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山东大学学报（医学版） ›› 2017, Vol. 55 ›› Issue (6): 108-113.doi: 10.6040/j.issn.1671-7554.0.2017.341

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基于社区2型糖尿病患者的心脑血管事件5年风险预测模型

张振堂1,杨洋2,3,韩福俊1,陈向华1,季晓康3,4,王永超3,5,王淑康2,3,孙苑潆2,3,李敏2,3,陈亚飞2,3,王丽6,薛付忠2,3,刘言训2,3   

  1. 1.青岛市黄岛区疾病预防控制中心, 山东 青岛 266400;2.山东大学公共卫生学院生物统计系, 山东 济南 250012;3.山东大学齐鲁生物医学大数据研究中心, 山东 济南 250012;4.山东大学公共卫生学院信息处理实验室, 山东 济南 250012;5.康评健康医疗大数据科技有限公司, 山东 济南 250101;6.山东电力中心医院心内科, 山东 济南 250001
  • 收稿日期:2017-04-19 出版日期:2017-06-10 发布日期:2017-06-10
  • 通讯作者: 刘言训. E-mail: liu-yx@sdu.edu.cn E-mail:liu-yx@sdu.edu.cn
  • 基金资助:
    国家自然科学基金青年基金(81400072);山东省自然科学基金(2013HQ047)

A prediction model of 5-year CVD risks for type 2 diabetic patients: a prospective cohort study among Chinese community population

ZHANG Zhentang1, YANG Yang2,3, HAN Fujun1, CHEN Xianghua1, JI Xiaokang3,4, WANG Yongchao3,5, WANG Shukang2,3, SUN Yuanying2,3, LI Min2,3, CHEN Yafei2,3, WANG Li6, XUE Fuzhong2,3, LIU Yanxun2,3   

  1. 1. Center for Disease Control and Prevention of Huangdao District, Qingdao 266400, Shandong, China;
    2. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    3. Cheeloo Research Center for Biomedical Big Data, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    4. Information Processing Laboratory, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    5. Kangping Health Care Big Data Technology Company Limited, Jinan 250101, Shandong, China;
    6. Department of Cardiology, Shandong Electric Power Central Hospital, Jinan 250001, Shandong, China
  • Received:2017-04-19 Online:2017-06-10 Published:2017-06-10

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摘要： 目的 构建新诊断的2型糖尿病患者5年内首次发生心脑血管事件的预测模型。 方法 研究对象选自青岛市黄岛区疾病预防控制中心慢性病管理系统,选择未发生过心脑血管事件的2型糖尿病患者2 899例作为训练样本,建立Cox模型和评分模型,并对模型进行内部验证;用“山东多中心健康管理纵向观察队列”中的1 016例2型糖尿病患者作为验证样本,对模型进行外部验证。 结果 随访期间训练样本共发生228例心脑血管事件,发病密度为16.86‰。模型变量包括年龄、性别、收缩压、低密度脂蛋白、高密度脂蛋白和心脑血管病家族史。训练样本Cox模型ROC曲线下面积(AUC)为0.678(95%CI:0.660~0.695),评分模型AUC为0.663(95%CI:0.648~0.680);外部验证Cox模型AUC为0.640(95%CI:0.608~0.676),评分模型AUC为0.631(95%CI:0.600~0.661)。 结论 研究建立的2型糖尿病患者心脑血管事件5年预测模型可以为社区糖尿病患者管理初期提供参考。

关键词: 糖尿病, 社区管理, 并发症, 心脑血管病, 预测模型

Abstract: Objective To construct a prediction model for risks of cardio-cerebrovascular disease(CVD)in 5 years for newly diagnosed type 2 diabetic patients in China. Methods We collected from an official chronic disease prevention and control project 2 899 participants newly diagnosed as diabetic who were free from CVD events. Cox proportional 山 东 大 学 学 报 (医 学 版)55卷6期 -张振堂,等.基于社区2型糖尿病患者的心脑血管事件5年风险预测模型 \=-hazards regression model was used to construct a 5-year CVD risk model. Calibration and goodness of fit test were applied. External validation based on Shandong Multi-center Health Management Large Database was adopted to assess the stability of model. Results a total of 228 first CVD events were recorded in the derivation cohort during an average follow-up of 4.7 years(16.86/1 000 person-year). The 6 variables included age, gender, systolic pressure, low-density lipoprotein, high-density lipoprotein and family history of CVD. In the derivation cohort, the area under the receiver operating characteristic curve(AUC)for the Cox model and scoring model was 0.678(95%CI: 0.660-0.695)and 0.663(95%CI: 0.648-0.680), respectively. In the external validation, the AUC for the Cox model and scoring model was 0.640(95%CI: 0.608-0.676)and 0.631(95% CI:0.600-0.661), respectively. Conclusion We have established a model to predict the 5-year risks of CVD in Chinese type 2 diabetic patients, which can be used for the early intervention of CVD among type 2 diabetic patients in residential communities.

Key words: Complication, Cardio-cerebrovascular disease, Community management, Diabetes, Prediction model

中图分类号: 

  • R587.1
[1] Association AD. Cardiovascular disease and risk management[J]. Diabetes Care, 2015, 38(suppl2): 49-57.
[2] Ruwanpathirana T, Owen A, Reid CM. Review on cardiovascular risk prediction[J]. Cardiovasc Ther, 2015, 33(2): 62-70.
[3] Shah AD, Langenberg C, Rapsomaniki E, et al. Type 2 diabetes and incidence of a wide range of cardiovascular diseases: a cohort study in 1.9 million people[J]. Lancet Diabetes Endocrinol, 2015, 3(2): 105-113.
[4] DAgostino RB, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study[J]. Circulation, 2008,117(6): 743-753.
[5] Dieren S Van, Beulens JWJ, Kengne AP, et al. Prediction models for the risk of cardiovascular disease in patients with type 2 diabetes: a systematic review[J]. Heart, 2012, 98(5): 360-369.
[6] Siontis GCM, Tzoulaki I, Siontis KC, et al. Comparisons of established risk prediction models for cardiovascular disease: systematic review[J]. Bmj, 2012, 344(21): e3318. doi: 10.1136/bmj.e3318.
[7] Echouffotcheugui JB, Greene SJ, Papadimitriou L, et al. Population risk prediction models for incident heart failure: a systematic review[J]. Circ Heart Fail, 2015, 8(3): 438-447.
[8] Stevens RJ, Kothari V, Adler AI, et al. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes(UKPDS 56)[J]. Clin Sci, 2002, 101(6): 671-679.
[9] Viti K, Stevens RJ, Adler AI, et al. UKPDS 60: risk of stroke in type 2 diabetes estimated by the UK Prospective Diabetes Study risk engine[J]. Stroke J Cereb Circ, 2002, 33(7): 1776-1781.
[10] Kengne AP, Patel A, Colagiuri S, et al. The Framingham and UK Prospective Diabetes Study(UKPDS)risk equations do not reliably estimate the probability of cardiovascular events in a large ethnically diverse sample of patients with diabetes: the Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation(ADVANCE)Study[J]. Diabetologia, 2010, 53(5): 821-831.
[11] Wenying Y, Juming L, Jianping W, et al. Prevalence of diabetes among men and women in China[J]. N Engl J Med, 2010, 362(12): 1090-1101.
[12] Tseng CH. Mortality and causes of death in a national sample of diabetic patients in Taiwan[J]. Diabetes Care, 2005, 27(7): 1605-1609.
[13] Sullivan LM, Massaro JM, D’Agostino RB. Presentation of multivariate data for clinical use: The Framingham Study risk score functions[J]. Stat Med, 2004, 23(10): 1631-1660.
[14] 林倍倍, 陈博武, 吴柏霆, 等. 上海市社区居民糖尿病并发症及相关因素调查研究[J]. 中国预防医学杂志, 2017, 18(4): 249-253.
[15] 王博. 慢性病社区防治管理的现状和发展趋势探讨[J]. 中国卫生产业, 2016, 13(23): 193-195.
[16] Chien KL, Su TH, Chang WT, et al. Constructing the prediction model for the risk of stroke in a Chinese population: report from a cohort study in Taiwan[J]. Stroke, 2010, 41(9): 1858-1864.
[17] Chamnan P, Simmons RK, Sharp SJ, et al. Cardiovascular risk assessment scores for people with diabetes: a systematic review[J]. Diabetologia, 2009, 52(10): 2001-2014.
[18] Yang X, So WY, Kong APS, et al. Development and validation of stroke risk equation for Hong Kong Chinese patients with type 2 diabetes: the Hong Kong Diabetes Registry[J]. Diabetes Care, 2007, 30(1): 65-70.
[19] Piniés JA, Fernando GC, Arteagoitia JM, et al. Development of a prediction model for fatal and non-fatal coronary heart disease and cardiovascular disease in patients with newly diagnosed type 2 diabetes mellitus: the Basque Country Prospective Complications and Mortality Study risk engine(BASCORE)[J]. Diabetologia, 2014, 57(11): 2324-2333.
[20] 孟祥英, 周勇, 汤玮, 等. ADVANCE心脑血管风险模型应用于上海市2型糖尿病患者的价值和意义[J]. 上海医学, 2015, 38(3): 226-230.
[21] 李乃适, 张念荣, 李光伟. 生活方式干预是预防2型糖尿病的重要举措[J]. 中华健康管理学杂志, 2013, 7(5): 289-291.
[22] 游小梅, 林红浪, 陈先辉, 等. 健康管理干预对社区2型糖尿病患者生活质量的效果评价[J]. 实用心脑肺血管病杂志, 2009, 17(1): 16-18.
[23] 王桂卿. 2型糖尿病患者的健康管理及对慢性并发症的影响[J]. 临床医药文献电子杂志, 2016, 3(59): 11725-11728.
[24] Tonstad S, Rosvold EO, Furu K, et al. Undertreatment and overtreatment with statins: the Oslo Health Study 2000-2001[J]. J Intern Med, 2004, 255(4): 494-502.
[25] Wingard DL, Barrett-Connor EL, Ferrara A. Is insulin really a heart disease risk factor[J]. Diabetes Care, 1995, 18(9): 1299-1304.
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