Aggregating data from COVID-19 trials

doi:10.1126/science.abc8993

GSTDTAP > 气候变化

DOI	10.1126/science.abc8993
	Aggregating data from COVID-19 trials
	Elizabeth L. Ogburn; Barbara E. Bierer; Ron Brookmeyer; Christine Choirat; Natalie E. Dean; Victor De Gruttola; Susan S. Ellenberg; M. Elizabeth Halloran; Daniel F. Hanley; Joseph K. Lee; Rui Wang; Daniel O. Scharfstein
	2020-06-12
发表期刊	Science
出版年	2020
英文摘要	In their Policy Forum “A strategic approach to COVID-19 vaccine R&D” (29 May, p. [948][1] ), L. Corey et al. discuss the importance of coordinating randomized clinical trial (RCT) protocols to facilitate the evaluation of coronavirus disease 2019 (COVID-19) vaccines, and they highlight the ACTIV (Accelerating COVID-19 Therapeutic Interventions and Vaccines) public-private partnership as one example of productive collaboration. We agree that coordination across RCTs is crucial to ensure that evidence for the treatment and prevention of COVID-19 is adjudicated and disseminated as quickly and reliably as possible. In the absence of coordination, false positives from underpowered and uncoordinated collections of redundant trials could fuel the proliferation of ineffective and potentially dangerous treatments. ACTIV provides infrastructure to coordinate efforts by pharmaceutical companies developing vaccines and novel compounds; a similar platform is needed for voluntary collaboration by diverse partners on the full spectrum of research questions. To increase the power of RCTs, we have created a pilot repository for RCT protocols led by principal investigators who are open to various levels of collaboration. On the COVID-19 Collaboration Platform (CovidCP), researchers can submit their draft or completed protocols and find collaborators. Together, they can initiate new multi-site trials, work to create collaborative protocols that can be used at multiple sites but as independent studies, admit new research sites under the existing trial and Institutional Review Board, share anonymized interim and final data with sites that choose to conduct a trial under a similar but not identical protocol, and collaborate on data collection tools, data standards, and case report forms. Organizing multi-site RCTs and, where that is not possible, combining data from separate but similar trials with the use of appropriate subject-level or meta-analytical methods, will produce answers faster and more accurately than conducting each trial independently. Every patient participating in an RCT has the right to have their data used as efficiently and meaningfully as possible. Streamlining protocols can help researchers make full use of data even from trials that are stopped early as a result of a change in standard of care or local epidemic waning, from trials that are small and possibly underpowered, and from single-arm trials. We trust that the clinical research community will share their work and knowledge in the service of developing all possible tools for fighting this pandemic, and we invite additional input and partnerships to maximize the effectiveness of CovidCP. By working together to determine how a cooperative platform such as CovidCP can most benefit researchers, clinicians, policy-makers, and patients, we can address the COVID-19 pandemic and prepare for future global health emergencies. B.E.B., E.L.O., and D.O.S. are members of the CovidCP executive committee. R.B., C.C., N.E.D., V.D.G., S.S.E., M.E.H., D.F.H. Jr., J.K.L., and R.W. are members of the CovidCP advisory board. S.S.E. serves on the Research Oversight Committee for COVID-19 trials conducted at the Perelman School of Medicine, University of Pennsylvania, and serves on a data monitoring committee for two trials of COVID-19 treatments being conducted at Stanford University. [1]: http://www.sciencemag.org/content/368/6494/948
领域	气候变化 ; 资源环境
URL	查看原文
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/274448
专题	气候变化资源环境科学
推荐引用方式 GB/T 7714	Elizabeth L. Ogburn,Barbara E. Bierer,Ron Brookmeyer,et al. Aggregating data from COVID-19 trials[J]. Science,2020.
APA	Elizabeth L. Ogburn.,Barbara E. Bierer.,Ron Brookmeyer.,Christine Choirat.,Natalie E. Dean.,...&Daniel O. Scharfstein.(2020).Aggregating data from COVID-19 trials.Science.
MLA	Elizabeth L. Ogburn,et al."Aggregating data from COVID-19 trials".Science (2020).