| dc.description.abstract | Background and Motivation: This paper develops a microsimulation model to assess the health and economic outcomes of implementing a prediabetes screening programme in Germany in combination a lifestyle intervention. It addresses the lack of comprehensive models in T2D prevention research and promotes transparency by sharing the model's code for further development. Methods: The methods of the study involve the development of a microsimulation state transition model to assess the cost-effectiveness of a population-based screening program and a behavioural intervention for individuals at risk of type 2 diabetes (T2D) compared to the current standard of care in Germany. The individual-level model considers different health states, transitions, and outcomes related to T2D. The analysis uses a societal per-spective, including direct and indirect costs, and employs incremental cost-effectiveness ratios (ICERs) to compare the interventions. Transitions probabilities are a function of HbA1c levels and are thus individual-specific. The screening programme involves HbA1c blood tests, and the lifestyle intervention is based on the German Prediabetes Lifestyle In-tervention (PLIS) trial. Results: The base case analysis of screening and treatment for prediabetes resulted in an incremental cost of €18,840 and an additional 0.57 quality-adjusted life years (QALYs) gained, with an incremental cost-effectiveness ratio (ICER) of €33,052 per QALY gained compared to no screening and no intervention. The intervention group showed a higher re-mission rate and fewer adverse events compared to the standard of care. The ICER changed significantly when the duration of the intervention effect was varied in scenario analysis, indicating a strong impact of this parameter on cost-effectiveness. Conclusions: This model provides the framework and a first exploratory analysis of a mi-crosimulation focussed on screening and treatment of prediabetes. Scenario analysis showed a large impact of the underlying assumptions on treatment effects and epidemio-logic data on the outcomes. This highlights the need for further research to obtain reliable data representing the population of interest to estimate the cost-effectiveness of a pro-gramme like this being rolled out on a population level. | eng |