Zweig M H, Campbell G
Clinical Pathology Department, Warren G. Magnuson Clinical Center, Bethesda, MD.
Clin Chem. 1993 Apr;39(4):561-77.
The clinical performance of a laboratory test can be described in terms of diagnostic accuracy, or the ability to correctly classify subjects into clinically relevant subgroups. Diagnostic accuracy refers to the quality of the information provided by the classification device and should be distinguished from the usefulness, or actual practical value, of the information. Receiver-operating characteristic (ROC) plots provide a pure index of accuracy by demonstrating the limits of a test's ability to discriminate between alternative states of health over the complete spectrum of operating conditions. Furthermore, ROC plots occupy a central or unifying position in the process of assessing and using diagnostic tools. Once the plot is generated, a user can readily go on to many other activities such as performing quantitative ROC analysis and comparisons of tests, using likelihood ratio to revise the probability of disease in individual subjects, selecting decision thresholds, using logistic-regression analysis, using discriminant-function analysis, or incorporating the tool into a clinical strategy by using decision analysis.
实验室检测的临床性能可以用诊断准确性来描述，即正确地将受试者分类到临床相关亚组的能力。诊断准确性指的是分类设备所提供信息的质量，应与信息的有用性或实际实用价值区分开来。通过展示在整个操作条件范围内测试区分不同健康状态的能力极限，受试者操作特征（ROC）曲线提供了一个纯粹的准确性指标。此外，ROC曲线在评估和使用诊断工具的过程中占据核心或统一的位置。一旦生成曲线，用户就可以轻松地进行许多其他活动，如进行定量ROC分析和测试比较、使用似然比来修正个体受试者的疾病概率、选择决策阈值、使用逻辑回归分析、使用判别函数分析，或通过决策分析将该工具纳入临床策略。
