Sharing clinical trial data on patient level: Opportunities and challenges

被引:30
|
作者
Koenig, Franz [1 ]
Slattery, Jim [2 ]
Groves, Trish [3 ]
Lang, Thomas [4 ]
Benjamini, Yoav [5 ]
Day, Simon [6 ]
Bauer, Peter [1 ]
Posch, Martin [1 ]
机构
[1] Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, A-1090 Vienna, Austria
[2] European Med Agcy, London E14 4HB, England
[3] BMJ, London WC1H 9JR, England
[4] AGES Austrian Agcy Hlth & Food Safety, Fed Off Safety Hlth Care, A-1200 Vienna, Austria
[5] Tel Aviv Univ, Dept Stat & Operat Res, Sackler Fac Exact Sci, IL-6997801 Tel Aviv, Israel
[6] Clin Trials Consulting & Training, North Marston MK18 3PL, Bucks, England
关键词
EMA draft policy/0070; Open access to clinical trial data; Raw data; Secondary research; Transparency; Validation; DRUG; STATISTICIANS; AUTHORS;
D O I
10.1002/bimj.201300283
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In recent months one of the most controversially discussed topics among regulatory agencies, the pharmaceutical industry, journal editors, and academia has been the sharing of patient-level clinical trial data. Several projects have been started such as the European Medicines Agency's (EMA) "proactive publication of clinical trial data", the BMJ open data campaign, or the AllTrials initiative. The executive director of the EMA, Dr. Guido Rasi, has recently announced that clinical trial data on patient level will be published from 2014 onwards (although it has since been delayed). The EMA draft policy on proactive access to clinical trial data was published at the end of June 2013 and open for public consultation until the end of September 2013. These initiatives will change the landscape of drug development and publication of medical research. They provide unprecedented opportunities for research and research synthesis, but pose new challenges for regulatory authorities, sponsors, scientific journals, and the public. Besides these general aspects, data sharing also entails intricate biostatistical questions such as problems of multiplicity. An important issue in this respect is the interpretation of multiple statistical analyses, both prospective and retrospective. Expertise in biostatistics is needed to assess the interpretation of such multiple analyses, for example, in the context of regulatory decision-making by optimizing procedural guidance and sophisticated analysis methods.
引用
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页码:8 / 26
页数:19
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