Samawi Hani M, Yin Jingjing, Rochani Haresh, Panchal Viral
Department of Biostatistics, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA, USA.
Stat Med. 2017 Nov 20;36(26):4230-4240. doi: 10.1002/sim.7435. Epub 2017 Aug 15.
The receiver operating characteristic (ROC) curve is frequently used to evaluate and compare diagnostic tests. As one of the ROC summary indices, the Youden index measures the effectiveness of a diagnostic marker and enables the selection of an optimal threshold value (cut-off point) for the marker. Recently, the overlap coefficient, which captures the similarity between 2 distributions directly, has been considered as an alternative index for determining the diagnostic performance of markers. In this case, a larger overlap indicates worse diagnostic accuracy, and vice versa. This paper provides a graphical demonstration and mathematical derivation of the relationship between the Youden index and the overlap coefficient and states their advantages over the most popular diagnostic measure, the area under the ROC curve. Furthermore, we outline the differences between the Youden index and overlap coefficient and identify situations in which the overlap coefficient outperforms the Youden index. Numerical examples and real data analysis are provided.
受试者工作特征（ROC）曲线常用于评估和比较诊断测试。作为ROC汇总指标之一，约登指数衡量诊断标志物的有效性，并能够为该标志物选择最佳阈值（临界点）。最近，直接捕捉两个分布之间相似性的重叠系数，已被视为确定标志物诊断性能的替代指标。在这种情况下，重叠越大表明诊断准确性越差，反之亦然。本文提供了约登指数与重叠系数之间关系的图形演示和数学推导，并阐述了它们相对于最常用的诊断指标——ROC曲线下面积的优势。此外，我们概述了约登指数与重叠系数之间的差异，并确定了重叠系数优于约登指数的情况。文中提供了数值示例和实际数据分析。
