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山东大学学报（医学版） ›› 2017, Vol. 55 ›› Issue (6): 104-107.doi: 10.6040/j.issn.1671-7554.0.2017.401

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健康管理队列白内障发病风险预测模型

于媛媛1,2,王春霞3,苏萍1,2,孙苑潆1,2,薛付忠1,2,刘言训1,2   

  1. 1.山东大学公共卫生学院生物统计学系, 山东 济南 250012;2.山东大学齐鲁生物医学大数据研究中心, 山东 济南 250012;3.济宁医学院附属医院健康管理中心, 山东 济宁 272000
  • 收稿日期:2017-05-06 出版日期:2017-06-10 发布日期:2017-06-10
  • 通讯作者: 薛付忠. E-mail:xuefzh@sdu.edu.cn刘言训. E-mail:liu-yx@sdu.edu.cn E-mail:xuefzh@sdu.edu.cn
  • 基金资助:
    国家国际科技合作专项项目(2014DFA32830)

A prediction model to estimate risks of cataract based on health management cohort

YU Yuanyuan1,2, WANG Chunxia3, SU Ping1,2, SUN Yuanying1,2, XUE Fuzhong1,2, LIU Yanxun1,2   

  1. 1. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Cheeloo Research Center for Biomedical Big Data, Shandong University, Jinan 250012, Shandong, China;
    3. Health Management Center, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong, China
  • Received:2017-05-06 Online:2017-06-10 Published:2017-06-10

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摘要： 目的 构建50岁以上健康管理队列的白内障发病风险预测模型。 方法 依托山东多中心健康管理纵向观察数据库,采用Cox比例风险回归构建白内障发病风险预测模型,通过ROC曲线下面积(AUC)评价模型的预测效果,并利用十折交叉验证来检验模型的稳定性。 结果 随访期间共新发白内障病例1 010例,发病密度为24.76‰。预测模型最终纳入年龄、性别、吸烟、高黏稠血症、鼓膜疾患、屈光不正、糖尿病、总胆固醇和收缩压9个变量。白内障发病风险预测模型的AUC为0.712(95%CI:0.693~0.732)。十折交叉验证的平均AUC为0.714。 结论 研究构建的白内障发病风险预测模型有较好的预测效果,为白内障高危人群的早期筛查提供了依据。

关键词: 风险预测模型, 队列研究, 白内障, Cox比例风险回归

Abstract: Objective To establish a prediction model to estimate risks of cataract among health management population aged above 50 years. Methods Based on the Shandong Multi-center Longitudinal Cohort for Health Management, a prediction model for cataract was constructed using Coxs proportional hazards regression model. The predictability was evaluated with the area under the receiver operating characteristic(ROC)curve(AUC). The stability was tested with ten-fold cross-validation. Results During the follow-up period, there were 1010 new cataract cases, and the incidence density was 24.76‰. The risk factors included in prediction model were age, sex, smoking habit, hyperviscosemia, tympanic diseases, ametropia, diabetes, total cholesterol and systolic blood pressure(SBP). The AUC of the prediction model was 0.712(95% CI: 0.693-0.732). The ten-fold cross-validation showed that the AUC was 0.714. Conclusion The prediction model of cataract has high predictability and reliability. It can provide scientific basis for identifying high-risk groups of cataract.

Key words: Cohort study, Cataract, Coxs proportional hazards regression, Risk prediction model

中图分类号: 

  • R776.1
[1] Brian G, Taylor H. Cataract blindness: challenges for the 21st century[J]. Bull World Health Organ, 2001, 79(3): 249-256.
[2] 张小梅, 杨剑锋. 长沙市老年性白内障患病率及其影响因素分析[J]. 湖南师范大学学报(医学版), 2015, 12(2): 40-43. ZHANG Xiaomei, YANG Jianfeng. Analysis on the prevalence and influence factors of senile cataract of Changsha City[J]. J Hunan Normal Univ(Med Sci), 2015, 12(2): 40-43.
[3] Abbas S, Raza ST, Chandra A, et al. Polymorphism of FABP2 and PPARG2 genes in risk prediction of cataract among North Indian population[J]. Meta Gene, 2014, 2(4): 307-313.
[4] Foster PJ, Wong TY, Machin D, et al. Risk factors for nuclear, cortical and posterior subcapsular cataracts in the Chinese population of Singapore: the Tanjong Pagar Survey[J]. Br J Ophthalmol, 2003, 87(9): 1112-1120.
[5] Abraham AG, Condon NG, Gower EW. The new epidemiology of cataract[J]. Ophthalmol Clin North Am, 2006, 19(4): 415-425.
[6] McCarty CA, Taylor HR. The genetics of cataract[J]. Invest Ophthalmol Vis Sci, 2001, 42(8): 1677-1678.
[7] Neale RE, Purdie JL, Hirst LW, et al. Sun exposure as a risk factor for nuclear cataract[J]. Epidemiology, 2003, 14(6): 707-712.
[8] 李德馨, 王思玲, 苏德森. 白内障的发病机制与药物治疗[J]. 沈阳药科大学学报, 2002, 19(4): 300-307.
[9] 陈章玲. 屈光性白内障手术研究进展[J]. 医学综述, 2015, 21(1): 69-71.
[10] 杨萍, 周文君. 白内障超声乳化术后影响角膜内皮细胞损伤因素的Logistic分析及预测模型[J]. 重庆医学, 2014, 43(25): 3343-3345.
[11] Mangione CM, Orav EJ, Lawrence MG, et al. Prediction of visual function after cataract surgery: a prospectively validated model[J]. Arch Ophthalmol, 1995, 113(10): 1305-1311.
[12] 杨梅, 朱蓉嵘, 梁从凯, 等. 基于江苏省阜宁县社区人群的白内障相关因素调查[J]. 中华眼科杂志, 2014, 50(3): 179-183. YANG Mei, ZHU Rongzheng, LIANG Congkai, et al. Cataract risk factor survey in Funing county of Jiangsu province[J]. Chin J Ophthalmol, 2014, 50(3): 179-183.
[13] Zhao J, Ellwein LB, Cui H, et al. Prevalence and outcomes of cataract surgery in rural China the China nine-province survey[J]. Ophthalmology, 2010, 117(11): 2120-2128.
[14] 中国高血压防治指南修订委员会. 中国高血压防治指南(2010年修订版)[J]. 中国实用乡村医生杂志, 2012, 19(10): 1-15.
[15] 中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2013年版)[J]. 中华糖尿病杂志, 2014, 6(7): 447-498.
[16] Ye J, He J, Wang C, et al. Smoking and risk of age-related cataract: a meta-analysis[J]. Invest Ophthalmol Vis Sci, 2012, 53(7): 3885-3895.
[17] Chatterjee A, Milton RC, Thyle S. Prevalence and aetiology of cataract in Punjab[J]. Br J Ophthalmol, 1982, 66(1): 35-42.
[18] Asbell PA, Dualan I, Mindel J, et al. Age-related cataract[J]. Lancet, 2005, 365(9459): 599-609.
[19] Harding JJ, Van Heyningen R. Drugs, including alcohol, that act as risk factors for cataract, and possible protection against cataract by aspirin-like analgesics and cyclopenthiazide[J]. Br J Ophthalmol, 1988, 72(11): 809-814.
[20] Saleemurrehman SR, Kaunsar R, Kadri S, et al. Prevalence of bilateral cataract blindness in persons ≥50 years of age in Pulwama district, Jammu & Kashmir, India[J]. Int J Res Med Sci, 2014, 2(1):145-150.
[21] Krishnaiah S, Vilas K, Shamanna BR, et al. Smoking and its association with cataract: results of the Andhra Pradesh eye disease study from India[J]. Invest Ophthalmol Vis Sci, 2005, 46(1): 58-65.
[22] Maralani HG, Tai BC, Wong TY, et al. Metabolic syndrome and risk of age-related cataract over time: an analysis of interval-censored data using a random-effects model metabolic syndrome and cataract[J]. Invest Ophthalmol Vis Sci, 2013, 54(1): 641-646.
[23] Nirmalan PK, Robin AL, Katz J, et al. Risk factors for age related cataract in a rural population of southern India: the Aravind Comprehensive Eye Study[J]. Br J Ophthalmol, 2004, 88(8): 989-994.
[24] Chen KJ, Pan WH, Huang CJ, et al. Association between folate status, diabetes, antihypertensive medication and age-related cataracts in elderly Taiwanese[J]. J Nutr Health Aging, 2011, 15(4): 304-310.
[25] Lindblad BE, Håkansson N, Wolk A. Smoking cessation and the risk of cataract: a prospective cohort study of cataract extraction among men[J]. JAMA Ophthalmol, 2014, 132(3): 253-257.
[26] 马德环, 叶冬青, 陈逖. 老年性白内障危险因素病例对照研究[J]. 临床眼科杂志, 2001, 9(4): 276-279. MA Dehuan, YE Dongqing, CHEN Di. A case-control study on dangerous factors of senile cataract[J]. Journal of clinical ophthalmology, 2001, 9(4): 276-279.
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