论文标题
估计异质治疗效果与建立个性化治疗规则：连接和断开连接
Estimating heterogeneous treatment effects versus building individualized treatment rules: Connection and disconnection
论文作者
论文摘要
估计异质治疗效果是统计文献中良好的主题。最近，由于对精确药物的需求越来越多，并且在估计中增加了最先进的机器学习方法的使用，因此引起了人们的注意。此外，估计异质治疗效果与制定个性化治疗规则直接相关，这是根据患者特征的治疗规则。本文研究了这两个研究问题之间的联系和断开连接。值得注意的是，对异质治疗效果的更好估计可能会或可能不会导致更好的个性化治疗规则。我们提供理论框架来解释连接和断开连接，并通过模拟演示两种不同的情况。我们的结论阐明了一个实用指南，即在某些情况下，无需加强对治疗效果的估计，因为它不会改变治疗决定。
Estimating heterogeneous treatment effects is a well-studied topic in the statistics literature. More recently, it has regained attention due to an increasing need for precision medicine as well as the increased use of state-of-art machine learning methods in the estimation. Furthermore, estimating heterogeneous treatment effects is directly related to building an individualized treatment rule, which is a decision rule of treatment according to patient characteristics. This paper examines the connection and disconnection between these two research problems. Notably, a better estimation of the heterogeneous treatment effects may or may not lead to a better individualized treatment rule. We provide theoretical frameworks to explain the connection and disconnection and demonstrate two different scenarios through simulations. Our conclusion sheds light on a practical guide that under certain circumstances, there is no need to enhance estimation of the treatment effects, as it does not alter the treatment decision.
