MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK.
Pragmatic Clinical Trials Unit, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London, E1 2AB, UK.
Trials. 2021 Mar 10;22(1):203. doi: 10.1186/s13063-021-05150-7.
Platform trials improve the efficiency of the drug development process through flexible features such as adding and dropping arms as evidence emerges. The benefits and practical challenges of implementing novel trial designs have been discussed widely in the literature, yet less consideration has been given to the statistical implications of adding arms. MAIN: We explain different statistical considerations that arise from allowing new research interventions to be added in for ongoing studies. We present recent methodology development on addressing these issues and illustrate design and analysis approaches that might be enhanced to provide robust inference from platform trials. We also discuss the implication of changing the control arm, how patient eligibility for different arms may complicate the trial design and analysis, and how operational bias may arise when revealing some results of the trials. Lastly, we comment on the appropriateness and the application of platform trials in phase II and phase III settings, as well as publicly versus industry-funded trials.
Platform trials provide great opportunities for improving the efficiency of evaluating interventions. Although several statistical issues are present, there are a range of methods available that allow robust and efficient design and analysis of these trials.
平台试验通过灵活的功能(如根据证据增加或删除试验组)提高药物开发过程的效率。在文献中已经广泛讨论了实施新型试验设计的益处和实际挑战,但对于增加试验组的统计学意义考虑较少。
我们解释了允许新的研究干预措施加入正在进行的研究中所产生的不同统计考虑因素。我们介绍了最近在解决这些问题方面的方法学进展,并说明了可能会增强设计和分析方法的方法,以便从平台试验中提供稳健的推断。我们还讨论了改变对照组的影响,不同试验组的患者入选标准可能使试验设计和分析复杂化,以及当揭示试验的某些结果时可能出现操作偏差。最后,我们评论了平台试验在 II 期和 III 期研究中的适用性和应用,以及公开资助和行业资助试验的适用性。
平台试验为提高干预措施评估的效率提供了很好的机会。尽管存在一些统计学问题,但有一系列方法可用于稳健且高效地设计和分析这些试验。