健康志愿者单剂量递增试验中的贝叶斯适应性设计。
Bayesian adaptive designs in single ascending dose trials in healthy volunteers.
作者信息
Guédé David, Reigner Bruno, Vandenhende Francois, Derks Mike, Beyer Ulrich, Jordan Paul, Worth Eric, Diack Cheikh, Frey Nicolas, Peck Richard
机构信息
ClinBAY SPRL, Genappe, Belgium.
出版信息
Br J Clin Pharmacol. 2014 Aug;78(2):393-400. doi: 10.1111/bcp.12344.
AIM
Recent publications indicate a strong interest in applying Bayesian adaptive designs in first time in humans (FTIH) studies outside of oncology. The objective of the present work was to assess the performance of a new approach that includes Bayesian adaptive design in single ascending dose (SAD) trials conducted in healthy volunteers, in comparison with a more traditional approach.
METHODS
A trial simulation approach was used and seven different scenarios of dose-response were tested.
RESULTS
The new approach provided less biased estimates of maximum tolerated dose (MTD). In all scenarios, the number of subjects needed to define a MTD was lower with the new approach than with the traditional approach. With respect to duration of the trials, the two approaches were comparable. In all scenarios, the number of subjects exposed to a dose greater than the actual MTD was lower with the new approach than with the traditional approach.
CONCLUSIONS
The new approach with Bayesian adaptive design shows a very good performance in the estimation of MTD and in reducing the total number of healthy subjects. It also reduces the number of subjects exposed to doses greater than the actual MTD.
目的
近期的出版物表明，人们对在肿瘤学以外的首次人体试验（FTIH）中应用贝叶斯自适应设计有着浓厚兴趣。本研究的目的是评估一种新方法的性能，该方法在健康志愿者进行的单剂量递增（SAD）试验中纳入了贝叶斯自适应设计，并与一种更传统的方法进行比较。
方法
采用试验模拟方法，测试了七种不同的剂量反应情况。
结果
新方法对最大耐受剂量（MTD）的估计偏差较小。在所有情况下，新方法确定MTD所需的受试者数量均低于传统方法。关于试验持续时间，两种方法相当。在所有情况下，新方法中暴露于高于实际MTD剂量的受试者数量均低于传统方法。
结论
采用贝叶斯自适应设计的新方法在MTD估计以及减少健康受试者总数方面表现出非常好的性能。它还减少了暴露于高于实际MTD剂量的受试者数量。
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