Treatment selection markers are generally sought for when the benefit of an innovative treatment in comparison with a reference treatment is considered, and this benefit is suspected to vary according to the characteristics of the patients. Classically, such quantitative markers are detected through testing a marker-by-treatment interaction in a parametric regression model. Most alternative methods rely on modeling the risk of event occurrence in each treatment arm or the benefit of the innovative treatment over the marker values, but with assumptions that may be difficult to verify. Herein, a simple non-parametric approach is proposed to detect and assess the general capacity of a quantitative marker for treatment selection when no overall difference in efficacy could be demonstrated between two treatments in a clinical trial. This graphical method relies on the area between treatment-arm-specific receiver operating characteristic curves (ABC), which reflects the treatment selection capacity of the marker. A simulation study assessed the inference properties of the ABC estimator and compared them with other parametric and non-parametric indicators. The simulations showed that the estimate of the ABC had low bias, power comparable to parametric indicators, and that its confidence interval had a good coverage probability (better than the other non-parametric indicator in some cases). Thus, the ABC is a good alternative to parametric indicators. The ABC method was applied to data of the PETACC-8 trial that investigated FOLFOX4 versus FOLFOX4 + cetuximab in stage III colon adenocarcinoma. It enabled the detection of a treatment selection marker: the DDR2 gene.

中文翻译：

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ROC 曲线之间的面积，一种评估用于患者治疗选择的生物标志物的非参数方法

当考虑创新治疗与参考治疗相比的益处时，通常会寻找治疗选择标记，并且怀疑这种益处会根据患者的特征而有所不同。传统上，通过在参数回归模型中测试标记与治疗的相互作用来检测此类定量标记。大多数替代方法依赖于对每个治疗组中事件发生的风险或创新治疗对标记值的益处进行建模，但假设可能难以验证。在此，提出了一种简单的非参数方法来检测和评估用于治疗选择的定量标记的一般能力，当在临床试验中的两种治疗之间无法证明总体疗效差异时。这种图形方法依赖于治疗组特定接收者操作特征曲线 (ABC) 之间的面积，它反映了标记的治疗选择能力。一项模拟研究评估了 ABC 估计器的推理特性，并将它们与其他参数和非参数指标进行了比较。模拟表明，ABC 的估计偏差小，功效与参数指标相当，并且其置信区间具有良好的覆盖概率（在某些情况下优于其他非参数指标）。因此，ABC 是参数指标的一个很好的替代品。ABC 方法被应用于 PETACC-8 试验的数据，该试验调查了 III 期结肠腺癌中的 FOLFOX4 与 FOLFOX4 + 西妥昔单抗。它能够检测治疗选择标记：DDR2 基因。