Department of Biostatistics & Data Science, University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd., Kansas City, KS, 66160, USA.
BMC Med Res Methodol. 2020 Jul 20;20(1):194. doi: 10.1186/s12874-020-01071-2.
Phase II clinical trials primarily aim to find the optimal dose and investigate the relationship between dose and efficacy relative to standard of care (control). Therefore, before moving forward to a phase III confirmatory trial, the most effective dose is needed to be identified.
The primary endpoint of a phase II trial is typically a binary endpoint of success or failure. The EMAX model, ubiquitous in pharmacology research, was fit for many compounds and described the data well, except for a single compound, which had nonmonotone dose-response (Thomas et al., Stat Biopharmaceutical Res. 6:302-317 2014). To mitigate the risk of nonmonotone dose response one of the alternative options is a Bayesian hierarchical EMAX model (Gajewski et al., Stat Med. 38:3123-3138 2019). The hierarchical EMAX adapts to its environment.
When the dose-response curve is monotonic it enjoys the efficiency of EMAX. When the dose-response curve is non-monotonic the additional random effect hyperprior makes the hierarchical EMAX model more adjustable and flexible. However, the normal dynamic linear model (NDLM) is a useful model to explore dose-response relationships in that the efficacy at the current dose depends on the efficacy of the previous dose(s). Previous research has compared the EMAX to the hierarchical EMAX (Gajewski et al., Stat Med. 38:3123-3138 2019) and the EMAX to the NDLM (Liu et al., BMC Med Res Method 17:149 2017), however, the hierarchical EMAX has not been directly compared to the NDLM.
The focus of this paper is to compare these models and discuss the relative merit for each of their uses for an ongoing early phase dose selection study.
二期临床试验主要旨在寻找最佳剂量，并研究剂量与对照（标准治疗）疗效之间的关系。因此，在推进三期确证性试验之前，需要确定最有效的剂量。
二期试验的主要终点通常是成功或失败的二项终点。EMAX 模型在药理学研究中广泛应用，适用于许多化合物，并且能够很好地描述数据，但对于一种具有非单调剂量反应的化合物除外（Thomas 等人，Stat Biopharmaceutical Res. 6:302-317 2014）。为了降低非单调剂量反应的风险，一种替代方案是贝叶斯分层 EMAX 模型（Gajewski 等人，Stat Med. 38:3123-3138 2019）。分层 EMAX 适应其环境。
当剂量-反应曲线是单调时，它具有 EMAX 的效率。当剂量-反应曲线是非单调时，额外的随机效应超先验使分层 EMAX 模型更具可调节性和灵活性。然而，正常动态线性模型（NDLM）是一种有用的模型，可以探索剂量-反应关系，因为当前剂量的疗效取决于先前剂量的疗效。先前的研究比较了 EMAX 与分层 EMAX（Gajewski 等人，Stat Med. 38:3123-3138 2019）和 EMAX 与 NDLM（Liu 等人，BMC Med Res Method 17:149 2017），但是，分层 EMAX 尚未与 NDLM 直接比较。
本文的重点是比较这些模型，并讨论它们在正在进行的早期阶段剂量选择研究中的各自用途的相对优势。
