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最大化随机临床试验的科学知识。

Maximizing scientific knowledge from randomized clinical trials.

机构信息

Rigshospitalet, Department of Cardiology, University of Copenhagen, Copenhagen, Denmark.

出版信息

Am Heart J. 2010 Jun;159(6):937-43. doi: 10.1016/j.ahj.2010.03.002.

Abstract

Trialists have an ethical and financial responsibility to plan and conduct clinical trials in a manner that will maximize the scientific knowledge gained from the trial. However, the amount of scientific information generated by randomized clinical trials in cardiovascular medicine is highly variable. Generation of trial databases and/or biobanks originating in large randomized clinical trials has successfully increased the knowledge obtained from those trials. At the 10th Cardiovascular Trialist Workshop, possibilities and pitfalls in designing and accessing clinical trial databases were discussed by a group of trialists. This review focuses on the arguments for conducting posttrial database studies and presents examples of studies in which posttrial knowledge generation has been substantial. Possible strategies to ensure successful trial database or biobank generation are discussed, in particular with respect to collaboration with the trial sponsor and to analytic pitfalls. The advantages of creating screening databases in conjunction with a given clinical trial are described; and finally, the potential for posttrial database studies to become a platform for training young scientists is outlined.

摘要

试验者有责任和义务以最大化从试验中获得的科学知识的方式来规划和进行临床试验。然而,心血管医学中随机临床试验所产生的科学信息量变化很大。源自大型随机临床试验的试验数据库和/或生物库的生成成功地增加了从这些试验中获得的知识。在第十届心血管试验者研讨会上,一组试验者讨论了设计和访问临床试验数据库的可能性和陷阱。本综述重点介绍了进行试验后数据库研究的理由,并提供了大量试验后知识生成的研究实例。讨论了确保成功生成试验数据库或生物库的可能策略,特别是与试验赞助商的合作以及分析陷阱。描述了与特定临床试验一起创建筛选数据库的优势;最后,概述了试验后数据库研究成为培训年轻科学家的平台的潜力。

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