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首页> 外文期刊>AStA Advances in statistical analysis >Biomarker assessment in ROC curve analysis using the length of the curve as an index of diagnostic accuracy: the binormal model framework
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Biomarker assessment in ROC curve analysis using the length of the curve as an index of diagnostic accuracy: the binormal model framework

机译：使用曲线长度作为诊断准确性的索引的ROC曲线分析中的生物标志物评估：双重模型框架

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摘要

In receiver operating characteristic (ROC) curve analysis, the area under the curve (AUC) is undoubtedly the most widely used index of diagnostic accuracy for the assessment of the utility of a biomarker or for the comparison of competing biomarkers. Along with the AUC, the maximum of the Youden index,J, is often used both as an index of diagnostic accuracy and as a tool useful for the estimation of an optimal cutoff point that can be used for diagnostic purposes based on the biomarker under consideration. In this work, we study the utility of the length of the binormal model-based ROC curve (LoC) as an index of diagnostic accuracy for biomarker evaluation. Estimation procedures for LoC, described in this article, are based either on normality assumptions or on the same assumptions after a Box-Cox transformation to normality. Two simulation studies are considered. In the first, the estimation procedures for LoC are compared in terms of bias and root mean squared error, while in the second one, the performance of LoC is compared with approaches based on AUC andJ, both for the case of the assessment of a single biomarker and for the comparison of two biomarkers, in a parametric framework. We provide an interpretation for the proposed index and illustrate with an application on biomarkers from a colorectal cancer study.
机译：在接收器操作特征（ROC）曲线分析中，曲线（AUC）下的区域无疑是用于评估生物标志物的效用或竞争生物标志物的比较的最广泛使用的诊断准确性指标。随着AUC的，YENEN指数j的最大值通常用作诊断准确性的索引，并且作为用于估计最佳截止点的工具，该工具可用于基于所考虑的生物标志物的诊断目的。在这项工作中，我们研究了基于双向基于模型的ROC曲线（LOC）的长度的效用作为生物标志物评估的诊断准确性指标。本文中描述的LOC的估计程序基于正常性假设或在盒子Cox转换到正常性之后的相同假设上。考虑了两项模拟研究。首先，在偏置和根均方误差方面比较LOC的估计程序，而在第二个中，将LOC的性能与基于AUC和J的方法进行比较，这两者都是对单一的评估的情况生物标志物和两个生物标志物的比较，在参数框架中。我们为拟议的指数提供了解释，并在与结直肠癌研究中的生物标志物的应用中说明。

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