Core for Biomedical Statistics, Seattle Children's Research Institute, Seattle, WA 98121, USA.
Clin Trials. 2013 Feb;10(1):63-80. doi: 10.1177/1740774512469311.
Novel dose-finding designs for Phase I cancer clinical trials, using estimation to assign the best estimated Maximum Tolerated Dose (MTD) at each point in the experiment, most prominently via Bayesian techniques, have been widely discussed and promoted since 1990.
To examine the small-sample behavior of these 'Bayesian Phase I' designs, and also of non-Bayesian designs sharing the same main 'Long-Memory' traits of using likelihood estimation and assigning the estimated MTD to the next patient.
Data from several recently published experiments are presented and discussed, and Long-Memory designs' operating principles are explained. Simulation studies compare the small-sample behavior of Long-Memory designs with short-memory 'Up-and-Down' designs.
In simulation, Long-Memory and Up-and-Down designs achieved similar success rates in finding the MTD. However, for all Long-Memory designs examined, the number n (*) of cohorts treated at the true MTD was highly variable between simulated experiments drawn from the same toxicity-threshold distribution. Further investigation using the same set of thresholds in permuted order indicates that this Long-Memory behavior is driven by sensitivity to the order in which participants enter the experiment. This sensitivity is related to Long-Memory designs' 'winner-takes-all' dose-assignment rule, which grants the early cohorts a disproportionately large influence, and causes many experiments to settle early on a specific dose. Additionally for the Bayesian Long-Memory designs, the prior-predictive distribution over the dose levels has a substantial impact upon MTD-finding performance, long into the experiment.
While the numerical evidence for Long-Memory designs' order sensitivity is broad, and plausible explanations for it are provided, we do not present a theoretical proof of the phenomenon.
Method developers, analysts, and practitioners should be aware of Long-Memory designs' order sensitivity and related phenomena. In particular, they should be informed that settling on a single dose does not guarantee that this dose is the MTD. Presently, Up-and-Down designs offer a simpler and more robust alternative for the sample sizes of 10-40 patients used in most Phase I trials. Future designs might benefit from combining the two approaches. We also suggest that the field's paradigm change from dose-selection to dose-estimation.
自 1990 年以来，新型的 I 期癌症临床试验剂量发现设计（使用估计值在实验的每个点分配最佳估计最大耐受剂量（MTD）），尤其是通过贝叶斯技术，已被广泛讨论和推广。
检查这些“贝叶斯 I 期”设计的小样本行为，以及具有相同主要“长记忆”特征的非贝叶斯设计，这些设计使用似然估计并将估计的 MTD 分配给下一个患者。
呈现并讨论了最近发表的几项实验的数据，并解释了长记忆设计的工作原理。模拟研究比较了长记忆设计与短记忆“上下”设计的小样本行为。
在模拟中，长记忆和上下设计在找到 MTD 方面具有相似的成功率。然而，对于所有检查的长记忆设计，在从相同毒性阈值分布中抽取的模拟实验中，在真实 MTD 处治疗的队列数（*）变化很大。使用相同的阈值进行置换顺序的进一步研究表明，这种长记忆行为是由对参与者进入实验的顺序的敏感性驱动的。这种敏感性与长记忆设计的“胜者通吃”剂量分配规则有关，该规则赋予早期队列不成比例的大影响，并导致许多实验在特定剂量上过早确定。此外，对于贝叶斯长记忆设计，在实验的后期，剂量水平的先验预测分布对 MTD 发现性能有很大的影响。
虽然长记忆设计顺序敏感性的数值证据广泛，但为其提供了合理的解释，我们没有对此现象进行理论证明。
方法开发者、分析人员和从业者应该意识到长记忆设计的顺序敏感性和相关现象。特别是，他们应该了解，确定一个剂量并不保证该剂量就是 MTD。目前，在大多数 I 期试验中使用的 10-40 名患者的样本量下，上下设计提供了一种更简单、更稳健的替代方案。未来的设计可能受益于两种方法的结合。我们还建议该领域从剂量选择转变为剂量估计。
