Estimated Optimal Individualized Diabetes Risk Prediction From Preventive Interventions in the U.S. General Population

OBJECTIVE: To calculate 3-year predicted risk for diabetes with a model including individualized preventive intervention effects for metformin therapy and intensive lifestyle among U.S. adults with prediabetes. RESEARCH DESIGN AND METHODS: We included 2,778 participants with prediabetes from the National Health and Nutrition Examination Survey (NHANES) cycles 2015-2020. Using a validated type 2 diabetes risk prediction model, we calculated predicted risk and summarized the optimal prevention strategy (lowest predicted risk). RESULTS: Mean predicted risk in this sample was 18.4% (95% CI 17.6, 19.3) for standard lifestyle recommendations (placebo), 14.4% (95% CI 13.9, 14.8) for metformin, 8.0% (95% CI 7.6, 8.4) for intensive lifestyle, and 7.6% (95% CI 7.2, 7.9) for participants' respective optimal intervention. The optimal intervention strategy was intensive lifestyle for 91% of the analytic sample. CONCLUSIONS: We demonstrate the potential population health benefits for diabetes prevention with use of a clinical decision tool, a diabetes risk prediction model with individualized preventive intervention effects.