Manley Brett J, McKinlay Christopher J D, Lee Katherine J, Groom Katie M, Whitehead Clare L
Newborn Research, Melbourne, VIC, Australia; Department of Obstetrics, Gynaecology and Newborn Health, The University of Melbourne, Melbourne, VIC, Australia; Murdoch Children's Research Institute, Melbourne, VIC, Australia.
Department of Paediatrics: Child and Youth Health, University of Auckland, Auckland, Aotearoa New Zealand.
Lancet Child Adolesc Health. 2025 Feb;9(2):131-137. doi: 10.1016/S2352-4642(24)00328-6.
In this Viewpoint, we discuss the challenges facing perinatal clinical researchers, many of which are unique to this field, and how traditional two-arm randomised trials using frequentist analysis might no longer be fit for purpose for perinatology. We propose a solution: the adoption of adaptive platform trials (APTs) with Bayesian methodology to address perinatal research questions to improve outcomes of preterm birth. APTs use a master protocol as a foundation to efficiently assess multiple interventions simultaneously for a particular disease. APTs can study these interventions in a perpetual manner, with interventions allowed to enter or leave the platform on the basis of preplanned decision algorithms. In this Viewpoint, we outline the ways in which APTs can overcome some of the issues facing perinatal clinical research, and the challenges and essential requirements for the design and implementation of perinatal APTs that should be considered.
在本观点文章中,我们讨论围产期临床研究人员面临的挑战,其中许多挑战是该领域所特有的,以及使用频率论分析的传统双臂随机试验可能如何不再适用于围产医学。我们提出一种解决方案:采用贝叶斯方法的适应性平台试验(APT)来解决围产期研究问题,以改善早产结局。APT以主方案为基础,同时高效评估针对特定疾病的多种干预措施。APT可以持续研究这些干预措施,允许干预措施根据预先规划的决策算法进入或退出该平台。在本观点文章中,我们概述了APT能够克服围产期临床研究面临的一些问题的方式,以及围产期APT设计和实施应考虑的挑战与基本要求。