Department of Statistics, Ohio State University, Columbus, Ohio, USA.
FSP Biometrics, Syneos Health, Toronto, Ontario, Canada.
J Biopharm Stat. 2023 Sep 3;33(5):515-543. doi: 10.1080/10543406.2022.2162067. Epub 2023 Jan 23.
Methods to extend the strong internal validity of randomized controlled trials to reliably estimate treatment effects in target populations are gaining attention. This paper enumerates steps recommended for undertaking such extended inference, discusses currently viable choices for each one, and provides recommendations. We demonstrate a complete extended inference from a clinical trial studying a pharmaceutical treatment for Alzheimer's disease (AD) to a realistic target population of European residents diagnosed with AD. This case study highlights approaches to overcoming practical difficulties and demonstrates limitations of reliably extending inference from a trial to a real-world population.
将随机对照试验的强内部有效性扩展到可靠估计目标人群的治疗效果的方法正受到关注。本文列举了开展此类扩展推断所建议的步骤，讨论了每一步目前可行的选择，并提供了建议。我们从一项研究阿尔茨海默病（AD）药物治疗的临床试验中进行了完整的扩展推断，将其推广到了真实的欧洲 AD 患者目标人群。这个案例研究强调了克服实际困难的方法，并说明了从试验可靠地推广到真实人群的推断的局限性。
