Abstract
李倩倩,梁靖媛,王佳敏,沈鹏,孙烨祥,陈奇,邬金国,路平,张敬谊,林鸿波,唐迅,高培.NDR和DIAL模型在宁波市社区2型糖尿病人群中预测心血管病发生风险的应用[J].Chinese journal of Epidemiology,2022,43(6):945-952
NDR和DIAL模型在宁波市社区2型糖尿病人群中预测心血管病发生风险的应用
Applications of the NDR and DIAL models for risk prediction on cardiovascular disease in patients with type 2 diabetes in Ningbo
Received:November 16, 2021  
DOI:10.3760/cma.j.cn112338-20211116-00891
KeyWord: 糖尿病,2型  心血管病风险评估  终生风险模型  队列研究
English Key Word: Diabetes, type 2  Cardiovascular risk assessment  Lifetime risk prediction model  Cohort study
FundProject:国家重点研发计划(2020YFC2003503);国家自然科学基金(81961128006,81973132)
Author NameAffiliationE-mail
Li Qianqian Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China  
Liang Jingyuan Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China  
Wang Jiamin Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China  
Shen Peng Yinzhou District Center for Disease Control and Prevention of Ningbo, Yinzhou 315100, China  
Sun Yexiang Yinzhou District Center for Disease Control and Prevention of Ningbo, Yinzhou 315100, China  
Chen Qi Yinzhou District Center for Disease Control and Prevention of Ningbo, Yinzhou 315100, China  
Wu Jinguo Wonders Information Company Limited, Shanghai 201112, China  
Lu Ping Wonders Information Company Limited, Shanghai 201112, China  
Zhang Jingyi Wonders Information Company Limited, Shanghai 201112, China  
Lin Hongbo Yinzhou District Center for Disease Control and Prevention of Ningbo, Yinzhou 315100, China  
Tang Xun Center of Real-world Evidence Evaluation, Clinical Research Institute, Peking University, Beijing 100191, China tangxun@bjmu.edu.cn 
Gao Pei Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China 
peigao@bjmu.edu.cn 
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Abstract:
      目的 在我国社区2型糖尿病人群中独立验证并比较基于瑞典糖尿病登记数据(NDR)建立的心血管病短期风险预测模型和糖尿病终生风险预测(DIAL)模型评估5年和10年心血管病发生风险的准确性。方法 研究对象为2010年1月1日至2020年12月31日在中国鄞州电子健康档案研究中的基线无心血管病史且年龄在30~75岁的2型糖尿病队列人群。采用校准后的NDR模型评估研究对象5年心血管病风险,采用DIAL模型评估5年和10年心血管病发生风险,采用调整竞争风险的Kaplan-Meier法计算研究对象5年和10年心血管病实际发生风险。采用区分度C统计量、校准度χ2值和校准图评价预测模型的准确性。结果 经过中位7.0年的随访,83 503名研究对象共发生7 326例心血管病事件和2 937例非心血管病死亡事件。在5年心血管病风险预测中,NDR模型对男性和女性发病风险分别高估39.4%和8.6%,DIAL模型分别高估14.6%和50.1%。在男性5年风险预测中DIAL模型区分度优于NDR模型,其C统计量(95%CI)分别为0.681(0.672~0.690)和0.667(0.657~0.677);女性中两模型C统计量(95%CI)分别为0.698(0.689~0.706)和0.699(0.690~0.708)。在10年风险预测中,DIAL模型准确度有所提高,在男性中低估1.6%,在女性中高估12.8%。结论 在我国社区2型糖尿病人群中,校准后的NDR短期风险模型高估了5年心血管病风险,校准后的DIAL终生风险模型高估程度更严重;但随着预测年限延长到10年,DIAL模型预测准确性有所改善,体现了终生风险评估的价值,并提示需要建立适合我国2型糖尿病人群的心血管病终生风险预测模型。
English Abstract:
      Objective To validate the performance of cardiovascular risk prediction models based on the Sweden National Diabetes Register (NDR) and Diabetes Lifetime-perspective prediction (DIAL) model for assessing risks of 5-year and 10-year cardiovascular disease (CVD) among Chinese patients with type 2 diabetes. Methods Based on the Chinese Electronic Health Records Research in Yinzhou study, 83 503 patients with type 2 diabetes aged 30-75 years without a history of CVD at baseline were included from January 1, 2010 to December 31, 2020. Recalibrated NDR model was used to estimate 5-year risk, while the recalibrated DIAL model was used to predict 5-year and 10-year risks. The competing events adjusted Kaplan-Meier analysis was used to obtain the observed cardiovascular events. Discrimination C statistics evaluated model accuracy, calibration χ2 value, and calibration plots. Results Through a median follow-up of 7.0 years, 7 326 cardiovascular events, and 2 937 non-vascular deaths were identified among a total of 83 503 subjects. The recalibrated NDR model overestimated 5-year risk by 39.4% in men and 8.6% in women, whereas the overestimation for the recalibrated DIAL model was 14.6% in men and 50.1% in women. The DIAL model had a better discriminative ability (C-statistic=0.681, 95%CI: 0.672-0.690) than NDR model (C-statistic=0.667, 95%CI: 0.657-0.677) in 5-year risk prediction for men, and the models had a similar ability for women (C-statistic=0.699, 95%CI: 0.690-0.708 for NDR and C-statistic=0.698, 95%CI: 0.689-0.706 for DIAL). The prediction accuracy of the DIAL model was improved in the 10-year risk, with the underestimation being 1.6% for men and the overestimation being 12.8% for women. Conclusions Both recalibrated NDR and DIAL models overestimated 5-year cardiovascular risk in Chinese patients with type 2 diabetes, while the higher overestimation was shown using the DIAL model. However, the improvement was found in predicting 10-year CVD risk using the DIAL model, which suggested the value of lifetime risk prediction and indicated the need for research on the lifetime risk prediction model for cardiovascular risk assessment in Chinese patients with type 2 diabetes.
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