A Microsimulation Model for Chronic Kidney Disease Progression in Type 2 Diabetes Patients in the United States: Michigan Model for Diabetes–Chronic Kidney Disease Model

ObjectivesTo develop and validate a microsimulation model to estimate the health outcomes and costs of chronic kidney disease (CKD) in type 2 diabetes (T2D) to inform health policies and reduce the burden of CKD.MethodsWe developed a comprehensive model for CKD in type 2 diabetes that assesses the impact of risk factors on the progression of urine albumin-to-creatinine ratio and estimated glomerular filtration rate and their impact on stroke, myocardial infarction (MI), congestive heart failure (CHF), end-stage kidney disease (ESKD), and death without dialysis or transplant using individual-level longitudinal data for T2D populations and summary data from published literature. We internally validated the model using data from the Chronic Renal Insufficiency Cohort (CRIC) of patients with T2D and CKD over 7 y and externally validated the model using the Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial data over 3 y.ResultsThe simulated event rates of ESKD, stroke, MI, CHF, and total mortality and the related 95% confidence intervals included the observed event rates in both the internal and external validation cohorts. Using this new model, we showed that lowering the blood pressure target from 140/90 to 120/80 mm Hg in patients with T2D and CKD was cost-saving at the population level.ConclusionThe Michigan Model for Diabetes-Chronic Kidney Disease (MMD-CKD) model provides accurate estimates of disease progression in patients with T2D and CKD. Modeling disease progression in this population will facilitate future assessments of the cost-effectiveness of systematic screening and interventions for CKD, which may reduce the health and economic burden of CKD in T2D. This model can also serve as a tool for predicting the clinical outcomes of individual patients with T2D and CKD. MMD-CKD 1.0 R Shiny app and is publicly available (https://michigandiabetesmodelinggroup.github.io/Software_App).HighlightsWe developed and validated a microsimulation model to simulate kidney disease progression, cardiovascular outcomes, mortality, direct medical costs, and quality of life in patients with chronic kidney disease (CKD) and type 2 diabetes (T2D).This model can be used to evaluate the long-term economic burden of CKD in T2D patients in the United States as well as to assess the costs and benefits associated with specific health policies and interventions.In addition, this model can help inform individual patients of their risk of end-stage kidney disease (ESKD) and cardiovascular events, thereby facilitating shared decision making.

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Publication Details

Journal
Medical Decision Making
Published
2026-06-19
DOI
https://doi.org/10.1177/0272989x261455313
Primary Topic
Chronic Kidney Disease and Diabetes
Type
article
Field-Weighted Citation Impact
0.00

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article

A Microsimulation Model for Chronic Kidney Disease Progression in Type 2 Diabetes Patients in the United States: Michigan Model for Diabetes–Chronic Kidney Disease Model

Shihchen Kuo, Jay Elliott, Ryan Farej, William H. Herman et al.
Medical Decision Making
Chronic Kidney Disease and Diabetes
article

A Microsimulation Model for Chronic Kidney Disease Progression in Type 2 Diabetes Patients in the United States: Michigan Model for Diabetes–Chronic Kidney Disease Model

Shihchen Kuo, Jay Elliott, Ryan Farej, William H. Herman, Xuemei Ding, Wen Ye, Rakesh Singh, Chun-Ting Yang, Sheldon X. Kong, Jason Lott, Jing Li
article en

Abstract

ObjectivesTo develop and validate a microsimulation model to estimate the health outcomes and costs of chronic kidney disease (CKD) in type 2 diabetes (T2D) to inform health policies and reduce the burden of CKD.MethodsWe developed a comprehensive model for CKD in type 2 diabetes that assesses the impact of risk factors on the progression of urine albumin-to-creatinine ratio and estimated glomerular filtration rate and their impact on stroke, myocardial infarction (MI), congestive heart failure (CHF), end-stage kidney disease (ESKD), and death without dialysis or transplant using individual-level longitudinal data for T2D populations and summary data from published literature. We internally validated the model using data from the Chronic Renal Insufficiency Cohort (CRIC) of patients with T2D and CKD over 7 y and externally validated the model using the Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial data over 3 y.ResultsThe simulated event rates of ESKD, stroke, MI, CHF, and total mortality and the related 95% confidence intervals included the observed event rates in both the internal and external validation cohorts. Using this new model, we showed that lowering the blood pressure target from 140/90 to 120/80 mm Hg in patients with T2D and CKD was cost-saving at the population level.ConclusionThe Michigan Model for Diabetes-Chronic Kidney Disease (MMD-CKD) model provides accurate estimates of disease progression in patients with T2D and CKD. Modeling disease progression in this population will facilitate future assessments of the cost-effectiveness of systematic screening and interventions for CKD, which may reduce the health and economic burden of CKD in T2D. This model can also serve as a tool for predicting the clinical outcomes of individual patients with T2D and CKD. MMD-CKD 1.0 R Shiny app and is publicly available (https://michigandiabetesmodelinggroup.github.io/Software_App).HighlightsWe developed and validated a microsimulation model to simulate kidney disease progression, cardiovascular outcomes, mortality, direct medical costs, and quality of life in patients with chronic kidney disease (CKD) and type 2 diabetes (T2D).This model can be used to evaluate the long-term economic burden of CKD in T2D patients in the United States as well as to assess the costs and benefits associated with specific health policies and interventions.In addition, this model can help inform individual patients of their risk of end-stage kidney disease (ESKD) and cardiovascular events, thereby facilitating shared decision making.

Medical Decision Making
Bayer (United States) (US), University of Michigan (US)
National Institute of Diabetes and Digestive and Kidney Diseases
Good health and well-being
Openalex Percentile: Top 8%
Chronic Kidney Disease and Diabetes
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