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While randomized controlled trials (RCTs) are critical for establishing the efficacy of new therapies, there are limitations regarding what comparisons can be made directly from trial data. RCTs are limited to a small number of comparator arms and often compare a new therapeutic to a standard of care which has already proven efficacious. It is sometimes of interest to estimate the efficacy of the new therapy relative to a treatment that was not evaluated in the same trial, such as a placebo or an alternative therapy that was evaluated in a different trial. Such dual‐study comparisons are challenging because of potential differences between trial populations that can affect the outcome. In this article, two bridging estimators are considered that allow for comparisons of treatments evaluated in different trials, accounting for measured differences in trial populations. A "multi‐span" estimator leverages a shared arm between two trials, while a "single‐span" estimator does not require a shared arm. A diagnostic statistic that compares the outcome in the standardized shared arms is provided. The two estimators are compared in simulations, where both estimators demonstrate minimal empirical bias and nominal confidence interval coverage when the identification assumptions are met. The estimators are applied to data from the AIDS Clinical Trials Group 320 and 388 to compare the efficacy of two‐drug vs four‐drug antiretroviral therapy on CD4 cell counts among persons with advanced HIV. The single‐span approach requires weaker identification assumptions and was more efficient in simulations and the application. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To determine whether the relationship between average glucose (AG) levels and hemoglobin A1c (HbA1c) differs across racial/ethnic groups. RESEARCH DESIGN AND METHODS: We performed a prospective substudy of GRADE, a comparative effectiveness randomized trial conducted in 36 centers in the U.S. A total of 1,454 of the 5,047 participants in the GRADE cohort, including 534 non-Hispanic White (NHW), 389 non-Hispanic Black (NHB), and 327 Hispanic White patients and 204 patients of other racial/ethnic backgrounds, were included in the substudy. Continuous glucose monitoring (CGM) performed for 10 days was used to calculate AG10. Immediately after CGM, HbA1c and glycated albumin were measured. Fasting plasma glucose (FPG) and glucose area under the curve (AUC) were derived from a 75-g oral glucose tolerance test. RESULTS: The relationship between AG10 and HbA1c was significantly different for NHB compared with NHW patients and those of other racial/ethnic groups. HbA1c levels were 0.2–0.6 percentage points higher in NHB than in NHW patients for AG10 levels from 100 to 250 mg/dL. For an HbA1c of 7%, AG10 was 11 mg/dL higher for NHW than for NHB patients. Similar findings were observed across races for relationships of FPG and AUC with HbA1c and for glucose measurements with glycated albumin levels. Differences in the relationship between AG10 and HbA1c across racial groups remained after adjustments for any demographic or other differences between racial/ethnic subgroups. CONCLUSIONS: The relationship between several measures of glucose with HbA1c and glycated albumin consistently differed across races. These findings should be considered in setting treatment goals and diagnostic levels. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]