Discussion Framework for Clinical Trial Data Sharing Guiding Principles, Elements, and Activities (2014) / Chapter Skim
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Discussion Framework for Clinical Trial Data Sharing
Discussion Framework for Clinical Trial Data Sharing
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has undertaken regulatory action to share anonymized clinical trial data with external requestors. The EMA's data sharing initiative is described on p.
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. To that end, a large number of people and organizations involved in clinical trials have endorsed principles promoting, in their view, responsible sharing of clinical trial data (Loder, 2013)
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, to be released in January 2014 for public comment. The framework will summarize the committee's initial thoughts on guiding principles that underpin responsible sharing of clinical trial data, define key elements of clinical trial data and data shar ing, and describe a selected set of clinical trial data sharing activ ities.
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The committee is also charged, in the final report, with suggesting strategies and practical approaches for responsible data sharing. As part of its recommendations, the committee will offer guiding principles for and characteristics of the optimal infrastructure and governance for data sharing.
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, surgical procedures, behavioral interventions, and changes in the administration or delivery of clinical care. A FRAMEWORK FOR DISCUSSION AND CALL FOR COMMENTS This framework for discussion articulates the committee's preliminary thoughts on guiding principles that underpin the responsible sharing of clinical trial data, defines key elements of data and data sharing activities, and describes a selected set of data sharing activities.
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x Should programs or approaches calling for or requiring new data sharing apply only to new trials undertaken from the date of a new program forward, or retroactively apply to clinical trials started before the data sharing program was initiated? Mitigating Risks x What might be done to minimize the risks to patients and to public health from the dissemination of findings from invalid analyses of shared clinical trial data?
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Measuring Impact x What would be appropriate outcome measures to assess the use fulness of different models of clinical trial data sharing, and how can they be used to guide improvements in data sharing practices? Invitation for Public Comments The issues identified and the options and observations described in this framework are preliminary and do not represent a comprehensive review of the subject.
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. Policies regarding clinical trial data sharing will have a stronger intellectual foundation and practical applicability if they take into account policies on related topics.
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In its further deliberations and final report, the committee will assess these potential consequences of clinical trials data sharing. Respect the Individual Participants Whose Data Are Shared The committee's first provisional guiding principle stems from the broadly articulated concept that respect for research participants is a fundamental principle of research ethics (ICH, 1996; National Commission, 1979)
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. For example, new policies and procedures regarding data sharing and subsequent additional analyses (particularly for specific trials or classes of trials as relevant)
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This provisional guiding principle for responsible sharing of clinical trial data is derived from the ethical concept of beneficence. Potential Benefits International ethical standards identify beneficence as a basic ethical principle and obligation of research involving human subjects.
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Sharing clinical trial data could potentially lead to enhanced efficiency and safety of the clinical research process by, for example, x reducing duplication of efforts and costs of future studies; x reducing exposure of participants in future trials to avoidable harms that can be identified through data sharing; x providing a deeper knowledge base for regulatory decisions; x supporting the development of clinical practice guidelines; and x allowing health care professionals and patients to make more in formed decisions about clinical care. The usefulness of clinical trial data would be enhanced if, in addition to sharing the protocol, manual of operations, statistical analysis plan, a copy of the case report forms, and metadata about the analyzable data file, the data user could ask the data generator questions regarding logistical and practical issues such as the conduct of the clinical trial or data analyses.
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Clinical trialists and sponsors of clinical trials could also suffer potential harms due to the administrative and financial burden of data sharing, which they might regard as an unfunded mandate. The manner in which data are shared might undermine the incentives of clinical trial sponsors, clinical investigators, coordinating centers, researchers, and other essential stakeholders to invest time and resources in the development and clinical testing of potential new treatment practices (Dickersin, 2013; Rathi et al., 2012)
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The process of data sharing should therefore be undertaken in a manner that enhances, rather than undermines, public trust in both the clinical trial process and the data sharing process. Trust in Clinical Trial Data By increasing the transparency of trial design and conduct and the pathway to trial conclusions, sharing clinical trial data might increase public trust in the outcomes of specific trials and of clinical trials generally (Loder, 2013)
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Trust in the Data Sharing Process Sharing clinical trial data could carry the risk of undermining public trust in clinical trials under certain circumstances, for example, if multiple analyses yield conflicting or invalid conclusions (Califf, 2013)
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Fairness in the Distribution of the Potential Benefits of Research Clinical trial data sharing could increase fairness in clinical research by helping to distribute the benefits of clinical research more equitably across different groups of participants and communities. Pooling shared data from several clinical trials could, for example, benefit groups who have been enrolled in clinical trials in such small numbers that the statistical power in any single trial to draw valid inferences about risks and
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Implementation of these principles might take into account operational considerations, such as x timing of when data are shared; x proportional consideration of benefits, burdens, and risks to vari ous parties in adopting a data sharing program or activity; x opportunities to embed "learning" in a clinical trial data sharing system, permitting tracking of the beneficial outcomes of differ ent approaches to data sharing, identification of unanticipated
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Foundational to any discussion of possibilities and needs for clinical trial data sharing is a fundamental philosophical question: To whom do the benefits of the data belong? Are data primarily for the benefit of the public or for private parties?
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While we have framed these positions as a dichotomy for the sake of discussion, another approach would be to balance both perspectives in a policy of clinical trial data sharing, in addition to adhering to the other guiding principles discussed above, as well as applicable existing, modified, or new legal requirements. Any attempt to balance competing interests would require careful attention to the conditions of sharing, responsibilities, limitations, and exceptions.
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. Many discussions of clinical trial data sharing thus far have not been specific regarding which of many possible clinical trial data elements or datasets might be shared.
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that might be included in a data sharing activity (see Figure 1)
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meet protocolspecified criteria. In addition to "traditional" clinical trial data, other types of health data are increasingly being collected, including self-reported measures (e.g., quality of life)
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Moreover, peer-reviewed journal publications of clinical trials generally draw on only part of the analyzable dataset. Supplemental data are often collected to permit exploration of ancillary questions not directly related to the primary purpose of the protocol, and researchers might conduct exploratory and post hoc analysis not defined in the SAP to answer additional questions.
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Registry results summary and lay-language summary Many clinical trials are subject to a requirement that their results be reported to one or more registries, in formats specified by the particular registry (for example, results of trials of FDA-regulated products must be reported to ClinicalTrials.gov in the United States)
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Supporting documentation critical to interpretation of shared clinical trial data include the full protocol, manual of operations, consent form, case report forms, and the SAP. The trial protocol describes the trial rationale; the eligibility and exclusion criteria for participants; the primary and secondary hypotheses
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For key analyses, full use of the shared data would be aided by providing the computer software and version used, as well as the statistical programming code for the statistical software used for each analysis. BOX 4 Metadata and Additional Documentation to Support the Use of Shared Clinical Trial Data x Clinical trial registration number and dataset (available through ClinicalTrials.gov and other registries)
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The final report will include discussion of how the information in the analyzable dataset, CSR, and IPD differ and which types of analyses, either confirmatory or exploratory, require which level of data sharing. Who Are the Providers of Shared Data?
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Many individuals and entities could be recipients of shared data from clinical trials. These include (but are not limited to)
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A variety of models for clinical trial data sharing have been proposed, planned, or implemented (select examples are summarized in Box 5)
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Data sharing can also take place indirectly, through a "trusted intermediary" or "honest broker," who either negotiates the conditions for data sharing (with the data provider retaining control over the data and its release) or takes full control of the data and brokers both the conditions for data release and the delivery to recipients (Mello et al., 2013)
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The rationale, benefits, risks, and burdens associated with one particular data sharing activity could differ from those of another data sharing activity, depending on the data elements and parties involved. To stimulate public comments and to provide heuristic organizational structure to its work, the committee has described a selected set of data sharing activities as examples of the types of arrangements or approaches under which clinical trial data might be shared (see Box 5)
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Detailed descriptions and, particularly, conclusions and recommendations regarding those descriptive characteristics or strategies and approaches for sharing will be included in the final report. BOX 5 Set of Clinical Trial Data Sharing Activities 1.
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, prohibition on use of data for commercial purposes, prohibition on attempts to re-identify data, requirement to inform data generator about any safety con cerns identified, agreement that the data generator retains exclu sive rights to inventions or other intellectual property generated by the data recipient, or requirement to acknowledge the source of the shared data and the investigators in the original clinical trial g. Example activities: PhRMA/EFPIA commitments, Harvard Multi Regional Clinical Trials Center proposal, Yale Open Data Access Controlled Access to Pooled or Multiple Data Sources A data sharing program or system in which data are made available to requestors on a controlled-access basis pursuant to defined re strictions or conditions.
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Providers of data: as determined by the organizational structure of the data sharing activity. Providers could include sponsors of applications for regulatory approval of products, researchers funded by a government source, or other data generators as re quired or agreed on c.
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Conditions of data use: restrictions or conditions on data use might include a requirement to sign a partnership/consortium agreement, an agreement governing rights to inventions or other intellectual property generated by the data sharing activity, or an agreement dictating whether and how future publications will be undertaken g. Example activities: PatientsLikeMe ____________________ a Activities listed here are considered examples of the described data sharing activity because they have some or many of the listed descriptive characteris tics.
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