Ohigashi Tomohiro, Maruo Kazushi, Sozu Takashi, Sawamoto Ryo, Gosho Masahiko
Department of Biostatistics, Tsukuba Clinical Research & Development Organization, University of Tsukuba, Tsukuba, Ibaraki, Japan.
Department of Biostatistics, Institute of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan.
Pharm Stat. 2025 Mar-Apr;24(2):e2453. doi: 10.1002/pst.2453. Epub 2024 Nov 17.
When multiple historical controls are available, it is necessary to consider the conflicts between current and historical controls and the relationships among historical controls. One of the assumptions concerning the relationships between the parameters of interest of current and historical controls is known as the "Potential biases." Within the "Potential biases" assumption, the differences between the parameters of interest of the current control and of each historical control are defined as "potential bias parameters." We define a class of models called "potential biases model" that encompass several existing methods, including the commensurate prior. The potential bias model incorporates homogeneous historical controls by shrinking the potential bias parameters to zero. In scenarios where multiple historical controls are available, a method that uses a horseshoe prior was proposed. However, various other shrinkage priors are also available. In this study, we propose methods that apply spike-and-slab, Dirichlet-Laplace, and spike-and-slab lasso priors to the potential bias model. We conduct a simulation study and analyze clinical trial examples to compare the performances of the proposed and existing methods. The horseshoe prior and the three other priors make the strongest use of historical controls in the absence of heterogeneous historical controls and reduce the influence of heterogeneous historical controls in the presence of a few historical controls. Among these four priors, the spike-and-slab prior performed the best for heterogeneous historical controls.
当有多个历史对照可用时，有必要考虑当前对照与历史对照之间的冲突以及历史对照之间的关系。关于当前对照和历史对照的感兴趣参数之间关系的一个假设被称为“潜在偏差”。在“潜在偏差”假设下，当前对照与每个历史对照的感兴趣参数之间的差异被定义为“潜在偏差参数”。我们定义了一类称为“潜在偏差模型”的模型，它涵盖了几种现有方法，包括相称先验。潜在偏差模型通过将潜在偏差参数收缩至零来纳入同质历史对照。在有多个历史对照可用的情况下，提出了一种使用马蹄形先验的方法。然而，也有各种其他收缩先验可用。在本研究中，我们提出了将尖峰和平板、狄利克雷 - 拉普拉斯以及尖峰和平板套索先验应用于潜在偏差模型的方法。我们进行了模拟研究并分析了临床试验实例，以比较所提出方法与现有方法的性能。在不存在异质历史对照的情况下，马蹄形先验和其他三种先验最充分地利用了历史对照，而在存在少数历史对照的情况下，减少了异质历史对照的影响。在这四种先验中，尖峰和平板先验在处理异质历史对照时表现最佳。
