Choi B C
Bureau of Cardio-Respiratory Diseases and Diabetes, Laboratory Centre for Disease Control, Health Canada, Ottawa, Ontario.
Am J Epidemiol. 1998 Dec 1;148(11):1127-32. doi: 10.1093/oxfordjournals.aje.a009592.
This paper clarifies two important concepts in clinical epidemiology: the slope of a receiver operating characteristic (ROC) curve and the likelihood ratio. It points out that there are three types of slopes in an ROC curve--the tangent at a point on the curve, the slope between the origin and a point on the curve, and the slope between two points on the curve. It also points out that there are three types of likelihood ratios that can be defined for a diagnostic test that produces results on a continuous scale--the likelihood ratio for a particular single test value, the likelihood ratio for a positive test result, and the likelihood ratio for a test result in a particular level or category. It further illustrates mathematically and empirically the following three relations between these various definitions of slopes and likelihood ratios: 1) the tangent at a point on the ROC curve corresponds to the likelihood ratio for a single test value represented by that point; 2) the slope between the origin and a point on the curve corresponds to the positive likelihood ratio using the point as a criterion for positivity; and 3) the slope between two points on the curve corresponds to the likelihood ratio for a test result in a defined level bounded by the two points. The likelihood ratio for a single test value is considered an important parameter for evaluating diagnostic tests, but it is not easily estimable directly from laboratory data because of limited sample size. However, by using ROC analysis, the likelihood ratio for a single test value can be easily measured from the tangent. It is suggested that existing ROC analysis software be revised to provide estimates for tangents at various points on the ROC curve.
受试者工作特征(ROC)曲线的斜率和似然比。指出ROC曲线存在三种类型的斜率——曲线上某一点的切线斜率、原点与曲线上某一点之间的斜率以及曲线上两点之间的斜率。还指出,对于产生连续尺度结果的诊断测试,可以定义三种类型的似然比——特定单个测试值的似然比、阳性测试结果的似然比以及特定水平或类别的测试结果的似然比。本文进一步从数学和实证角度说明了这些斜率和似然比的各种定义之间的以下三种关系:1)ROC曲线上某一点的切线对应于该点所代表的单个测试值的似然比;2)原点与曲线上某一点之间的斜率对应于以该点为阳性标准的阳性似然比;3)曲线上两点之间的斜率对应于由这两点界定的定义水平内的测试结果的似然比。单个测试值的似然比被认为是评估诊断测试的一个重要参数,但由于样本量有限,很难直接从实验室数据中估计出来。然而,通过使用ROC分析,可以很容易地从切线上测量单个测试值的似然比。建议对现有的ROC分析软件进行修订,以提供ROC曲线上各点切线的估计值。