Parodi S, Muselli M, Carlini B, Fontana V, Haupt R, Pistoia V, Corrias M V
Clinical Epidemiology Unit, Department of Epidemiology and Prevention, IRCCS AOU San Martino-IST, Genoa, Italy
Institute of Electronics, Computer and Telecommunication Engineering, Genoa, Italy.
Stat Methods Med Res. 2016 Feb;25(1):294-314. doi: 10.1177/0962280212452199. Epub 2012 Jun 26.
In Clinical Epidemiology, receiver operating characteristic (ROC) analysis is a standard approach for the evaluation of the performance of diagnostic tests for binary classification based on a tumour marker distribution. The area under a ROC curve is a popular indicator of test accuracy, but its use has been questioned when the curve is asymmetric. This situation often happens when the marker concentrations overlap in the two groups under study in the range of low specificity, corresponding to a subset of values useless for classification purposes (non-informative values). The partial area under the curve at a high specificity threshold has been proposed as an alternative, but a method to identify an optimal cut-off that separates informative from non-informative values is not yet available. In this study, a new statistical approach is proposed to perform this task. Furthermore, a statistical test associated with the area under a ROC curve corresponding to informative values only (restricted ROC curve) is provided and its properties are explored by extensive simulations. Finally, the proposed method is applied to a real data set containing peripheral blood levels of six tumour markers proposed for the diagnosis of neuroblastoma. A new approach to combine couples of markers for classification purposes is also illustrated.
在临床流行病学中，受试者操作特征（ROC）分析是一种基于肿瘤标志物分布评估二元分类诊断试验性能的标准方法。ROC曲线下面积是检验准确性的常用指标，但当曲线不对称时，其应用受到质疑。这种情况经常发生在低特异性范围内研究的两组中标志物浓度重叠时，这对应于对分类无用的一部分值（非信息性值）。有人提出在高特异性阈值下的曲线下部分面积作为替代方法，但尚未有一种方法来确定将信息性值与非信息性值分开的最佳截断点。在本研究中，提出了一种新的统计方法来执行此任务。此外，还提供了一种仅与对应于信息性值的ROC曲线下面积相关的统计检验（受限ROC曲线），并通过广泛的模拟探索了其性质。最后，将所提出的方法应用于包含为神经母细胞瘤诊断提出6种肿瘤标志物外周血水平的真实数据集。还阐述了一种为分类目的组合标志物对的新方法。
