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A method for representing the overall discriminative capacity of binary markers with right-censored time-to-event endpoints

机译:一种表示具有右删减时间到事件终点的二进制标记的总体判别能力的方法

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Survival curves are a popular tool for representing the association between a binary marker and the risk of an event. The separation between the survival curves in patients with a positive marker (high-risk group) and a negative marker (low-risk group) reflects the prognostic ability of the marker. In this article, we propose an alternative graphical approach to represent the discriminative capacity of the marker - a receiver operating characteristic (ROC) curve, tentatively named prognostic ROC curve - obtained by plotting 1 minus the survival in the high-risk group against 1 minus the survival in the low-risk group. The area under the curve corresponds to the probability that a patient in the low-risk group has a longer lifetime than a patient in the high-risk group. The prognostic ROC curve provides complementary information compared with survival curves. However, when the survival functions do not reach 0, the prognostic ROC curve is incomplete. We show how a range of possible values for the area under the curve can be derived in this situation. A simulation study is performed to analyze the accuracy of this methodology, which is also illustrated by applications to the survival of patients with brain metastases and survival of kidney transplant recipients.
机译:生存曲线是一种流行的工具,用于表示二元标记和事件风险之间的关联。具有阳性标记物(高风险组)和阴性标记物(低风险组)的患者的生存曲线之间的分离反映了标记物的预后能力。在本文中,我们提出了一种替代的图形方法来表示标记的区分能力-接收者操作特征(ROC)曲线,暂定为预后ROC曲线-通过将1减去高风险组的生存率与1减去得到低危人群的生存率。曲线下的面积对应于低风险组患者的寿命比高风险组患者更长的概率。与生存曲线相比,预后的ROC曲线可提供补充信息。但是,当生存函数未达到0时,ROC曲线的预后就不完整。我们展示了在这种情况下如何得出曲线下面积的可能值范围。进行了仿真研究以分析该方法的准确性,这也通过在脑转移患者的生存和肾移植受者的生存中的应用来说明。

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