Sharing clinical trial data on patient level: opportunities and challenges

Abstract

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.

Keywords: EMA draft policy/0070; Open access to clinical trial data; Raw data; Secondary research; Transparency; Validation.

Figure 1

Testing a family of families (Benjamini and Bogomolov, 2014). Based on the data at hand H_m is not selected, so H_m1, H_m2, and H_m3 are not tested. Since two of three families were selected at each family FDR needs to be controlled at level q(2/3) in order to assure FDR on the average over the selected at level q.

Figure 2

Hierarchical testing of hypotheses (Yekutieli et al., 2006). Each family of hypotheses is tested at FDR level q only if its parent hypothesis was rejected. Counting all discoveries made, the overall FDR remains at about 2q, no matter how large and what form the tree takes.