Developing a Bayesian adaptive design for a phase I clinical trial: a case study for a novel HIV treatment.
Developing a Bayesian adaptive design for a phase I clinical trial: a case study for a novel HIV treatment.
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DOI：
10.1002/sim.7169
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发表时间：
2017-02-28
影响因子：
2
通讯作者：
Ashby D
中科院分区：
文献类型：
--
作者：
Mason AJ;Gonzalez-Maffe J;Quinn K;Doyle N;Legg K;Norsworthy P;Trevelion R;Winston A;Ashby D
第一阶段研究的设计往往是具有挑战性的，因为提供研究方案的证据有限。适应性设计现在已经在癌症领域得到了很好的证实，但在其他临床领域却少得多。在医学研究委员会的资助下，已经建立了一项评估C34-PEG4-CHOL的安全性、药代动力学和抗逆转录病毒疗效的第一阶段研究。C34-PEG4-CHOL是一种用于治疗艾滋病毒感染的新型多肽融合抑制剂。在研究工作期间，将基于持续重新评估方法的贝叶斯自适应设计与更标准的基于规则的设计进行比较，目的是选择一种将从研究中获得的科学信息最大化的设计。指定和评估设计备选方案的过程非常耗时，需要试验方案开发小组所有成员的积极参与。然而，这一努力是值得的，因为最初提出的基于规则的设计已被更有效的贝叶斯自适应设计所取代。虽然要模拟的结果、设计细节和评估标准是特定于试验的，但选择它们背后的原则是一般性的。本案例研究说明了在新的环境中建立设计所需的步骤。©2016作者。John Wiley&Sons Ltd出版的医学统计数据
The design of phase I studies is often challenging, because of limited evidence to inform study protocols. Adaptive designs are now well established in cancer but much less so in other clinical areas. A phase I study to assess the safety, pharmacokinetic profile and antiretroviral efficacy of C34‐PEG4‐Chol, a novel peptide fusion inhibitor for the treatment of HIV infection, has been set up with Medical Research Council funding. During the study workup, Bayesian adaptive designs based on the continual reassessment method were compared with a more standard rule‐based design, with the aim of choosing a design that would maximise the scientific information gained from the study. The process of specifying and evaluating the design options was time consuming and required the active involvement of all members of the trial's protocol development team. However, the effort was worthwhile as the originally proposed rule‐based design has been replaced by a more efficient Bayesian adaptive design. While the outcome to be modelled, design details and evaluation criteria are trial specific, the principles behind their selection are general. This case study illustrates the steps required to establish a design in a novel context. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd