Suppr超能文献

比较两个具有右删失生存结局的相关C指数:一种一次性非参数方法。

Comparing two correlated C indices with right-censored survival outcome: a one-shot nonparametric approach.

作者信息

Kang Le, Chen Weijie, Petrick Nicholas A, Gallas Brandon D

机构信息

Department of Biostatistics, School of Medicine, Virginia Commonwealth University, Richmond, VA, U.S.A.; Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, U.S.A.

出版信息

Stat Med. 2015 Feb 20;34(4):685-703. doi: 10.1002/sim.6370. Epub 2014 Nov 17.

Abstract

The area under the receiver operating characteristic curve is often used as a summary index of the diagnostic ability in evaluating biomarkers when the clinical outcome (truth) is binary. When the clinical outcome is right-censored survival time, the C index, motivated as an extension of area under the receiver operating characteristic curve, has been proposed by Harrell as a measure of concordance between a predictive biomarker and the right-censored survival outcome. In this work, we investigate methods for statistical comparison of two diagnostic or predictive systems, of which they could either be two biomarkers or two fixed algorithms, in terms of their C indices. We adopt a U-statistics-based C estimator that is asymptotically normal and develop a nonparametric analytical approach to estimate the variance of the C estimator and the covariance of two C estimators. A z-score test is then constructed to compare the two C indices. We validate our one-shot nonparametric method via simulation studies in terms of the type I error rate and power. We also compare our one-shot method with resampling methods including the jackknife and the bootstrap. Simulation results show that the proposed one-shot method provides almost unbiased variance estimations and has satisfactory type I error control and power. Finally, we illustrate the use of the proposed method with an example from the Framingham Heart Study.

摘要

当临床结局(真值)为二元变量时,在评估生物标志物时,受试者工作特征曲线下面积常被用作诊断能力的汇总指标。当临床结局为右删失生存时间时,作为受试者工作特征曲线下面积的扩展,Harrell提出了C指数,作为预测生物标志物与右删失生存结局之间一致性的一种度量。在这项工作中,我们研究了两种诊断或预测系统(它们可以是两种生物标志物或两种固定算法)在C指数方面进行统计比较的方法。我们采用基于U统计量的C估计量,其渐近正态分布,并开发了一种非参数分析方法来估计C估计量的方差以及两个C估计量的协方差。然后构建z检验来比较两个C指数。我们通过模拟研究在I型错误率和检验效能方面验证了我们的一次性非参数方法。我们还将我们的一次性方法与包括刀切法和自助法在内的重抽样方法进行了比较。模拟结果表明,所提出的一次性方法提供了几乎无偏的方差估计,并且具有令人满意的I型错误控制和检验效能。最后,我们用弗明汉心脏研究中的一个例子说明了所提出方法的应用。

相似文献

1
Comparing two correlated C indices with right-censored survival outcome: a one-shot nonparametric approach.
Stat Med. 2015 Feb 20;34(4):685-703. doi: 10.1002/sim.6370. Epub 2014 Nov 17.
2
Bootstrap-based procedures for inference in nonparametric receiver-operating characteristic curve regression analysis.
Stat Methods Med Res. 2018 Mar;27(3):740-764. doi: 10.1177/0962280217742542. Epub 2017 Dec 12.
3
Jackknife variance of the partial area under the empirical receiver operating characteristic curve.
Stat Methods Med Res. 2017 Apr;26(2):528-541. doi: 10.1177/0962280214551190. Epub 2014 Sep 16.
4
Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate.
Stat Med. 2016 Mar 30;35(7):1090-102. doi: 10.1002/sim.6769. Epub 2015 Oct 20.
6
Combining biomarkers for classification with covariate adjustment.
Stat Med. 2017 Jul 10;36(15):2347-2362. doi: 10.1002/sim.7274. Epub 2017 Mar 9.
7
On comparing 2 correlated C indices with censored survival data.
Stat Med. 2017 Nov 10;36(25):4041-4049. doi: 10.1002/sim.7414. Epub 2017 Jul 31.
8
Smooth time-dependent receiver operating characteristic curve estimators.
Stat Methods Med Res. 2018 Mar;27(3):651-674. doi: 10.1177/0962280217740786. Epub 2017 Nov 29.
9
A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size.
Stat Methods Med Res. 2017 Dec;26(6):2603-2621. doi: 10.1177/0962280215602040. Epub 2015 Aug 30.
10
Optimal linear combination of biomarkers for multi-category diagnosis.
Stat Med. 2016 Jan 30;35(2):202-13. doi: 10.1002/sim.6622. Epub 2015 Aug 6.

引用本文的文献

4
Multi-cohort machine learning identifies predictors of cognitive impairment in Parkinson's disease.
NPJ Digit Med. 2025 Jul 26;8(1):482. doi: 10.1038/s41746-025-01862-1.
8
Oral microbiota signature predicts the prognosis of colorectal carcinoma.
NPJ Biofilms Microbiomes. 2025 May 5;11(1):71. doi: 10.1038/s41522-025-00702-0.
10
Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images: PRESENT SHD.
J Am Coll Cardiol. 2025 Apr 1;85(12):1302-1313. doi: 10.1016/j.jacc.2025.01.030.

本文引用的文献

1
Variances and Covariances of Kendall's Tau and Their Estimation.
Multivariate Behav Res. 1991 Oct 1;26(4):693-707. doi: 10.1207/s15327906mbr2604_6.
2
On the assessment of the added value of new predictive biomarkers.
BMC Med Res Methodol. 2013 Jul 29;13:98. doi: 10.1186/1471-2288-13-98.
3
Misuse of DeLong test to compare AUCs for nested models.
Stat Med. 2012 Oct 15;31(23):2577-87. doi: 10.1002/sim.5328. Epub 2012 Mar 13.
4
Quantifying discrimination of Framingham risk functions with different survival C statistics.
Stat Med. 2012 Jul 10;31(15):1543-53. doi: 10.1002/sim.4508. Epub 2012 Feb 17.
5
On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data.
Stat Med. 2011 May 10;30(10):1105-17. doi: 10.1002/sim.4154. Epub 2011 Jan 13.
6
One statistical test is sufficient for assessing new predictive markers.
BMC Med Res Methodol. 2011 Jan 28;11:13. doi: 10.1186/1471-2288-11-13.
8
Maximum likelihood ratio tests for comparing the discriminatory ability of biomarkers subject to limit of detection.
Biometrics. 2008 Sep;64(3):895-903. doi: 10.1111/j.1541-0420.2007.00941.x. Epub 2007 Nov 19.
9
Receiver-operating characteristic analysis for evaluating diagnostic tests and predictive models.
Circulation. 2007 Feb 6;115(5):654-7. doi: 10.1161/CIRCULATIONAHA.105.594929.
10
An ROC-type measure of diagnostic accuracy when the gold standard is continuous-scale.
Stat Med. 2006 Feb 15;25(3):481-93. doi: 10.1002/sim.2228.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验