Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
J Thorac Oncol. 2010 Sep;5(9):1315-6. doi: 10.1097/JTO.0b013e3181ec173d.
The performance of a diagnostic test in the case of a binary predictor can be evaluated using the measures of sensitivity and specificity. However, in many instances, we encounter predictors that are measured on a continuous or ordinal scale. In such cases, it is desirable to assess performance of a diagnostic test over the range of possible cutpoints for the predictor variable. This is achieved by a receiver operating characteristic (ROC) curve that includes all the possible decision thresholds from a diagnostic test result. In this brief report, we discuss the salient features of the ROC curve, as well as discuss and interpret the area under the ROC curve, and its utility in comparing two different tests or predictor variables of interest.
对于二项预测指标，诊断测试的性能可以使用灵敏度和特异性等指标进行评估。但是，在许多情况下，我们遇到的预测指标是连续或有序的。在这种情况下，理想情况下是在预测变量的所有可能切点范围内评估诊断测试的性能。这可以通过包括诊断测试结果的所有可能决策阈值的受试者工作特征 (ROC) 曲线来实现。在本简要报告中，我们讨论了 ROC 曲线的显著特征，以及讨论和解释 ROC 曲线下的面积，及其在比较两种不同的测试或感兴趣的预测变量方面的效用。
