Long-term glycemia trajectories, which can be predicted by a combination of factors, are identified for patients with T2D in a research article published in Clinical Epidemiology. Piia Lavikainen, PhD, and colleagues extracted data covering primary and specialized healthcare for 9,631 patients with T2D. Six-year A1C trajectories were examined. To predict trajectory membership, a linear discriminant analysis and neural networks were applied. Over 6 years, A1C trajectories were distinguished: stable, adequate; improving but inadequate; and fluctuating, inadequate glycemic control (86.5%, 7.3%, and 6.2%, respectively). The most important predictors for long- term treatment balance were prior glucose levels, T2D duration, use of insulin only, use of insulin and oral antidiabetic medications, and use of metformin only. Balanced accuracy was 85% for the prediction model, and the area under the receiver operating characteristic curve was 91%. “Our findings suggest that heterogeneity in long-term treatment outcomes is predictable with [a] patient’s unique risk factors,” the authors wrote. “This, in turn, offers a useful tool to support treatment planning in the future.”