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用于识别有发展为 2 型糖尿病风险的个体的风险评估工具。

Risk assessment tools for identifying individuals at risk of developing type 2 diabetes.

机构信息

Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany.

出版信息

Epidemiol Rev. 2011;33(1):46-62. doi: 10.1093/epirev/mxq019. Epub 2011 May 27.

Abstract

Trials have demonstrated the preventability of type 2 diabetes through lifestyle modifications or drugs in people with impaired glucose tolerance. However, alternative ways of identifying people at risk of developing diabetes are required. Multivariate risk scores have been developed for this purpose. This article examines the evidence for performance of diabetes risk scores in adults by 1) systematically reviewing the literature on available scores and 2) their validation in external populations; and 3) exploring methodological issues surrounding the development, validation, and comparison of risk scores. Risk scores show overall good discriminatory ability in populations for whom they were developed. However, discriminatory performance is more heterogeneous and generally weaker in external populations, which suggests that risk scores may need to be validated within the population in which they are intended to be used. Whether risk scores enable accurate estimation of absolute risk remains unknown; thus, care is needed when using scores to communicate absolute diabetes risk to individuals. Several risk scores predict diabetes risk based on routine noninvasive measures or on data from questionnaires. Biochemical measures, in particular fasting plasma glucose, can improve prediction of such models. On the other hand, usefulness of genetic profiling currently appears limited.

摘要

研究表明,通过生活方式改变或药物治疗,可以预防糖耐量受损人群发生 2 型糖尿病。然而,我们需要寻找其他方法来识别有发生糖尿病风险的人群。为此,已经开发了多种多变量风险评分。本文通过以下三个方面,探讨了成人糖尿病风险评分的表现证据:1)系统地回顾现有评分的文献;2)在外部人群中验证;3)探索围绕风险评分的开发、验证和比较的方法学问题。对于开发风险评分的人群,风险评分总体上显示出良好的区分能力。然而,在外部人群中,区分性能更加多样且通常较弱,这表明风险评分可能需要在其预期使用的人群中进行验证。风险评分是否能够准确估计绝对风险仍然未知;因此,在使用评分向个体传达绝对糖尿病风险时需要谨慎。一些风险评分基于常规的非侵入性测量或问卷调查数据来预测糖尿病风险。生化指标,特别是空腹血浆葡萄糖,可以改善这些模型的预测。另一方面,目前看来基因分析的应用价值有限。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/013a/3132807/4473345e26ea/ajerevmxq019f01_lw.jpg

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