Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker
Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker
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DOI：
10.1093/aje/kwh101
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发表时间：
2004-05-01
影响因子：
5
通讯作者：
Newcomb, P
中科院分区：
文献类型：
--
作者：
Pepe, MS;Janes, H;Newcomb, P
一种与结果(或疾病)密切相关的标记物通常被认为是根据当前或未来结果对人进行分类的有效方法。然而，要使这一假设成为现实，相关的优势比必须达到流行病学研究中罕见的程度。本文举例说明了赔率比与接收器工作特性曲线之间的关系，例如，赔率比高达3的标记实际上是一个非常差的分类工具。如果标记将10%的对照识别为阳性(假阳性)，并且优势比为3，那么它将正确地识别只有25%的病例为阳性(真阳性)。作者们指出，单一的关联性衡量标准，如赔率，并不能有意义地描述标记者对受试者进行分类的能力。描述了用于评估和报告标记的分类能力的适当统计方法。此外，还说明了在Logistic回归模型中使用更传统的基于参数的方法存在的严重缺陷。
A marker strongly associated with outcome (or disease) is often assumed to be effective for classifying persons according to their current or future outcome. However, for this assumption to be true, the associated odds ratio must be of a magnitude rarely seen in epidemiologic studies. In this paper, an illustration of the relation between odds ratios and receiver operating characteristic curves shows, for example, that a marker with an odds ratio of as high as 3 is in fact a very poor classification tool. If a marker identifies 10% of controls as positive (false positives) and has an odds ratio of 3, then it will correctly identify only 25% of cases as positive (true positives). The authors illustrate that a single measure of association such as an odds ratio does not meaningfully describe a marker's ability to classify subjects. Appropriate statistical methods for assessing and reporting the classification power of a marker are described. In addition, the serious pitfalls of using more traditional methods based on parameters in logistic regression models are illustrated.