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Effectiveness of different screening strategies for type 2 diabete on preventing cardiovascular diseases in a community-based Chinese population using a decision-analytic Markov model
Received date: 2022-02-06
Online published: 2022-06-14
Supported by
National Natural Sciences Foundation of China(81973132);National Natural Sciences Foundation of China(81961128006);National Key Research and Development Program of China(2020YFC2003503)
Objective: To evaluate the effectiveness of different screening strategies for type 2 diabetes to prevent cardiovascular disease in a community-based Chinese population from economically developed areas based on the Chinese electronic health records research in Yinzhou (CHERRY) study. Methods: A Markov model was used to simulate different systematic diabetes screening strategies, including: (1) screening among Chinese adults aged 40-70 years recommended by the 2020 Chinese Guideline for the prevention and Treatment of Type 2 Diabetes (Strategy 1); (2) screening among Chinese adults aged 35 to 70 years recommended by the 2022 American Diabetes Association Standard of Medical Care in Diabetes (Strategy 2); and (3) screening among Chinese adults aged 35-70 years with overweight or obesity recommended by the 2021 United States Preventive Services Task Force Recommendation Statement on Screening for Prediabetes and Type 2 Diabetes (Strategy 3). According to the guidelines, individuals who were screened positively (fasting plasma glucose ≥ 7.0 mmol/L) would be introduced to intensive glycemic targets management (glycated hemoglobin < 7.0%).The Markov model simulated different screening scenarios for ten years (cycles) with parameters mainly from the CHERRY study or published literature. Number of cardiovascular disease events or deaths could be prevented and number needed to screen (NNS) were calculated to compare the effectiveness of the different strategies. One-way sensitivity analysis on the sensitivity of screening methods and probabilistic sensitivity analysis on uncertainties of diabetes incidence, the sensitivity of screening methods, and intensive glycemic management effects were conducted. Results: Totally 289 245 Chinese adults aged 35-70 years without cardiovascular diseases or diagnosed diabetes at baseline were enrolled. In terms of the number of cardiovascular disease events could be prevented, Strategy 1 for systematic diabetes screening among the adults aged 35-70 years was 222 (95%UI: 180-264), Strategy 2 for systematic diabetes screening among the adults aged 40-70 years was 227 (95%UI: 185-271), and Strategy 3 for systematic diabetes screening among the adults aged 35-70 years with obesity or overweight (body mass index ≥ 24 kg/m2) was 131 (95%UI: 98-164), compared with opportunistic screening. NNS per cardiovascular disease event for the strategies 1, 2 and 3 were 1 184 (95%UI: 994-1 456), 1 274 (95%UI: 1 067-1 564) and 814 (95%UI: 649-1 091), respectively. Compared with Strategy 1, NNS per cardiovascular disease event for Strategy 2 increased by 90 (95%UI: -197-381) with similar effectiveness of cardiovascular prevention; however, NNS per cardiovascular disease event for Strategy 3 was reduced by 460 (95%UI: 185-724) in contrast to the Strategy 2, suggesting that the Strategy 3 was more efficient. The results were consistent in multiple sensitivity analyses. Conclusion: Systematic screening for diabetes based on the latest guidelines in economically developed areas of China can reduce cardiovascular events and deaths. However, merely lowering the starting age of screening from 40 to 35 years seems ineffective for preventing cardiovascular disease, while screening strategy for Chinese adults aged 35-70 years with overweight or obesity is recommended to improve efficiency.
Key words: Diabetes; Screening; Cardiovascular diseases; Markov model
Jia-min WANG , Qiu-ping LIU , Ming-lu ZHANG , Chao GONG , Shu-dan LIU , Wei-ye CHEN , Peng SHEN , Hong-bo LIN , Pei GAO , Xun TANG . Effectiveness of different screening strategies for type 2 diabete on preventing cardiovascular diseases in a community-based Chinese population using a decision-analytic Markov model[J]. Journal of Peking University(Health Sciences), 2022 , 54(3) : 450 -457 . DOI: 10.19723/j.issn.1671-167X.2022.03.009
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