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

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.

Graphical abstract

Figure 1

CART analysis of all baseline factors and treatment group determining the glycemic outcome by year 1 (A) and year 4 (B). A and B: Visual representation of the CART model for glycemic outcome by year separately, displayed as a “decision tree” based on the values of the important predictors identified with the CART model. The following quantitative variables were included in fitting the CART model: age, fasting glucose, BMI, waist-to-hip ratio, systolic blood pressure, diastolic blood pressure, triglycerides, HDL, eGFR, diabetes duration, HbA_1c, SEVLT score, DSST score, WFT Letter F/P score, WFT Animal category score, IGI, and Matsuda index. The following categorical variables were included in fitting the CART model: treatment group, sex, race (Black, White, others), Hispanic ethnicity, education, income, marital status (married/living together vs. other), hypertension, ACR >30 mg/g, smoking status (never, past, current), DSPN, alcohol use (never, occasionally, weekly, daily), and depression/medications.