Quantifying diagnostic accuracy improvement of new biomarkers for competing risk outcomes
Quantifying diagnostic accuracy improvement of new biomarkers for competing risk outcomes
复制标题
量化新生物标志物诊断准确性的提高，以应对竞争风险结果
DOI：
10.1093/biostatistics/kxaa048
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发表时间：
2020
期刊：
影响因子：
2.1
通讯作者：
Becker, James T
中科院分区：
文献类型：
--
作者：
Wang, Zheng;Cheng, Yu;Seaberg, Eric C;Becker, James T
净重分类改进(NRI)和综合判别改进(IDI)最初被提出用来表征当新的生物标记物被添加到回归模型中时，预测二元结果的准确性的提高。这两个指数已经从二元结果扩展到多类别和生存结果。在一项艾滋病研究中，认知障碍的发生是通过死亡审查的竞争风险，我们将NRI和IDI扩展到竞争风险结果，通过使用累积关联函数来量化竞争事件的累积风险，并采用多类别结果的两个指数的定义。通过逆概率加权处理因独立审查而导致的“遗漏”类别。考虑了各种竞争风险模型，如Fine和Gray、多状态和多项Logistic模型。给出了从竞争风险数据中估计NRI和IDI的方法。NRI的推论是基于其估计量的渐近正态来构造的，IDI采用的是偏差修正的加速Bootstrap过程。仿真结果表明，所提出的推理过程具有很好的性能。多中心艾滋病队列研究被用来说明扩展的NRI和IDI对于相互竞争的风险结果的实际效用。
The net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) were originally proposed to characterize accuracy improvement in predicting a binary outcome, when new biomarkers are added to regression models. These two indices have been extended from binary outcomes to multi-categorical and survival outcomes. Working on an AIDS study where the onset of cognitive impairment is competing risk censored by death, we extend the NRI and the IDI to competing risk outcomes, by using cumulative incidence functions to quantify cumulative risks of competing events, and adopting the definitions of the two indices for multi-category outcomes. The “missing” category due to independent censoring is handled through inverse probability weighting. Various competing risk models are considered, such as the Fine and Gray, multistate, and multinomial logistic models. Estimation methods for the NRI and the IDI from competing risk data are presented. The inference for the NRI is constructed based on asymptotic normality of its estimator, and the bias-corrected and accelerated bootstrap procedure is used for the IDI. Simulations demonstrate that the proposed inferential procedures perform very well. The Multicenter AIDS Cohort Study is used to illustrate the practical utility of the extended NRI and IDI for competing risk outcomes.