McClish D K
Department of Biostatistics, Medical College of Virginia, Richmond, VA 23298.
Med Decis Making. 1990 Oct-Dec;10(4):283-7. doi: 10.1177/0272989X9001000406.
Many indices have been proposed for summarizing the information contained in the ROC curve. When comparing two ROC curves, though, there are times when global summary measures are either not optimal or not appropriate. The author presents a method for directly comparing true-positive rates for two diagnostic, screening or prognostic tools, determining over what range of false-positive values the tests differ. The method is applicable for independent or dependent samples. An example concerning gallium citrate imaging is presented, as well as an example using a prognostic index for severity of illness in the ICU. The range of false-positive rates for which the ROC curves differ is determined for each example.
已经提出了许多指标来总结ROC曲线中包含的信息。然而，在比较两条ROC曲线时，有时全局汇总指标既不是最优的，也不合适。作者提出了一种直接比较两种诊断、筛查或预后工具的真阳性率的方法，确定在哪些假阳性值范围内测试结果存在差异。该方法适用于独立样本或相关样本。文中给出了一个关于枸橼酸镓成像的例子，以及一个使用ICU中疾病严重程度预后指数的例子。针对每个例子，确定了ROC曲线存在差异的假阳性率范围。
