论文标题
关于竞争风险方法的审查生存分析的方法
A review on competing risks methods for survival analysis
论文作者
论文摘要
在建模竞争风险生存数据时，在统计和机器学习文献中都提出了几种技术。最先进的方法具有扩展的经典方法，具有更灵活的假设，可以提高预测性能，允许高维数据和缺失值等。尽管如此，现代方法并未在应用环境中广泛使用。本文旨在通过提供跨方法的统一符号和解释来提供浓缩风险的生存方法来帮助吸收此类方法。我们重点介绍可用的软件，并在可能的情况下通过可重复的r小插图演示其使用情况。此外，我们讨论了在这种情况下可能影响基准研究的两个主要问题：绩效指标和可重复性的选择。
When modelling competing risks survival data, several techniques have been proposed in both the statistical and machine learning literature. State-of-the-art methods have extended classical approaches with more flexible assumptions that can improve predictive performance, allow high dimensional data and missing values, among others. Despite this, modern approaches have not been widely employed in applied settings. This article aims to aid the uptake of such methods by providing a condensed compendium of competing risks survival methods with a unified notation and interpretation across approaches. We highlight available software and, when possible, demonstrate their usage via reproducible R vignettes. Moreover, we discuss two major concerns that can affect benchmark studies in this context: the choice of performance metrics and reproducibility.
