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A placebo-controlled Bayesian dose finding design based on continuous reassessment method with application to stroke research

机译:基于连续重新评估方法的安慰剂对照贝叶斯剂量发现设计及其在中风研究中的应用

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摘要

Traditional dose-finding designs do not require assignment of patients to a control group. Motivated by SHRINC (Safety of Pioglitazone for hematoma resolution in intracerebral hemorrhage), we developed a placebo-controlled dose-finding study to identify the maximum tolerated dose for pioglitazone in stroke patients with spontaneous intracerebral hemorrhage. We designed an extension of the continuous reassessment method that allowed to incorporate information from the control group (i.e., the standard of care), and utilized it to determine the maximum tolerated dose in the SHRINC trial. We evaluated the operating characteristics of our design by conducting extensive simulation studies. Our findings from the simulation studies demonstrate that our proposed design is robust and performs well. By estimating the toxicity rate in the control group, we were able to obtain more accurate information about the natural history of the disease and identify appropriate dose for the next phase of this study. The proposed design provides a tool to incorporate the information from the control group into the dose-finding framework for trials with similar objectives.
机译:传统的剂量查找设计不需要将患者分配到对照组。受SHRINC(吡格列酮对脑出血的血肿消解的安全性)的启发,我们开展了一项安慰剂对照剂量寻找研究,以确定在自发性脑出血的卒中患者中吡格列酮的最大耐受剂量。我们设计了一种扩展的连续重新评估方法,该方法允许纳入对照组的信息(即护理标准),并利用它来确定SHRINC试验中的最大耐受剂量。我们通过进行广泛的仿真研究来评估设计的操作特性。从仿真研究中得出的结果表明,我们提出的设计是可靠且性能良好的。通过估计对照组的毒性率,我们能够获得有关疾病自然史的更准确信息,并为下一步研究确定合适的剂量。拟议的设计提供了一种工具,可将来自对照组的信息纳入剂量寻找框架,以进行具有相似目标的试验。

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