Introduction: We previously developed a type 2 diabetes (T2D) risk prediction model with guideline-recommended prevention intervention effects. We lack population-level estimates of potential benefits for use of this model among US adults. Objective: To estimate 3-year predicted risk for T2D with an established model that includes individualized preventive intervention effects for metformin therapy and intensive lifestyle and summarize predicted benefits among the US adult population. Methods: Data for 4545 participants (age 20-80 years) without diabetes from the National Health and Nutrition Examination Survey (NHANES) cycles 2015-2020. The risk prediction model included empirical data for fasting glucose, glycated hemoglobin, body mass index, triglycerides, age, and sex and previously estimated intervention effects for metformin and lifestyle. We calculated 3-year predicted risk of incident diabetes conditional on the participant initiating lifestyle, metformin, or no intervention (placebo) and summarized risk estimates and the optimal prevention strategy (lowest predicted risk) for each participant overall and according to demographic and clinical subgroups. We used NHANES fasting sample weights and accounted for the stratified, clustered sample design. Results: The weighted NHANES sample represented 193,087,634 US adults (mean age 46 years, 52% female, 61% with prediabetes). The overall mean 3-year predicted risk for type 2 diabetes in this sample was 12.5% (95% CI: 11.8, 13.2) for placebo, 10.5% (95%: 10.1, 10.9) for metformin, 5.8% (95% CI: 5.5, 6.0) for lifestyle, and 5.5% (95%CI: 5.2, 5.7) when everyone is assigned their optimal intervention strategy ( Table ). The optimal intervention strategy was lifestyle for 91% of the analytic sample (91% for those with prediabetes and 90% for those with normal glucose), proportions consistently observed across demographic (Figure 1) and clinical subgroups (Figure 2) except for when body mass index ≥35 kg/m 2 , where metformin was the optimal preventive strategy for >40%. Conclusion: These findings highlight the potential for improving efficiency and maximizing individual and population-level benefits by identifying an individual’s optimal T2D prevention strategy and helping target preventive care.
Stafford et al. (Tue,) studied this question.