Abstract
AIMS: To determine which drugs were selected to be added to metformin for patients on dual anti-diabetic medication in the management of type 2 diabetes and to assess HbA1c and BMI outcomes at 6 and 12 months after the initiation of a second anti-diabetic medication.
METHODS: A retrospective chart review of electronic medical record data. Second line anti-diabetic medication added to metformin between 7/1/2012 to 8/31/2017 in the primary care practice in Fairview Health System in Minnesota.
RESULTS: 3413 patients met the selection criteria of type 2 diabetes, 18 years and older, dual anti-diabetes therapy with metformin being the first prescribed. The most frequently prescribed medications added to metformin were sulfonylurea and basal insulin accounting for 51% (1724/3413) and 37% (1268/3413) respectively. Mean HbA1c reductions at 6 and 12 months among 2134 patients with baseline and follow-up HbA1c data respectively were: GLP-1 agonist (-1.3, P < 0.001; -1.2, P < 0.001), sulfonylurea (-1.1, P < 0.001; -0.9, P < 0.001), basal insulin (-1.1, P < 0.001; -1.0, P < 0.001), DPP4 inhibitor (-0.7, P = 0.223; -0.8, P = 0.049). Patients prescribed a GLP-1 agonist had a higher mean baseline BMI (BMI =40.3 kg/m 2) and this was the only group with a statistically significant BMI reduction from baseline at 6 and 12 months (-1.5, P = 0.049 and -1.8, P = 0.041).
CONCLUSION AND RELEVANCE: Type 2 diabetes patients treated with sulfonylurea, basal insulin and GLP-1 agonist as an add on to metformin had significant reductions in HbA1c. Patients prescribed a GLP-1 agonist had a significant BMI reduction.
| Original language | English (US) |
|---|---|
| Article number | 107477 |
| Journal | Journal of Diabetes and Its Complications |
| Volume | 34 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2020 |
Bibliographical note
Funding Information:The authors would like to thank the Informatics Consulting Service of the Clinical and Translational Science Institute of the University of Minnesota and the Fairview Health services. Funding was provided by institutional funds to Dr. Seaquist. This research was supported by the National Institutes of Health 's National Center for Advancing Translational Sciences, grant UL1TR002494 . The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health's National Center for Advancing Translational Sciences.
Funding Information:
The authors declare that there are no conflicts of interest. Dr. Elizabeth Seaquist serves as a consultant for Lilly, Sanofi, MannKind, Zucara, and WebMD. The University that employs Dr. Seaquist has accepted research funding from Lilly to support her work.The authors would like to thank the Informatics Consulting Service of the Clinical and Translational Science Institute of the University of Minnesota and the Fairview Health services. Funding was provided by institutional funds to Dr. Seaquist. This research was supported by the National Institutes of Health's National Center for Advancing Translational Sciences, grant UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health's National Center for Advancing Translational Sciences.
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