Bayesian Model Averaging Continual Reassessment Method in Phase I Clinical Trials
Bayesian Model Averaging Continual Reassessment Method in Phase I Clinical Trials
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DOI：
10.1198/jasa.2009.ap08425
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发表时间：
2009-09-01
影响因子：
3.7
通讯作者：
Yuan, Ying
中科院分区：
文献类型：
--
作者：
Yin, Guosheng;Yuan, Ying
连续再评估方法（CRM）是I期临床试验中常用的剂量探索设计。该方法要求从业者预先指定每个剂量的毒性概率。这种预先规定可以是任意的，不同的毒性概率规定可能导致非常不同的设计特性。为了克服任意性并进一步增强设计的鲁棒性，我们建议使用多个并行CRM模型，每个模型具有不同的预先指定的毒性概率。在贝叶斯范式中。我们为每个CRM模型分配一个离散的概率质量作为先验模型概率。毒性的后验概率可以通过贝叶斯模型平均（BMA）方法估计。通过比较目标毒性率和BMA估计的毒性概率来确定剂量递增或递减。我们通过广泛的模拟研究检查的BMA-CRM方法的属性，并将这种新方法及其变体与原始CRM进行比较。结果表明，我们的BMA-CRM是有竞争力的和强大的，并消除了预先指定的毒性概率的任意性，
The continual reassessment method (CRM) is a popular dose-finding design for phase I clinical trials. This method requires that practitioners prespecify the toxicity probability at each dose. Such prespecification can be arbitrary, and different specifications of toxicity probabilities may lead to very different design properties. To overcome the arbitrariness and further enhance the robustness of the design, we propose using multiple parallel CRM models, each with a different set of prespecified toxicity probabilities. In the Bayesian paradigm. we assign a discrete probability mass to each CRM model as the prior model probability. The posterior probabilities of toxicity can be estimated by the Bayesian model averaging (BMA) approach. Dose escalation or deescalation is determined by comparing the target toxicity rate and the BMA estimates of the (lose toxicity probabilities. We examine the properties of the BMA-CRM approach through extensive simulation studies, and also compare this new method and its variants with the original CRM. The results demonstrate that our BMA-CRM is competitive and robust, and eliminates the arbitrariness of the prespecification of toxicity probabilities,