发表机构
Indian Institute of Technology Guwahati; Indian Statistical Institute, Chennai（印度理工学院古瓦哈提分校; 印度统计学院，金奈）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对右删失数据，提出时变双向部分AUC与部分Youden指数的非参数估计量，经模拟验证其可有效处理删失，并通过两个真实数据集示例说明方法的应用。
AI 中文摘要
在医学研究中，评估生物标志物的预测性能常受关注。基于受试者工作特征（ROC）曲线及其汇总指标（如曲线下面积AUC、Youden指数）的统计方法被广泛用于评估这些生物标志物的预后性能。在时间-事件研究中，由于疾病状态随时间变化及存在删失个体，ROC分析面临额外挑战。为解决这些问题，时变ROC曲线被提出。本文针对右删失数据，提出了一种时变双向部分AUC的非参数估计量；同时还讨论了右删失数据的部分Youden指数及相关的最优生物标志物临界值估计量。本文开展了广泛的模拟研究以探究所提估计量的有限样本性能，模拟研究表明，所提非参数估计量可有效处理右删失问题。最后，本文使用两个真实数据集对所提方法进行了示例说明，一个来自原发性胆汁性肝硬化研究，另一个来自乳腺癌国际联盟分子分类试验。
英文摘要
In medical research, it is often of interest to evaluate the predictive performance of a biomarker. Statistical approaches based on the Receiver Operating Characteristic (ROC) curve and its summary measures, such as the area under the curve (AUC) and the Youden index, are widely used to evaluate the prognostic performance of these biomarkers. In time-to-event studies, ROC analysis poses additional challenges due to change in disease status over time and the presence of censored individuals. To address these issues, time-dependent ROC curves were introduced. In this paper, we propose a non-parametric estimator of the time-dependent two-way partial AUC for right-censored data. We also discuss the partial Youden index and the associated optimal biomarker cutoff estimator for the right-censored data. We conduct an extensive simulation study to investigate the finite sample performance of the proposed estimators. The simulation study indicates that the proposed non-parametric estimators efficiently account for right censoring. Finally, we illustrate the proposed methods using two real data sets, one from the Primary Biliary Cirrhosis study and the other from the Molecular Taxonomy of Breast Cancer International Consortium trial.
CommentsI accidentally duplicated the second author's name during entry. I have now corrected it from 'Sudheesh Kumar KattumannilSudheesh Kumar Kattumannil' to 'Sudheesh Kumar Kattumannil'. Additionally, the corresponding author has now been clearly indicated
