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亚洲 2 型糖尿病发病风险预测模型的系统评价

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贺婷，袁丽 ，杨小玲，叶子溦，李饶，古艳 扫描二维码
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【摘要】 背景 2 型糖尿病（T2DM）的患病率不断上升。2021 年成年糖尿病患者人数最多的 10 个国家中，
有 6 个是亚洲国家。可靠的 T2DM 发病风险预测模型能够识别有患 T2DM 风险的个体，并可为开展针对性的预防干
预工作提供决策依据。目的 系统分析、评价亚洲 T2DM 发病风险预测模型，以期为 T2DM 的防治提供参考。方
法 于 2021 年 4 月，计算机检索 PubMed、EmBase、the Cochrane Library 获取有关亚洲 T2DM 发病风险预测模型的研
究，检索时限均为建库至 2021-04-01。由 2 名研究者独立筛选文献、提取资料后，应用预测模型研究偏倚风险评估
工具（PROBAST）评价纳入文献的偏倚风险和适用性。采用描述性分析法对模型的基本特征及纳入研究的偏倚风险与
适用性评价结果进行总结、分析。结果 共纳入 31 项亚洲 T2DM 发病风险预测模型研究，其中 17 项为前瞻性队列研
究，14 项为回顾性队列研究。纳入研究多采用 Cox 回归、Logistic 回归构建模型；5 项研究仅对模型进行了外部验证，
22 项研究仅对模型进行了内部验证，4 项研究采用内部验证与外部验证相结合的方法对模型进行了验证。模型的受试
者工作特征曲线下面积为 0.62~0.92，包含预测因子数量为 3~24 个。纳入研究均存在较高的偏倚风险，主要原因为对
连续变量的处理不合理、对缺失数据的处理不合理、忽略了模型的过度拟合问题等。结论 纳入的模型具有良好的预
测效能，可帮助医务人员早期识别 T2DM 发病高风险人群。未来，应对数据建模及统计分析方法进行改进，开发性能
优良、偏倚风险低的预测模型，注重对模型进行外部验证和重新校准。
【关键词】 糖尿病，2 型；预测模型；风险评分；系统评价；亚洲；循证医学
【中图分类号】 R 587.1 R 4 【文献标识码】 A DOI：10.12114/j.issn.1007-9572.2022.0358
贺婷，袁丽，杨小玲，等 . 亚洲 2 型糖尿病发病风险预测模型的系统评价［J］. 中国全科医学，2022，25（34）：
4267-4277.［www.chinagp.net］
HE T，YUAN L，YANG X L，et al. Risk prediction models for type 2 diabetes in Asian adults：a systematic review［J］.
Chinese General Practice，2022，25（34）：4267-4277.

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Risk Prediction Models for Type 2 Diabetes in Asian Adults：a Systematic Review HE Ting，YUAN Li ，YANG
Xiaoling，YE Ziwei，LI Rao，GU Yan
West China School of Nursing，Sichuan University/Department of Endocrinology & Metabolism，West China Hospital，Sichuan
University，Chengdu 610041，China
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Corresponding author：YUAN Li，Chief superintendent nurse，Master supervisor；E-mail：1409933235@qq.com
【Abstract】 Background The prevalence of type 2 diabetes mellitus（T2DM）is increasing throughout the world. Six out
of the top 10 countries with the highest number of adults with diabetes in 2021 were in Asia. Reliable type 2 diabetes risk prediction
models can identify individuals at risk of developing T2DM，which may provide a basis for decision-making in the prevention and
intervention of T2DM. Objective To perform a systematic review of risk prediction models for T2DM，providing a reference for the
prevention and treatment of T2DM. Methods In April 2021，we searched for studies on risk prediction models for T2DM in Asian
adults in databases of PubMed，EmBase，and the Cochrane Library from inception to April 1，2021. Two reviewers independently
screened the literature，extracted data，and evaluated the risk of bias and applicability of included studies using the Prediction model
Risk Of Bias Assessment Tool（PROBAST）. A descriptive analysis was used to summarise the basic characteristics of the models and
the risk of bias and applicability of included studies. Results A total of 31 studies were included，among which 17 are prospective
cohort studies and other 14 are retrospective cohort studies. Logistic regression and Cox regression were widely used to construct the
models. The models were externally validated in 5 studies，internally validated in 22 studies，and externally and internally validated in
4 studies. The number of predictors included in the models ranged from 3 to 24，with performance measured by the area under the curve
of receiver operating characteristic curve lying between 0.62 and 0.92. There was a high risk of bias in the included studies，which may
mainly due to inappropriate treatment of continuous variables and missing data，and ignoring the overfitting of the model. Conclusion

基金项目：四川省科技厅项目（2019YFS0305，2022YFS0271）；四川省卫健委课题（20PJ023）；四川大学华西医院学科卓越发展
1•3•5 工程临床研究孵化项目（2019HXFH045）
610041 四川省成都市，四川大学华西护理学院 / 四川大学华西医院内分泌代谢科
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通信作者：袁丽，主任护师，研究生导师；E-mail：1409933235@qq.com
本文数字出版日期：2022-09-29