Data Science & Analytics, Bayer U.S. LLC, Pharmaceuticals, 100 Bayer Boulevard, Whippany, NJ, 07981, USA.
Center of Excellence, Methodology and Data Visualization, Biostatistics Department, Servier pharmaceuticals, 200 Pier Four Blvd, Boston, MA, 02210, USA.
Orphanet J Rare Dis. 2020 Mar 12;15(1):69. doi: 10.1186/s13023-020-1332-x.
Historical controls (HCs) can be used for model parameter estimation at the study design phase, adaptation within a study, or supplementation or replacement of a control arm. Currently on the latter, there is no practical roadmap from design to analysis of a clinical trial to address selection and inclusion of HCs, while maintaining scientific validity. This paper provides a comprehensive roadmap for planning, conducting, analyzing and reporting of studies using HCs, mainly when a randomized clinical trial is not possible. We review recent applications of HC in clinical trials, in which either predominantly a large treatment effect overcame concerns about bias, or the trial targeted a life-threatening disease with no treatment options. In contrast, we address how the evidentiary standard of a trial can be strengthened with optimized study designs and analysis strategies, emphasizing rare and pediatric indications. We highlight the importance of simulation and sensitivity analyses for estimating the range of uncertainties in the estimation of treatment effect when traditional randomization is not possible. Overall, the paper provides a roadmap for using HCs.
历史对照(HC)可用于研究设计阶段的模型参数估计、研究中的调整或对照臂的补充或替代。目前在后者方面,从设计到分析临床试验以解决 HC 的选择和纳入问题,同时保持科学有效性,还没有实用的路线图。本文提供了使用 HC 进行规划、进行、分析和报告研究的综合路线图,主要是在不可能进行随机临床试验的情况下。我们回顾了 HC 在临床试验中的最新应用,其中主要是由于治疗效果较大,克服了对偏倚的担忧,或者试验针对的是没有治疗选择的危及生命的疾病。相比之下,我们讨论了如何通过优化的研究设计和分析策略来加强试验的证据标准,强调罕见和儿科适应症。我们强调了在无法进行传统随机化时,模拟和敏感性分析对于估计治疗效果估计不确定性范围的重要性。总的来说,本文提供了使用 HC 的路线图。