42229813›Full record

Observational studyOphthalmology2026

Semaglutide and Neovascular Age-Related Macular Degeneration among Adults with Type 2 Diabetes: An Observational Health Data Sciences and Informatics Network Study.

Cindy X Cai, Brian Toy, Benjamin Martin, Ruochong Fan, Erik Westlund, Diep Tran, Akihiko Nishimura, Haeun Lee, Theodore Leng, Paul Nagy and 37 more

Abstract readObservational Study
In one paragraph

Observational study in Ophthalmology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

47 authors.

Cindy X CaiWilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland; Biomedical Informatics and Data Science, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland. Electronic address: ccai6@jhmi.edu.
Brian ToyRoski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, California.
Benjamin MartinBiomedical Informatics and Data Science, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Ruochong FanInstitute for Informatics, Data Science and Biostatistics, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri.
Erik WestlundDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Diep TranWilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland.
Akihiko NishimuraDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Haeun LeeBiomedical Informatics and Data Science, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Theodore LengByers Eye Institute at Stanford, Stanford University School of Medicine, Palo Alto, California.
Paul NagyBiomedical Informatics and Data Science, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Nestoras MathioudakisDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Linying ZhangInstitute for Informatics, Data Science and Biostatistics, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri.
Michelle HribarOphthalmology and Visual Sciences, AI.Health4All College of Medicine, University of Illinois at Chicago, Chicago, Illinois.
Aiyin ChenCasey Eye Institute, Oregon Health and Science University, Portland, Oregon; Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, Oregon.
Karen ArmbrustDepartment of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, Minnesota; Department of Ophthalmology, Minneapolis Veterans Affairs Health Care System, Minneapolis, Minnesota.
Kerry GoetzDepartment of Clinical Science, Topcon Healthcare, Inc., Oakland, New Jersey.
Sally BaxterViterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California, San Diego, La Jolla, California; Division of Biomedical Informatics, Department of Medicine, University of California, San Diego, La Jolla, California.
Michael V BolandDepartment of Ophthalmology, Mass Eye and Ear and Harvard Medical School, Boston, Massachusetts.
Eric N BrownVanderbilt Eye Institute, Vanderbilt University Medical Center, Nashville, Tennessee.
Edmund TsuiUCLA Stein Eye Institute, University of California, Los Angeles, Los Angeles, California.
Andrew J BarkmeierDepartment of Ophthalmology, Mayo Clinic, Rochester, Minnesota.
Sophia WangByers Eye Institute at Stanford, Stanford University School of Medicine, Palo Alto, California.
Nitish MehtaDepartment of Ophthalmology, NYU Langone Health, New York, New York.
Jacqueline C StockingDepartment of Internal Medicine, University of California, Davis, Sacramento, California.
Ghazala O'KeefePrivate Practice.
Cecilia S LeeJohn F. Hardesty, MS, Department of Ophthalmology and Visual Sciences, Washington University in St. Louis, St. Louis, Missouri.
Philip R O PayneInstitute for Informatics, Data Science and Biostatistics, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri.
William J O'BrienVeterans Affairs Informatics and Computing Infrastructure, George E. Wahlen VA Medical Center, Salt Lake City, Utah.
Scott DuVallData Science and Advanced Analytics, PurpleLab, Inc., Salt Lake City, Utah.
Thamir AlshammariDepartment of Clinical Practice, College of Pharmacy, Jazan University, Jazan, Saudi Arabia; Pharmacy Practice Research Unit, College of Pharmacy, Jazan University, Jazan, Saudi Arabia.
Thomas FalconerDepartment of Biomedical Informatics, Columbia University, New York, New York.
David A DorrDivision of Informatics, Clinical Epidemiology, and Translational Data Science, Department of Medicine, Oregon Health and Science University, Portland, Oregon.
Izabelle HumesOregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, Oregon.
David McCoyOregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, Oregon.
Mohammed AdibuzzamanOregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, Oregon.
Rumel MahmoodOregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, Oregon.
Hannah Morgan-CooperStanford School of Medicine and Stanford Health Care, Palo Alto, California.
Priya DesaiStanford School of Medicine and Stanford Health Care, Palo Alto, California.
Shikha Yashwant KothariStanford School of Medicine and Stanford Health Care, Palo Alto, California.
Anthony SenaGlobal Epidemiology Organization, Johnson & Johnson, Raritan, New Jersey; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
Clair BlacketerGlobal Epidemiology Organization, Johnson & Johnson, Raritan, New Jersey; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
Anna OstropoletsDepartment of Biomedical Informatics, Columbia University, New York, New York; Global Epidemiology Organization, Johnson & Johnson, Raritan, New Jersey.
Azza ShoaibiGlobal Epidemiology Organization, Johnson & Johnson, Raritan, New Jersey.
Gowtham RaoResearch Department, CoReason, Inc, Princeton, New Jersey.
George HripcsakDepartment of Biomedical Informatics, Columbia University, New York, New York.
Patrick RyanDepartment of Biomedical Informatics, Columbia University, New York, New York; Global Epidemiology Organization, Johnson & Johnson, Raritan, New Jersey.
Marc A SuchardDepartment of Biostatistics, UCLA School of Public Health, University of California, Los Angeles, Los Angeles, California; VA Informatics and Computing Infrastructure, US Department of Veterans Affairs, Salt Lake City, Utah.

Funding

Aging eyes and aging brains in studying alzheimer's disease: Modern ophthalmic data collection in the adult changes in thought (ACT) studyR01AG060942 · NIA · WASHINGTON UNIVERSITY · PI Cecilia Sungmin Lee · 2019 to 2026
$39.4M
Bridge2AI:Salutogenesis Data Generation ProjectOT2OD032644 · OD · WASHINGTON UNIVERSITY · PI BAXTER, SALLY LIU, CHUTE, CHRISTOPHER G · 2022 to 2025
$32.7M
Vision BiostatisticsP30EY022589 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Derek Stuart Welsbie · 2012 to 2026
$10.3M
Supplement to Effectiveness of Digital Versus In-Person Diabetes Prevention ProgramsR01DK125780 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI MATHIOUDAKIS, NESTORAS N · 2020 to 2023
$3.0M
Real-world Evidence to Inform Decisions for Hypertension Treatment EscalationR01HL169954 · NHLBI · YALE UNIVERSITY · PI Yuan Lu · 2023 to 2026
$2.6M
Translating Personalized Inference from Randomized Clinical Trials to Real-World Cardiovascular CareR01HL167858 · NHLBI · YALE UNIVERSITY · PI Rohan Khera · 2024 to 2026
$2.3M
Implementation of a diabetes navIgator to Mitigate disPArities and improve CGM upTake and sustained use across the lifespan of T1D (IMPACT T1D)R01DK134955 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI MATHIOUDAKIS, NESTORAS N, WOLF, RISA MICHELLE · 2022 to 2025
$1.8M
Impact of Social Determinants of Health in Diabetic RetinopathyK23EY033440 · NEI · JOHNS HOPKINS UNIVERSITY · PI Cindy Xinji Cai · 2022 to 2026
$1.1M
Towards precision risk stratification, diagnosis, and treatment: statistical and computational machinery for synthesizing information across massive, diverse sources of genomic and clinical dataR35GM160458 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Akihiko Nishimura · 2025 to 2026
$854k
Investigating the Development, Persistence, and Progression of Uveitis and Ocular Inflammation in the United StatesK23EY032985 · NEI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOY, BRIAN · 2021 to 2025
$820k
NEI NIH HHS K23 EY032985NEI NIH HHS K23 EY033440NEI NIH HHS P30 EY022589NHLBI NIH HHS R01 HL167858NHLBI NIH HHS R01 HL169954NIA NIH HHS R01 AG060942NIDDK NIH HHS R01 DK125780NIDDK NIH HHS R01 DK134955NIGMS NIH HHS R35 GM160458NIH HHS OT2 OD032644
6 · The paper itself

Abstract

purposeTo investigate the potential association of semaglutide use and neovascular age-related macular degeneration (NVAMD).

designRetrospective study across 12 databases in the Observational Health Data Sciences and Informatics network from December 1, 2017, through December 31, 2024.

participantsAdults with type 2 diabetes (T2D) taking semaglutide, other glucagon-like peptide-1 receptor agonists (GLP-1RAs; e.g., dulaglutide or exenatide), or non-GLP-1RAs (e.g., empagliflozin, sitagliptin, or glipizide).

methodsThe association between semaglutide use and NVAMD was assessed using 2 approaches: an active-comparator cohort design and a self-controlled case series analysis. The former used propensity score-adjusted Cox proportional hazards models to estimate hazard ratios (HRs). The latter used conditional Poisson regression models to estimate incidence rate ratios (IRRs). A random-effects meta-analysis was used to generate network-wide HR and IRR estimates.

main outcome measuresTwo definitions of NVAMD, one based on condition codes alone (NVAMD-C) and one based on condition codes and procedures (NVAMD-CP).

resultsA total of 227 971 new users of semaglutide were included in the study. The risk of NVAMD among semaglutide users was similar to that of users of dulaglutide (NVAMD-C: HR, 0.57; 95% CI, 0.21-1.57; P = 0.28; NVAMD-CP: HR, 0.25; 95% CI, 0.05-1.27; P = 0.10), empagliflozin (NVAMD-C: HR, 0.98; 95% CI, 0.54-1.79; P = 0.94; NVAMD-CP: HR, 0.79; 95% CI, 0.38-1.64; P = 0.52), sitagliptin (NVAMD-C: HR, 2.08; 95% CI, 0.90-4.83; P = 0.09; NVAMD-CP: HR, 1.80; 95% CI, 0.55-5.86; P = 0.33), and glipizide (NVAMD-C: HR, 0.83; 95% CI, 0.35-2.02; P = 0.69; NVAMD-CP: HR, 0.50; 95% CI, 0.21-1.19; P = 0.12). No evidence was found of increased or decreased risk for NVAMD associated with semaglutide exposure (NVAMD-C: IRR, 0.92; 95% CI, 0.67-1.26; P = 0.60; NVAMD-CP: IRR, 1.02; 95% CI, 0.76-1.36; P = 0.92) nor with any of the other GLP-1RAs or non-GLP-1RAs.

conclusionsWe detected no differences in the risk of NVAMD associated with semaglutide use among adults with T2D. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Diabetes Mellitus, Type 2Glucagon-Like PeptidesHypoglycemic AgentsWet Macular DegenerationAgedFemaleHumansImmunoglobulin Fc FragmentsIncidenceMaleMiddle AgedRetrospective StudiesSemaglutideGlucagon-Like PeptidesHypoglycemic AgentsImmunoglobulin Fc FragmentsSemaglutideBig dataNeovascular age-related macular degenerationObservational Health Data Sciences and InformaticsSemaglutide

Identifiers

PMID42229813
PMCPMC13318194

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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 OpenQuestion graph.