Blanche Paul, Dartigues Jean-François, Jacqmin-Gadda Hélène
Université Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France.
Biom J. 2013 Sep;55(5):687-704. doi: 10.1002/bimj.201200045. Epub 2013 Jun 21.
To quantify the ability of a marker to predict the onset of a clinical outcome in the future, time-dependent estimators of sensitivity, specificity, and ROC curve have been proposed accounting for censoring of the outcome. In this paper, we review these estimators, recall their assumptions about the censoring mechanism and highlight their relationships and properties. A simulation study shows that marker-dependent censoring can lead to important biases for the ROC estimators not adapted to this case. A slight modification of the inverse probability of censoring weighting estimators proposed by Uno et al. (2007) and Hung and Chiang (2010a) performs as well as the nearest neighbor estimator of Heagerty et al. (2000) in the simulation study and has interesting practical properties. Finally, the estimators were used to evaluate abilities of a marker combining age and a cognitive test to predict dementia in the elderly. Data were obtained from the French PAQUID cohort. The censoring appears clearly marker-dependent leading to appreciable differences between ROC curves estimated with the different methods.
为了量化一种标志物预测未来临床结局发生的能力，已经提出了考虑结局删失情况的敏感性、特异性和ROC曲线的时间依赖估计量。在本文中，我们回顾这些估计量，回忆它们关于删失机制的假设，并强调它们之间的关系和性质。一项模拟研究表明，标志物依赖的删失可能会给未针对此情况进行调整的ROC估计量带来重大偏差。对Uno等人（2007年）以及Hung和Chiang（2010a）提出的删失加权估计量的逆概率进行轻微修改后，在模拟研究中的表现与Heagerty等人（2000年）的最近邻估计量相当，并且具有有趣的实际性质。最后，这些估计量被用于评估结合年龄和认知测试的一种标志物预测老年人痴呆的能力。数据来自法国PAQUID队列。删失情况明显依赖于标志物，导致用不同方法估计的ROC曲线之间存在显著差异。
