Silva Patrick, Janjan Nora, Ramos Kenneth S, Udeani George, Zhong Lixian, Ory Marcia G, Smith Matthew Lee
Institute of Bioscience and Technology and Department of Translational Medical Sciences, College Station, TX, United States.
Center for Community Health and Aging, School of Public Health, Texas A&M University, College Station, TX, United States.
Front Med (Lausanne). 2023 Jul 6;10:1198088. doi: 10.3389/fmed.2023.1198088. eCollection 2023.
Randomized controlled trials are considered the 'gold standard' to reduce bias by randomizing patients to an experimental intervention, versus placebo or standard of care cohort. There are inherent challenges to enrolling a standard of care or cohorts: costs, site engagement logistics, socioeconomic variability, patient willingness, ethics of placebo interventions, cannibalizing the treatment arm population, and extending study duration. The COVID-19 pandemic has magnified aspects of constraints in trial recruitment and logistics, spurring innovative approaches to reducing trial sizes, accelerating trial accrual while preserving statistical rigor. Using data from medical records and databases allows for construction of external control arms that reduce the costs of an external control arm (ECA) randomized to standard of care. Simultaneously examining covariates of the clinical outcomes in ECAs that are being measured in the interventional arm can be particularly useful in phase 2 trials to better understand social and genetic determinants of clinical outcomes that might inform pivotal trial design. The FDA and EMA have promulgated a number of publicly available guidance documents and qualification reports that inform the use of this regulatory science tool to streamline clinical development, of phase 4 surveillance, and policy aspects of clinical outcomes research. Availability and quality of real-world data (RWD) are a prevalent impediment to the use of ECAs given such data is not collected with the rigor and deliberateness that characterizes prospective interventional control arm data. Conversely, in the case of contemporary control arms, a clinical trial outcome can be compared to a contemporary standard of care in cases where the standard of care is evolving at a fast pace, such as the use of checkpoint inhibitors in cancer care. Innovative statistical methods are an essential aspect of an ECA strategy and regulatory paths for these innovative approaches have been navigated, qualified, and in some cases published.
随机对照试验被认为是通过将患者随机分配到实验性干预组、安慰剂组或护理标准队列来减少偏差的“金标准”。纳入护理标准或队列存在一些内在挑战：成本、站点参与后勤、社会经济变异性、患者意愿、安慰剂干预的伦理问题、蚕食治疗组人群以及延长研究持续时间。COVID-19大流行加剧了试验招募和后勤方面的限制，促使人们采取创新方法来减少试验规模，在保持统计严谨性的同时加速试验入组。利用医疗记录和数据库中的数据可以构建外部对照臂，从而降低随机分配到护理标准的外部对照臂（ECA）的成本。在2期试验中，同时检查干预组正在测量的ECA临床结果的协变量，对于更好地理解可能为关键试验设计提供信息的临床结果的社会和遗传决定因素特别有用。美国食品药品监督管理局（FDA）和欧洲药品管理局（EMA）已经发布了一些公开可用的指导文件和资格报告，这些文件为使用这种监管科学工具简化临床开发、4期监测以及临床结果研究的政策方面提供了指导。鉴于真实世界数据（RWD）不是以前瞻性干预对照臂数据所具有的严谨性和审慎性收集的，其可用性和质量是使用ECA的一个普遍障碍。相反，在当代对照臂的情况下，在护理标准快速演变的情况下，例如在癌症治疗中使用检查点抑制剂时，可以将临床试验结果与当代护理标准进行比较。创新统计方法是ECA策略的一个重要方面，并且已经为这些创新方法开辟、确认并在某些情况下发布了监管路径。
