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山东大学学报（医学版） ›› 2017, Vol. 55 ›› Issue (6): 114-118.doi: 10.6040/j.issn.1671-7554.0.2016.1275

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基于体检人群的非酒精性脂肪肝筛查工具的建立

蒋正1,2,申振伟1,2,张光3,李润滋1,2,曹瑾1,2,王丽4,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中心, 山东 济南 250012;3.山东大学附属千佛山医院健康管理中心, 山东 济南 250014;4.山东电力中心医院, 山东 济南 250012
  • 收稿日期:2016-10-09 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:
    国家国际科技合作专项项目(2014DFA32830)

Construction of a NAFLD screening tool based on health examination subjects

JIANG Zheng1,2, SHEN Zhenwei1,2, ZHANG Guang3, LI Runzi1,2, CAO Jin1,2, WANG Li4, 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, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan 250014, Shandong, China;
    4. Shandong Electric Power Central Hospital, Jinan 250012, Shandong, China
  • Received:2016-10-09 Online:2017-06-10 Published:2017-06-10

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摘要： 目的 建立一个非酒精性脂肪肝(NAFLD)筛查模型并对其进行验证。 方法 对“山东多中心健康管理纵向观察队列”中8 993名接受健康体检且无过量饮酒个体随机抽取80%进行建模,并做组内评价,剩余20%作组外评价。通过逐步Logistic回归,建立NAFLD筛查模型,并进行评价及验证。 结果 多因素Logistic回归分析表明,性别、体质量指数、高血压、血脂异常、谷草转氨酶/谷丙转氨酶(AST/ALT)和血糖(FBG)进入了模型,构建了NAFLD筛查模型并可通过计算得到脂肪肝指数(fatty liver index, FLI)。筛查模型的鉴别能力采用受试者工作特征曲线下面积(AUC)进行评价(组内:0.859,95%CI:0.851~0.867;组外:0.853,95%CI: 0.835~0.869)。当FLI≤1.25时排除疾病,组内和组外的阴性预测值分别为93.1%和93.3%,FLI≥2.25诊断为NAFLD,两组的阳性预测值分别为74.6%和72.7%。 结论 FLI是一个简单有效的筛查工具,可以用于高危人群的筛查,具有一定的实用价值。

关键词: 非酒精性脂肪肝, 筛查, 体检人群, 脂肪肝指数

Abstract: Objective To devise and verify a screening model for nonalcoholic fatty liver disease(NAFLD). Methods From the “Shandong Multi-center Longitudinal Cohort for Health Management”, 8,993 health examination clients without excessive drinking habits were randomly selected and divided into 2 groups, internal group(80% subjects, for derivation and internal assessment), and external group(20% subjects, for external assessment). Multivariate stepwise logistic regression was used to build a screening model, and prediction power of the model was assessed. Results Multivariate analysis demonstrated that gender, body mass index(BMI), hypertension, dyslipidemia, aspartate transaminase to alanine aminotransferase ratio(AST/ALT)and fasting blood glucose(FBG)were involved in the model and fatty liver index(FLI)could be constructed. The discriminatory power of the model was tested with the area under the receiver-operating characteristic curve(AUC),(0.859, 95%CI, 0.851 2-0.867 in the internal group, and 0.853, 95%CI, 0.835-0.869 in the external group). When FLI≤1.25 was used to exclude the possibility of NAFLD, the negative predictive value was 93.1% and 93.3% respectively for the internal and external group. When FLI≥2.25 was used to detect NAFLD, the positive predictive value was 74.6% and 72.7% respectively. Conclusion FLI is an effective screening tool for the identification of high-risk subjects of NAFLD.

Key words: Nonalcoholic fatty liver disease, Health examination clients, Fatty liver index, Screening

中图分类号: 

  • R575.5
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