CSTE curve for selection of the optimal treatment when outcome is binary
CSTE curve for selection of the optimal treatment when outcome is binary
复制标题
当结果是二元时用于选择最佳治疗的 CSTE 曲线
DOI：
10.1360/scm-2015-0595
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Liu BaoFang
中科院分区：
文献类型：
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作者：
Han KaiShan;Zhou Xiaohua;Liu BaoFang
在这篇文章中，我们提出了一个统计框架，用于对一组患者进行最佳治疗选择，使用他们的生物标记物值，基于对二元结果数据的随机推断。这种新方法基于一个概念，称为协变量特异性治疗效应(CSTE)曲线和CSTE曲线同时可信区间(SCB)，它可以用来表示给定协变量(生物标记物)值的治疗的平均疗效，并为特定患者选择最佳治疗方案。然后我们提出了估计CSTE曲线和构造CSTE曲线的同时置信带的B-Splines方法。我们得到了所提出方法的渐近性质。我们还进行了大量的模拟研究，以评估所提出的同时置信带的有限样本性质。最后，我们说明了CSTE曲线及其同时置信带在真实数据集的最优处理选择中的应用。
In this paper, we propose a statistical framework for optimal treatment selection for a subgroup of patients, using their biomarker values based on casual inference for binary outcome data. This new method was based on a concept, called covariate-specific treatment effect (CSTE) curve and CSTE curves simultaneous confidence bands (SCBs), which could be used to represent the average treatment effect of the treatment for a given value of the covariate (biomarker) and to select an optimal treatment for one particular patient. We then propose B-splines methods for estimating the CSTE curves and constructing simultaneous confidence bands for the CSTE curves. We derive the asymptotic properties of the proposed methods. We also conduct extensive simulation studies to evaluate finite-sample properties of the proposed simultaneous confidence bands. Finally, we illustrate the application of the CSTE curve and its simultaneous confidence bands in optimal treatment selection in a real-world data set.