It's not black and white: individualizing metformin treatment in type 2 diabetes.

The treatment of type 2 diabetes is algorithmic. Given a new diagnosis of type 2 diabetes, professional organizations offer a series of competing guidelines which share, as a common denominator, suggestions for both the initiation of therapy and subsequent escalation, depending on the ability of the prescribed regimen to achieve prespecified treatment goals (1, 2). At the top of all algorithms stands the generic drug metformin, which is safe, cheap, and effective; therefore, it is universally prescribed as the first-line agent in the treatment of type 2 diabetes, barring unusual contraindications. More recent recommendations have attempted to individualize treatment based on personal characteristics (3), but metformin remains in a pre-eminent position, and the prescriber’s assessment of suitability is necessarily subjective. This practice persists despite emerging evidence that metformin is not equally effective in everyone (4, 5). Thus, there is an urgent need to increase our granularity in type 2 diabetes therapeutics, so that precision medicine can guide the right prescription for the right patient at the right time. The paper by Williams et al (6) in this issue of the JCEM represents one step in that direction. Williams et al (6) examined whether response to metformin differs in European American or African American patients with type 2 diabetes by comparing change in glycated hemoglobin (HbA1C) in enrollees in the Henry Ford HealthSystem in southernMichigan.Theymadeuseof the electronic health records to identify 19 672 patients with diabetes taking metformin, among whom 7429 individuals self-identified as being African American and 8783 identified themselves as being European American. Participants had to have at least two HbA1C measurements while on metformin. The authors calculated the total daily dose of metformin exposure based on prescription information, normalized it to the allowed maximal dose (850 mg thrice daily, or 2550 mg), and derived 120-day windows to reflect the average lifespan of a red blood cell. They then used a variety of statistical models based on generalized estimating equations with repeated measures to examine the impact of metformin exposure on the outcome HbA1C, before and after adjustment for several relevant covariates such as patient age, sex, race/ethnicity, duration of time on treatment, baseline HbA1C level, and concomitant use of other diabetes medications (ie, similarly obtained exposure measures for meglitinides, sulfonylureas, thiazolidinediones, fast-acting insulin, and slow-acting insulin). They included interaction terms for self-reported ethnicity and conducted additional stratified analyses to confirm the observed effects. The authors found that African American patients were younger and had a higher HbA1C at baseline; a greater proportion of African American patients were women. They were also less likely to receive dipeptidyl peptidase-4 inhibitors and more likely to receive insulin. In every statistical model, African Americans were shown to be more responsive to metformin in terms of a change in HbA1C, even after adjusting for all relevant covariates. This provocative finding, if confirmed, would define African Americans as more likely metformin responders when compared to European Americans. Given the retrospective and uncontrolled nature of this exploration, however, great caution must be exercised to ensure that the observed differences are not the result of unmeasured confounders, and the authors take this valid concern to heart.