Multinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM
Rohan Khera,
Jing Li,
Katherine Simon,
Yuan Lu,
Joseph S Ross,
Talita Duarte-Salles,
Michael E Matheny,
Harlan Krumholz,
Kenneth KC Man,
Carlen Reyes,
Paul Nagy,
Nigam Shah,
Martijn J Schuemie,
Daniel R Morales,
Scott L DuVall,
Seng Chan You,
Jose D Posada,
George Hripcsak,
Marc A Suchard,
Patrick B Ryan,
Anna Ostropolets,
Michael Cook,
Evan Minty,
Andrea Pistillo,
Clair Blacketer,
Arya Aminorroaya,
Thomas Falconer,
Nestoras Mathioudakis,
Jin J Zhou,
Can Yin,
Kelly Li,
Lovedeep Singh Dhingra,
Faaizah Arshad,
Mary G Bowring,
Fan Bu,
David A Dorr,
Tina E French,
Elizabeth E Hanchrow,
Scott Horban,
Wallis CY Lau,
Yuntian Liu,
Michael F McLemore,
Akihiko Nishimura,
Nicole Pratt,
Sarah Seager,
Eric YF Wan,
Jianxiao Yang
Affiliations
Rohan Khera
Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
Jing Li
Department of Infectious Diseases and Hepatology, The Second Hospital of Shandong University, Jinan, China
Katherine Simon
Research, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
Yuan Lu
Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
Joseph S Ross
professor
Talita Duarte-Salles
Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
Michael E Matheny
Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
Harlan Krumholz
Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
Kenneth KC Man
Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK
Carlen Reyes
Fundació Institut Universitari per a la Recerca a l`Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
Paul Nagy
Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Nigam Shah
Center for Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA, USA
Martijn J Schuemie
Epidemiology, Office of the Chief Medical Officer, Johnson & Johnson, Titusville, NJ, USA
Daniel R Morales
clinical research fellow
Scott L DuVall
Veterans Affairs Informatics and Computing Infrastructure, United States Department of Veterans Affairs, Salt Lake City, UT, USA
Seng Chan You
Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea (aka South Korea)
Jose D Posada
Systems Engineering and Computing, School of Engineering, Universidad del Norte, Barranquilla, Colombia
George Hripcsak
Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
Marc A Suchard
Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
Patrick B Ryan
Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
Anna Ostropolets
Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
Michael Cook
1The University of Manchester, Arthritis Research UK Centre for Epidemiology, Centre for Musculoskeletal Research, Manchester, United Kingdom
Evan Minty
Faculty of Medicine, O`Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada
Andrea Pistillo
IDIAP Jordi Gol, Barcelona, Catalunya, Spain
Clair Blacketer
Observational Health Data Analytics, Janssen Research and Development, Titusville, NJ, USA
Arya Aminorroaya
Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
Thomas Falconer
Department of Biomedical Informatics, Columbia University, New York, NY, USA
Nestoras Mathioudakis
Division of Endocrinology, Diabetes, and Metabolism, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
Jin J Zhou
Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
Can Yin
Data Transformation, Analytics, and Artificial Intelligence, Real World Solutions, IQVIA Inc, Durham, NC, USA
Kelly Li
Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
Lovedeep Singh Dhingra
Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
Faaizah Arshad
Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
Mary G Bowring
Johns Hopkins University School of Medicine, Baltimore, MD, USA
Fan Bu
Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
David A Dorr
Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University School of Medicine, Portland, OR, USA
Tina E French
Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
Elizabeth E Hanchrow
Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
Scott Horban
Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
Wallis CY Lau
Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK
Yuntian Liu
Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, CT, USA
Michael F McLemore
Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
Akihiko Nishimura
Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
Nicole Pratt
Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia
Sarah Seager
Data Transformation, Analytics, and Artificial Intelligence, Real World Solutions, IQVIA Inc, Durham, NC, USA
Eric YF Wan
Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
Jianxiao Yang
Department of Computational Medicine, University of California Los Angeles David Geffen School of Medicine, Los Angeles, CA, USA
Objective To assess the uptake of second line antihyperglycaemic drugs among patients with type 2 diabetes mellitus who are receiving metformin.Design Federated pharmacoepidemiological evaluation in LEGEND-T2DM.Setting 10 US and seven non-US electronic health record and administrative claims databases in the Observational Health Data Sciences and Informatics network in eight countries from 2011 to the end of 2021.Participants 4.8 million patients (≥18 years) across US and non-US based databases with type 2 diabetes mellitus who had received metformin monotherapy and had initiated second line treatments.Exposure The exposure used to evaluate each database was calendar year trends, with the years in the study that were specific to each cohort.Main outcomes measures The outcome was the incidence of second line antihyperglycaemic drug use (ie, glucagon-like peptide-1 receptor agonists, sodium-glucose cotransporter-2 inhibitors, dipeptidyl peptidase-4 inhibitors, and sulfonylureas) among individuals who were already receiving treatment with metformin. The relative drug class level uptake across cardiovascular risk groups was also evaluated.Results 4.6 million patients were identified in US databases, 61 382 from Spain, 32 442 from Germany, 25 173 from the UK, 13 270 from France, 5580 from Scotland, 4614 from Hong Kong, and 2322 from Australia. During 2011-21, the combined proportional initiation of the cardioprotective antihyperglycaemic drugs (glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors) increased across all data sources, with the combined initiation of these drugs as second line drugs 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 glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors increased more significantly among populations with no cardiovascular disease compared with patients with established cardiovascular disease. No data source provided evidence of a greater increase in the uptake of these two drug classes in populations with cardiovascular disease compared with no cardiovascular disease.Conclusions Despite the increase in overall uptake of cardioprotective antihyperglycaemic drugs as second line treatments for type 2 diabetes mellitus, their uptake was lower in patients with cardiovascular disease than in people with no cardiovascular disease over the past decade. A strategy is needed to ensure that medication use is concordant with guideline recommendations to improve outcomes of patients with type 2 diabetes mellitus.
