医学
临床试验
杠杆(统计)
数据共享
数据质量
精确肿瘤学
肿瘤科
医学物理学
临床研究设计
梅德林
内科学
重症监护医学
替代医学
计算机科学
人工智能
运营管理
病理
经济
公制(单位)
法学
政治学
作者
Rifaquat Rahman,Steffen Ventz,Jon McDunn,Bill Louv,Irmarie Reyes-Rivera,Mei Yin C. Polley,Fahar J. A. Merchant,Lauren E. Abrey,Joshua E. Allen,Laura K. Aguilar,Estuardo Aguilar-Cordova,David Arons,Kirk G. Tanner,Stephen J Bagley,Mustafa Khasraw,Timothy F. Cloughesy,Patrick Y. Wen,Brian M. Alexander,Lorenzo Trippa
出处
期刊:Lancet Oncology
[Elsevier]
日期:2021-10-01
卷期号:22 (10): e456-e465
被引量:16
标识
DOI:10.1016/s1470-2045(21)00488-5
摘要
Integration of external control data, with patient-level information, in clinical trials has the potential to accelerate the development of new treatments in neuro-oncology by contextualising single-arm studies and improving decision making (eg, early stopping decisions). Based on a series of presentations at the 2020 Clinical Trials Think Tank hosted by the Society of Neuro-Oncology, we provide an overview on the use of external control data representative of the standard of care in the design and analysis of clinical trials. High-quality patient-level records, rigorous methods, and validation analyses are necessary to effectively leverage external data. We review study designs, statistical methods, risks, and potential distortions in using external data from completed trials and real-world data, as well as data sources, data sharing models, ongoing work, and applications in glioblastoma.
科研通智能强力驱动
Strongly Powered by AbleSci AI