Evaluating disease burden in chronic kidney disease screening using a micro-simulation model

Abstract

Introduction: Chronic kidney disease (CKD) has a high prevalence, poor prognosis, and high medical costs, and awareness of the disease is low. Therefore, in this study, we aimed to simulate and analyze the evolution of CKD burden among different groups at high risk of CKD in Shanghai, with or without screening intervention, and provide a quantifiable basis for the selection of screening intervention strategies for CKD. Methods: A micro-simulation model was constructed to analyze the evolution of CKD burden using data from CKD screening of the population in the Jing’an and Minhang Districts of Shanghai, China, from January 2015 to December 2020. SAS Statistical Software 9.4 was used to simulate and analyze the evolution of disease burden under different screening intervention strategies. Results: By 2033, screening interventions for high-risk groups with hypertension, diabetes, and an age of 65 years and older would be associated with 6,250 fewer patients with end-stage renal disease. Furthermore, the number of patients with end-stage renal disease would be reduced to only 41.64% of the projected number of patients without screening intervention, leading to a general improvement in the quality of life of the population, better quality-adjusted life-years, and a reduction in the economic burden of disease. Discussion: The results of this study highlight the importance of combining the concepts of integrated prevention and treatment of chronic diseases to improve screening and intervention of CKD for people with hypertension, diabetes, and those aged 65 years and older, thereby effectively reducing the number of patients with end-stage renal disease, lowering the cost of treatment and intervention, and improving the quality of life of the population.