Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA.
Stat Med. 2013 Jun 15;32(13):2221-34. doi: 10.1002/sim.5621. Epub 2012 Sep 17.
The use of the continual reassessment method (CRM) and other model-based approaches to design Phase I clinical trials has increased owing to the ability of the CRM to identify the maximum tolerated dose better than the 3 + 3 method. However, the CRM can be sensitive to the variance selected for the prior distribution of the model parameter, especially when a small number of patients are enrolled. Although methods have emerged to adaptively select skeletons and to calibrate the prior variance only at the beginning of a trial, there has not been any approach developed to adaptively calibrate the prior variance throughout a trial. We propose three systematic approaches to adaptively calibrate the prior variance during a trial and compare them via simulation with methods proposed to calibrate the variance at the beginning of a trial.
由于连续评估方法（CRM）和其他基于模型的方法能够比 3+3 方法更好地确定最大耐受剂量，因此其在设计 I 期临床试验中的应用有所增加。然而，CRM 对模型参数先验分布选择的方差较为敏感，尤其是在入组患者数量较少的情况下。尽管已经出现了一些自适应选择骨架和仅在试验开始时校准先验方差的方法，但还没有开发出在整个试验过程中自适应校准先验方差的方法。我们提出了三种系统的方法来在试验过程中自适应地校准先验方差，并通过模拟与在试验开始时校准方差的方法进行比较。
