Association of Baseline Factors With Glycemic Outcomes in GRADE: A Comparative Effectiveness Randomized Clinical Trial

W Timothy Garvey, Department of Nutrition Sciences, University of Alabama at Birmingham, Birmingham, AL.
Robert M. Cohen, Division of Endocrinology, Diabetes, and Metabolism, University of Cincinnati College of Medicine and Cincinnati VA Medical Center, Cincinnati, OH.
Nicole M. Butera, The Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Rockville, MD.
Erin J. Kazemi, The Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Rockville, MD.
Naji Younes, The Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Rockville, MD.
Samuel P. Rosin, The Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Rockville, MD.
Colleen E. Suratt, The Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Rockville, MD.
Andrew Ahmann, Division of Endocrinology, Diabetes and Clinical Nutrition, Oregon Health and Science University, Portland, OR.
Priscilla A. Hollander, Baylor Scott & White Research Institute, Dallas, TX.
Jonathan Krakoff, Southwestern American Indian Center, Phoenix, AZ.
Catherine L. Martin, Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
Elizabeth Seaquist, Division of Diabetes and Endocrinology, Department of Medicine, University of Minnesota, Minneapolis, MN.
Michael W. Steffes, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN.
John M. Lachin, The Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Rockville, MD.

Document Type

Journal Article

Publication Date

4-1-2024

Journal

Diabetes care

Volume

47

Issue

4

DOI

10.2337/dc23-1782

Abstract

OBJECTIVE: To describe the individual and joint associations of baseline factors with glycemia, and also with differential effectiveness of medications added to metformin. RESEARCH DESIGN AND METHODS: Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE) participants (with type 2 diabetes diagnosed for <10 years, on metformin, and with HbA1c 6.8-8.5%; N = 5,047) were randomly assigned to a basal insulin (glargine), sulfonylurea (glimepiride), glucagon-like peptide 1 agonist (liraglutide), or dipeptidyl peptidase 4 inhibitor (sitagliptin). The glycemic outcome was HbA1c ≥7.0%, subsequently confirmed. Univariate and multivariate regression and classification and regression tree (CART) analyses were used to assess the association of baseline factors with the glycemic outcome at years 1 and 4. RESULTS: In univariate analyses at baseline, younger age (<58 years), Hispanic ethnicity, higher HbA1c, fasting glucose, and triglyceride levels, lower insulin secretion, and relatively greater insulin resistance were associated with the glycemic outcome at years 1 and/or 4. No factors were associated with differential effectiveness of the medications by year 4. In multivariate analyses, treatment group, younger age, and higher baseline HbA1c and fasting glucose were jointly associated with the glycemic outcome by year 4. The superiority of glargine and liraglutide at year 4 persisted after multiple baseline factors were controlled for. CART analyses indicated that failure to maintain HbA1c <7% by year 4 was more likely for younger participants and those with baseline HbA1c ≥7.4%. CONCLUSIONS: Several baseline factors were associated with the glycemic outcome but not with differential effectiveness of the four medications. Failure to maintain HbA1c <7% was largely driven by younger age and higher HbA1c at baseline. Factors that predict earlier glycemic deterioration could help in targeting patients for more aggressive management.

Department

Biostatistics and Bioinformatics

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