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浙江大学学报（医学版）
J Zhejiang Univ (Med Sci)  2018, Vol. 47 Issue (2): 194-200    DOI: 10.3785/j.issn.1008-9292.2018.04.14
    
Multiple risk factors prediction models for high risk population of colorectal cancer
JIANG Xiyi1(),LI Lu2,TANG Huijuan1,CHEN Tianhui1,3,*()
1. Group of Molecular Epidemiology & Cancer Precision Prevention, Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Hangzhou 310013, China
2. School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China
3. Medical School of Ningbo University, Ningbo 315211, China
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Abstract  

Colorectal cancer is caused by the interaction of genetic and environment factors. Domestic and foreign scholars have attempted to develop several colorectal cancer risk prediction models, in order to identity risk factors, to screen for high risk population and evaluate the risk of developing colorectal cancer, so as to provide personalized screening protocols for individuals with different risk, and eventually reduce the incidence and mortality rate of colorectal cancer. Currently, the common colorectal cancer risk prediction models were mainly developed based on case-control study and cohort study. Models developed in European and American regions and Asia (excluding China) only include common risk factors, while Chinese models also include hereditary factors on the bases of common risk factors. However, the development and verification of each model are mainly based on local population, whether it can be applied for other population need to be determined. This article reviews the development, validation and evaluation of the risk prediction models, in order to provide a basis for developing more precise risk prediction models for colorectal cancer.

Key words： Colorectal neoplasms/epidemiology      Forecasting      Models, statistical      Risk factors      Review     
Received: 04 January 2018      Published: 24 July 2018
CLC:  R181.2  
  R735.3  
Corresponding Authors: CHEN Tianhui     E-mail: jiangxy@zjams.com.cn;t.chen@zjams.com.cn
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JIANG Xiyi
LI Lu
TANG Huijuan
CHEN Tianhui
Cite this article:

JIANG Xiyi,LI Lu,TANG Huijuan,CHEN Tianhui. Multiple risk factors prediction models for high risk population of colorectal cancer. J Zhejiang Univ (Med Sci), 2018, 47(2): 194-200.

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http://www.zjujournals.com/med/10.3785/j.issn.1008-9292.2018.04.14     OR     http://www.zjujournals.com/med/Y2018/V47/I2/194


结直肠癌高危人群多因素风险预测模型及评价

结直肠癌的发生是遗传因素和环境因素共同作用的结果。国内外学者已尝试建立多种结直肠癌风险预测模型用于识别危险因素、筛选高危人群及评估发病风险，从而为不同风险人群提供个性化的筛查方案，有效降低结直肠癌的发病率和病死率。现有的典型结直肠癌风险预测模型的建立多基于病例对照研究和队列研究。欧美地区和亚洲地区（除中国外）模型仅纳入常见风险因素；中国的模型在常见风险因素的基础上，还纳入了遗传因素。然而，各模型的建立和验证多基于本地区人群，是否适用于外部人群尚待验证。本文就各种模型的建立、验证和评价进行综述，为进一步建立精确的风险预测模型提供依据。


关键词： 结直肠肿瘤/流行病学,  预测,  模型, 统计学,  危险因素,  综述 
模型 国别 模型验证方式 建模(研究设计，样本数/结直肠癌数) 验证(研究设计，样本数/结直肠癌数) 纳入的因素 模型预测价值(AUC/c指数)
“—”无相关数据；HPFS：健康专业人士随访研究；NHS：护士健康研究；a包括rs1983891、rs869736、rs3214050、rs10411210、rs3731055、rs231775、rs1412829、rs1572072、rs6983267、rs1799782、rs712221、rs160277、rs11721827、rs2736100、rs3135967、rs1760944；b包括rs647161、rs10505477、rs6983267、rs10795668、rs7229639、rs4939827、rs242327.
哈佛癌症风险指数模型[9-11] 美国 外部验证 文献查阅、总结归纳 队列研究HPFS队列：38 953/230；NHS队列：52 668/244 一级亲属结肠癌史、体质指数、筛查史(粪潜血试验、结肠镜检查)、阿司匹林使用史、炎性肠疾病史、叶酸摄入史、饮食(红肉、蔬菜、水果、纤维、脂肪)、吸烟、饮酒、身高、体力活动和雌激素替代治疗史 男性：0.71女性：0.67
Freedman模型[12-13] 美国 外部验证 病例对照研究病例：2263对照：2833 队列研究男：155 345/2093；女：108 057/832 男性：过去10年息肉史、一级亲属结直肠癌史、阿司匹林及非甾体抗炎药使用史、吸烟、体质指数、体力活动和蔬菜摄入；女性：结肠镜检查史、息肉史、一级亲属结直肠癌史、阿司匹林及非甾体抗炎药使用史、体力活动、蔬菜摄入、激素替代治疗史和绝经期雌激素暴露史 男性：0.61女性：0.61
Tao模型[14] 德国 外部验证 队列研究7891/107 横断面研究3519/29 性别、年龄、吸烟、一级亲属结肠癌史、饮酒、息肉史、红肉摄入、非甾体抗炎药使用史、结肠镜检查史 0.68
Imperiale模型[15] 印度 外部验证 横断面研究1994/67 横断面研究1031/15 年龄、性别、远端结肠病变 0.74
Ma模型[16] 日本 外部验证 队列研究28 115/543 队列研究18 256/389 年龄、体质指数、体力活动、吸烟、饮酒 0.64
Shin模型[17] 韩国 外部验证 队列研究男：846 559/6492；女：479 449/2655 队列研究男：547 874/3555女：415 875/1969 男性：年龄、身高、体质指数、空腹血糖、血清总胆固醇、肿瘤家族史、饮酒和肉类摄入；女性：年龄、身高、肿瘤家族史、空腹血糖和肉类摄入 男性：0.78女性：0.73
Cai模型[18] 中国 外部验证 队列研究5229/332 队列研究2312/147 性别、年龄、吸烟、糖尿病、绿色蔬菜、腌制食品、油炸食品和白肉摄入 0.74
Chen模型[19] 中国 内部验证 横断面研究905/48 自助抽样法 年龄、性别、冠心病、鸡蛋摄入、排便频率 0.75
Wang模型[20] 中国 内部验证 病例对照研究病例：218对照：315 五折交叉验证法 16个单核苷酸多态性位点a 0.72
李娇元模型[21] 中国 无 病例对照研究病例：1066对照：3880 — 性别、年龄、吸烟、饮酒、7个单核苷酸多态性位点b 0.59
Tab 1 Review of risk prediction models for colorectal cancer
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