Literature DB >> 35701121

[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 M Wang1, Q P Liu1, M L Zhang1, C Gong1, S D Liu1, W Y Chen1, P Shen2, H B Lin2, P Gao1,3, X Tang1.   

Abstract

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.

Entities:  

Keywords:  Cardiovascular diseases; Diabetes; Markov model; Screening

Mesh:

Year:  2022        PMID: 35701121      PMCID: PMC9197700     

Source DB:  PubMed          Journal:  Beijing Da Xue Xue Bao Yi Xue Ban        ISSN: 1671-167X


  21 in total

1.  Age at initiation and frequency of screening to detect type 2 diabetes: a cost-effectiveness analysis.

Authors:  Richard Kahn; Peter Alperin; David Eddy; Knut Borch-Johnsen; John Buse; Justin Feigelman; Edward Gregg; Rury R Holman; M Sue Kirkman; Michael Stern; Jaakko Tuomilehto; Nick J Wareham
Journal:  Lancet       Date:  2010-03-29       Impact factor: 79.321

2.  Diabetes incidence and prevalence in Hong Kong, China during 2006-2014.

Authors:  J Quan; T K Li; H Pang; C H Choi; S C Siu; S Y Tang; N M S Wat; J Woo; J M Johnston; G M Leung
Journal:  Diabet Med       Date:  2016-11-29       Impact factor: 4.359

3.  The impact of new screen-detected and previously known type 2 diabetes on health-related quality of life: a population-based study in Qingdao, China.

Authors:  Yanlei Zhang; Jianping Sun; Zengchang Pang; Xiaoyong Wang; Weiguo Gao; Feng Ning; Jie Ren; Anil Kapur; Harri Sintonen; Qing Qiao
Journal:  Qual Life Res       Date:  2014-03-28       Impact factor: 4.147

Review 4.  General Health Checks in Adult Primary Care: A Review.

Authors:  David T Liss; Toshiko Uchida; Cheryl L Wilkes; Ankitha Radakrishnan; Jeffrey A Linder
Journal:  JAMA       Date:  2021-06-08       Impact factor: 56.272

5.  2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022.

Authors: 
Journal:  Diabetes Care       Date:  2022-01-01       Impact factor: 19.112

6.  2021 ESC Guidelines on cardiovascular disease prevention in clinical practice.

Authors:  Frank L J Visseren; François Mach; Yvo M Smulders; David Carballo; Konstantinos C Koskinas; Maria Bäck; Athanase Benetos; Alessandro Biffi; José-Manuel Boavida; Davide Capodanno; Bernard Cosyns; Carolyn Crawford; Constantinos H Davos; Ileana Desormais; Emanuele Di Angelantonio; Oscar H Franco; Sigrun Halvorsen; F D Richard Hobbs; Monika Hollander; Ewa A Jankowska; Matthias Michal; Simona Sacco; Naveed Sattar; Lale Tokgozoglu; Serena Tonstad; Konstantinos P Tsioufis; Ineke van Dis; Isabelle C van Gelder; Christoph Wanner; Bryan Williams
Journal:  Eur Heart J       Date:  2021-09-07       Impact factor: 35.855

Review 7.  Health policy and public health implications of obesity in China.

Authors:  Youfa Wang; Li Zhao; Liwang Gao; An Pan; Hong Xue
Journal:  Lancet Diabetes Endocrinol       Date:  2021-06-04       Impact factor: 32.069

8.  Estimating the delay between onset and diagnosis of type 2 diabetes from the time course of retinopathy prevalence.

Authors:  Massimo Porta; Giulia Curletto; Dario Cipullo; Roberta Rigault de la Longrais; Marina Trento; Pietro Passera; Anna Viola Taulaigo; Sabrina Di Miceli; Antonella Cenci; Paola Dalmasso; Franco Cavallo
Journal:  Diabetes Care       Date:  2014-04-04       Impact factor: 19.112

9.  Screening for type 2 diabetes: do screen-detected cases fare better?

Authors:  Adina L Feldman; Simon J Griffin; Eva Fhärm; Margareta Norberg; Patrik Wennberg; Lars Weinehall; Olov Rolandsson
Journal:  Diabetologia       Date:  2017-08-23       Impact factor: 10.122

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