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心血管疾病研究中的风险预测模型概述。

Overview of risk prediction models in cardiovascular disease research.

作者信息

Cui Jisheng

机构信息

World Health Organization Collaborating Centre for Obesity Prevention, Deakin University, Melbourne, Australia.

出版信息

Ann Epidemiol. 2009 Oct;19(10):711-7. doi: 10.1016/j.annepidem.2009.05.005. Epub 2009 Jul 22.

Abstract

Many risk prediction models have been developed for cardiovascular diseases in different countries during the past three decades. However, there has not been consistent agreement regarding how to appropriately assess a risk prediction model, especially when new markers are added to an established risk prediction model. Researchers often use the area under the receiver operating characteristic curve (ROC) to assess the discriminatory ability of a risk prediction model. However, recent studies suggest that this method has serious limitations and cannot be the sole approach to evaluate the usefulness of a new marker in clinical and epidemiological studies. To overcome the shortcomings of this traditional method, new assessment methods have been proposed. The aim of this article is to overview various risk prediction models for cardiovascular diseases, to describe the receiver operating characteristic curve method and discuss some new assessment methods proposed recently. Some of the methods were illustrated with figures from a cardiovascular disease study in Australia.

摘要

在过去三十年里,不同国家已开发出许多用于心血管疾病的风险预测模型。然而,对于如何恰当地评估一个风险预测模型,尤其是当新的标志物被添加到已有的风险预测模型中时,尚未达成一致意见。研究人员通常使用受试者工作特征曲线(ROC)下的面积来评估风险预测模型的辨别能力。然而,最近的研究表明,这种方法有严重的局限性,不能作为评估新标志物在临床和流行病学研究中有用性的唯一方法。为克服这种传统方法的缺点,已提出了新的评估方法。本文的目的是概述各种心血管疾病的风险预测模型,描述受试者工作特征曲线方法,并讨论最近提出的一些新的评估方法。其中一些方法用澳大利亚一项心血管疾病研究的数据进行了说明。

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