Adoption of New Glucose-Lowering Medications in the U.S.—The Case of SGLT2 Inhibitors: Nationwide Cohort Study
Open accessAbstract
Background: High-quality diabetes care is evidence-based, timely, and equitable. Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are the most recently approved class of glucose-lowering medications with additional cardio- and renal-protective benefits and low risk of hypoglycemia. Cardiovascular and kidney disease are among the most common chronic diabetes complications, whereas hypoglycemia is the most prevalent adverse effect of glucose-lowering therapy. We examine the sociodemographic and clinical factors associated with early SGLT2i initiation and appropriateness of use based on contemporaneous scientific evidence. Materials and Methods: Retrospective analysis of medical and pharmacy claims data from OptumLabs ® Data Warehouse for commercially insured and Medicare Advantage adult beneficiaries with diabetes types 1 and 2, who filled any glucose-lowering medication between January 1, 2013 and December 31, 2016. Demographic (age, sex, race, income), clinical (comorbidities), and insurance-related factors affecting first prescription for a SGLT2i were examined using multivariable logistic regression. Results: Among 1,054,727 adults with pharmacologically treated diabetes, 7.2% ( n = 75,500) initiated a SGLT2i. Patients with prior myocardial infarction (MI) (odds ratio [OR]: 0.94, 95% confidence interval [CI]: 0.91–0.96), heart failure (HF) (OR: 0.93, 95% CI: 0.91–0.94), kidney disease (OR: 0.80, 95% CI: 0.78–0.81), and severe hypoglycemia (OR: 0.96, 95% CI: 0.94–0.98) were all less likely to start a SGLT2i; P < 0.001 for all. SGLT2i were also less likely to be started by patients ≥75 years (OR: 0.57, 95% CI: 0.55–0.59, vs. 18–44 years), Black patients (OR: 0.93, 95% CI: 0.91–0.95, vs. White), and those with Medicare Advantage insurance (OR: 0.63, 95% CI: 0.62–0.64, vs. commercial). Conclusions: Younger, healthier, non-Black patients with commercial health insurance were most likely to start taking SGLT2i. Patients with MI, HF, kidney disease, and prior hypoglycemia were less likely to use SGLT2i, despite evidence supporting their preferential use in these patients. Efforts to address this treatment-risk paradox may help improve health outcomes among patients with type 2 diabetes.
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SGLT2i and GLP1ra are widely endorsed by clinical practice guidelines.
“Sodium-glucose co-transporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1ra) are novel classes of medications for type 2 diabetes that significantly reduce cardiovascular deaths independent of their effect on hyperglycemia and are widely endorsed by clinical practice guidelines.4–11”
From Disparities in Use of Novel Diabetes Medications by Insurance: A Nationally Representative Cohort Study (2024) · cites this paper as [6]
The Introduction (page unavailable) says several clinical guidelines recommend SGLT2i use in select clinical contexts, and the Discussion describes their recommendation as second-line agents. The paper does not say that GLP-1 receptor agonists are guideline-endorsed, so it supports only the SGLT2i portion of the attributed claim. (LLM, conf=0.87)
Experimental — accuracy not yet measuredSGLT2i and GLP1ra significantly reduce cardiovascular deaths independent of their effect on hyperglycemia.
“Sodium-glucose co-transporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1ra) are novel classes of medications for type 2 diabetes that significantly reduce cardiovascular deaths independent of their effect on hyperglycemia and are widely endorsed by clinical practice guidelines.4–11”
From Disparities in Use of Novel Diabetes Medications by Insurance: A Nationally Representative Cohort Study (2024) · cites this paper as [6]
The Introduction (page unavailable) reports improved cardiovascular outcomes with SGLT2 inhibitors and says guidelines recommend their use in selected clinical contexts. It does not establish a significant reduction in cardiovascular deaths independent of glucose lowering, or make that claim for GLP-1 receptor agonists, which the Discussion mentions only as a comparator class. (LLM, conf=0.86)
Experimental — accuracy not yet measuredUse of SGLT2 inhibitors and GLP-1 receptor agonists is paradoxically lower among patients with evidence of or increased risk factors for cardiovascular disease.
“Despite these recommendations, data from studies in the clinical setting show that use of these newer drug classes have been paradoxically lower among patients with evidence of, or increased risk factors for, CVD.3,4,5,6”
From Evaluation of Out-of-Pocket Costs and Treatment Intensification With an SGLT2 Inhibitor or GLP-1 RA in Patients With Type 2 Diabetes and Cardiovascular Disease (2023) · cites this paper as [6]
The Discussion reports that patients with CVD or heart failure were among those least likely to initiate SGLT2 inhibitors, supporting the treatment-risk paradox for that class. This study examines SGLT2 inhibitor initiation, not whether GLP-1 receptor agonist use was lower in patients with CVD or its risk factors; it therefore does not support that part of the claim. (LLM, conf=0.89)
Experimental — accuracy not yet measured
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“Several prior studies in patients without CKD have demonstrated lower use of these agents among Black patients.(18,24,25) Similar to our finding, studies have shown that racial disparity persists at all levels of social economic status.”
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- Authors
- McCoy, R. G., Dykhoff, H. J., Sangaralingham, L., Ross, J. S., Karaca-Mandic, P., Montori, V. M., & Shah, N. D.
- Affiliations
- Mayo Clinic (US)
- Yale New Haven Hospital (US)
- Carlson School of Management, University of Minnesota, Minneapolis, Minnesota.
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine, Mayo Clinic, Rochester, Minnesota.
- Corresponding author
- McCoy, Rozalina G.
- Venue
- Diabetes Technology & Therapeutics
- Publisher
- SAGE Publications
- Published
- 2019-11-22
- Volume
- 21
- Issue
- 12
- Pages
- 702-712
- ISSN
- 1520-9156 (ISSN-L)
- 1557-8593
- PMC
- PMC7207017
- OpenAlex
- W2967214797
- Cited by
- 122
- References
- 57
- Citations by year
- 2026: 9 · 2025: 12 · 2024: 16 · 2023: 15 · 2022: 28 · 2021: 26 · 2020: 16
- FWCI
- 14.20
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Diabetes Technology & Therapeutics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Mayo Clinic
- U.S. Food and Drug Administration (U01 FD004585, U01FD005938)
- Agency for Healthcare Research and Quality (R03 HS025517, U19 HS024075, R01 HS025402, R01 HS025164, R01HS022882)
- National Institute on Aging (P01AG005842)
- National Heart, Lung, and Blood Institute (R56HL130496, R01HL131535)
- National Institute of Diabetes and Digestive and Kidney Diseases (K23DK114497)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Failure Treatment and Management
- Keywords
- SGLT2 inhibitors, glucose-lowering medications, diabetes mellitus, racial disparities, socioeconomic disparities, older adults, heart failure, kidney disease, myocardial infarction, severe hypoglycemia, commercially insured patients, Medicare Advantage, prescribing patterns, evidence-based prescribing, health equity, health care access
- MeSH terms
- Canagliflozin, Sodium-Glucose Transporter 2 Inhibitors, Adult, Age Factors, Aged, Benzhydryl Compounds, Diabetes Mellitus, Type 2, Female, Glucosides, Medicare, Humans, Hypoglycemic Agents, Male, Middle Aged, Practice Patterns, Physicians', Drug Prescriptions, Retrospective Studies, United States, Cohort Studies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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