Literature DB >> 22987578

Nonparametric receiver operating characteristic-based evaluation for survival outcomes.

Xiao Song1, Xiao-Hua Zhou, Shuangge Ma.   

Abstract

For censored survival outcomes, it can be of great interest to evaluate the predictive power of individual markers or their functions. Compared with alternative evaluation approaches, approaches based on the time-dependent receiver operating characteristics (ROC) rely on much weaker assumptions, can be more robust, and hence are preferred. In this article, we examine evaluation of markers' predictive power using the time-dependent ROC curve and a concordance measure that can be viewed as a weighted area under the time-dependent area under the ROC curve profile. This study significantly advances from existing time-dependent ROC studies by developing nonparametric estimators of the summary indexes and, more importantly, rigorously establishing their asymptotic properties. It reinforces the statistical foundation of the time-dependent ROC-based evaluation approaches for censored survival outcomes. Numerical studies, including simulations and application to an HIV clinical trial, demonstrate the satisfactory finite-sample performance of the proposed approaches.
Copyright © 2012 John Wiley & Sons, Ltd.

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Year:  2012        PMID: 22987578      PMCID: PMC3743052          DOI: 10.1002/sim.5386

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  11 in total

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Authors:  J Brooks Jackson; Philippa Musoke; Thomas Fleming; Laura A Guay; Danstan Bagenda; Melissa Allen; Clemensia Nakabiito; Joseph Sherman; Paul Bakaki; Maxensia Owor; Constance Ducar; Martina Deseyve; Anthony Mwatha; Lynda Emel; Corey Duefield; Mark Mirochnick; Mary Glenn Fowler; Lynne Mofenson; Paolo Miotti; Maria Gigliotti; Dorothy Bray; Francis Mmiro
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  4 in total

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3.  A numerical strategy to evaluate performance of predictive scores via a copula-based approach.

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Journal:  Stat Med       Date:  2020-05-11       Impact factor: 2.373

4.  Time-dependent ROC curve analysis in medical research: current methods and applications.

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Journal:  BMC Med Res Methodol       Date:  2017-04-07       Impact factor: 4.615

  4 in total

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