Travis James, Rothmann Mark, Thomson Andrew
Office of Biostatistics, Office of Translational Science, Center for the Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA.
Data Analytics and Methods Taskforce, European Medicines Agency, Amsterdam, NL.
J Biopharm Stat. 2023 Nov 2;33(6):830-843. doi: 10.1080/10543406.2023.2170405. Epub 2023 Jan 29.
Bayesian methods have been proposed as a natural fit for pediatric extrapolation, as they allow the incorporation of relevant external data to reduce the required sample size and hence trial burden for the pediatric patient population. In this paper we will discuss our experience and perspectives with these methods in pediatric trials. We will present some of the background and thinking underlying pediatric extrapolation and discuss the use of Bayesian methods within this context. We will present two recent case examples illustrating the value of a Bayesian approach in this setting and present perspectives on some of the issues that we have encountered in these and other cases.
贝叶斯方法已被提议作为儿科外推法的自然选择,因为它们允许纳入相关外部数据,以减少所需样本量,从而减轻儿科患者群体的试验负担。在本文中,我们将讨论我们在儿科试验中使用这些方法的经验和观点。我们将介绍儿科外推法的一些背景和基本思路,并讨论在此背景下贝叶斯方法的应用。我们将给出两个近期的案例,说明贝叶斯方法在这种情况下的价值,并就我们在这些案例及其他案例中遇到的一些问题发表观点。