论文标题
非参数相对治疗效果，用于直接比较审查的配对生存结果
A nonparametric relative treatment effect for direct comparisons of censored paired survival outcomes
论文作者
论文摘要
统计中一个非常经典的问题是测试一个分布对另一个分布的随机优势。但是，为独立样本开发了许多现有方法，此外，不考虑审查数据。我们开发了一种新的估算和驱动方法，以比较右核心生存数据与匹配对的两种治疗方法的有效性。借助竞争风险技术，估计所谓的相对治疗效果。它量化了接受第一种治疗的个人生存的可能性，接受了第二次治疗。假设检验和置信区间基于估算器的学生化版本，在该版本中，通过随机化方法建立了基于重新采样的推理。在一项仿真研究中，我们发现，与实际测试两个边际生存函数平等的较简单的零假设相比，开发的测试具有良好的功率。最后，我们将方法应用于试验的众所周知的基准数据集，患有糖尿病性视网膜病的患者。
A very classical problem in statistics is to test the stochastic superiority of one distribution to another. However, many existing approaches are developed for independent samples and, moreover, do not take censored data into account. We develop a new estimand-driven method to compare the effectiveness of two treatments in the context of right-censored survival data with matched pairs. With the help of competing risks techniques, the so-called relative treatment effect is estimated. It quantifies the probability that the individual undergoing the first treatment survives the matched individual undergoing the second treatment. Hypothesis tests and confidence intervals are based on a studentized version of the estimator, where resampling-based inference is established by means of a randomization method. In a simulation study, we found that the developed test exhibits good power, when compared to competitors which are actually testing the simpler null hypothesis of the equality of both marginal survival functions. Finally, we apply the methodology to a well-known benchmark data set from a trial with patients suffering from with diabetic retinopathy.
