Concordance Measures and Time-Dependent ROC Methods.

Q3 Medicine Biostatistics and Epidemiology Pub Date : 2021-01-01 Epub Date: 2021-05-25 DOI:10.1080/24709360.2021.1926189
Norberto Pantoja-Galicia, Olivia I Okereke, Deborah Blacker, Rebecca A Betensky
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Abstract

The receiver operating characteristic (ROC) curve displays sensitivity versus 1-specificity over a set of thresholds. The area under the ROC curve (AUC) is a global scalar summary of this curve. In the context of time-dependent ROC methods, we are interested in global scalar measures that summarize sequences of time-dependent AUCs over time. The concordance probability is a candidate for such purposes. The concordance probability can provide a global assessment of the discrimination ability of a test for an event that occurs at random times and may be right censored. If the test adequately differentiates between subjects who survive longer times and those who survive shorter times, this will assist clinical decisions. In this context the concordance probability may support assessment of precision medicine tools based on prognostic biomarkers models for overall survival. Definitions of time-dependent sensitivity and specificity are reviewed. Some connections between such definitions and concordance measures are also reviewed and we establish new connections via new measures of global concordance. We explore the relationship between such measures and their corresponding time-dependent AUC. To illustrate these concepts, an application in the context of Alzheimer's disease is presented.

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一致性测量和时间相关 ROC 方法。
接收者操作特征曲线(ROC)显示一组阈值的灵敏度与特异性的关系。ROC 曲线下面积(AUC)是该曲线的全局标量总结。对于随时间变化的 ROC 方法,我们感兴趣的是能总结随时间变化的 AUC 序列的全局标量指标。一致性概率就是这样一个候选指标。一致性概率可以全面评估测试对随机发生且可能是右删失的事件的区分能力。如果测试能充分区分存活时间较长的受试者和存活时间较短的受试者,这将有助于临床决策。在这种情况下,一致性概率可支持对基于预后生物标志物模型的精准医疗工具进行评估,以确定总生存期。本文回顾了与时间相关的敏感性和特异性的定义。我们还回顾了此类定义与一致性测量之间的一些联系,并通过全局一致性的新测量方法建立了新的联系。我们还探讨了这些指标与其相应的随时间变化的 AUC 之间的关系。为了说明这些概念,我们介绍了在阿尔茨海默病中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biostatistics and Epidemiology
Biostatistics and Epidemiology Medicine-Health Informatics
CiteScore
1.80
自引率
0.00%
发文量
23
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