Patient consent to publication and data sharing in industry and NIH-funded clinical trials

Spence, O’Mareen; Uba, Richie Onwuchekwa; Shin, Seunghyup; Doshi, Peter

doi:10.1186/s13063-018-2651-2

Cited by 14 publications

(8 citation statements)

References 16 publications

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“…While consent seems to be a crucial issue for trial participants, an analysis of 98 informed consent forms found that only 6 (4%) indicated a commitment to share deidentified IPD with third party researchers. 44 Commitments to share were more common in publicly funded trials than in industry-funded trials (7% vs 3%).…”

Section: Resultsmentioning

confidence: 99%

Status, use and impact of sharing individual participant data from clinical trials: a scoping review

et al. 2021

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ObjectivesTo explore the impact of data-sharing initiatives on the intent to share data, on actual data sharing, on the use of shared data and on research output and impact of shared data.Eligibility criteriaAll studies investigating data-sharing practices for individual participant data (IPD) from clinical trials.Sources of evidenceWe searched the Medline database, the Cochrane Library, the Science Citation Index Expanded and the Social Sciences Citation Index via Web of Science, and preprints and proceedings of the International Congress on Peer Review and Scientific Publication. In addition, we inspected major clinical trial data-sharing platforms, contacted major journals/publishers, editorial groups and some funders.Charting methodsTwo reviewers independently extracted information on methods and results from resources identified using a standardised questionnaire. A map of the extracted data was constructed and accompanied by a narrative summary for each outcome domain.Results93 studies identified in the literature search (published between 2001 and 2020, median: 2018) and 5 from additional information sources were included in the scoping review. Most studies were descriptive and focused on early phases of the data-sharing process. While the willingness to share IPD from clinical trials is extremely high, actual data-sharing rates are suboptimal. A survey of journal data suggests poor to moderate enforcement of the policies by publishers. Metrics provided by platforms suggest that a large majority of data remains unrequested. When requested, the purpose of the reuse is more often secondary analyses and meta-analyses, rarely re-analyses. Finally, studies focused on the real impact of data-sharing were rare and used surrogates such as citation metrics.ConclusionsThere is currently a gap in the evidence base for the impact of IPD sharing, which entails uncertainties in the implementation of current data-sharing policies. High level evidence is needed to assess whether the value of medical research increases with data-sharing practices.

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Section: Resultsmentioning

confidence: 99%

Status, use and impact of sharing individual participant data from clinical trials: a scoping review

et al. 2021

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“…Other analyses explored the actual commitment to IPD sharing. Very few (5%) of the studies registered at ClinicalTrials.gov in 2016–2017 by high-volume registrants provided a data-sharing plan [ 36 ] and only 4% of the consent forms of a sample of antibiotic studies, both from public and industry funders, reported a commitment to share IPD [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of repositories for sharing individual-participant data from clinical studies

Banzi

Canham²,

Kuchinke

et al. 2019

Trials

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BackgroundData repositories have the potential to play an important role in the effective and safe sharing of individual-participant data (IPD) from clinical studies. We analysed the current landscape of data repositories to create a detailed description of available repositories and assess their suitability for hosting data from clinical studies, from the perspective of the clinical researcher.MethodsWe assessed repositories that enable storage, sharing, discoverability, re-use of the IPD and associated documents from clinical studies using a pre-defined set of 34 items and publicly available information from April to June 2018. For this purpose, we developed an indicator set to capture the maturity of the repositories’ procedures and their suitability for the hosting of IPD. The indicators cover guidelines for data upload and data de-identification, data quality controls, contracts for upload and storage, flexibility of access, application of identifiers, availability of metadata, and long-term preservation.ResultsWe analysed 25 repositories, from an initial set of 55 identified as possibly relevant. Half of the included repositories were generic, i.e. not limited to a specific disease or clinical area and 13 were launched in the last 8 years. The sample was extremely heterogeneous and included repositories developed by research funders, infrastructures, universities, and editors. All but three repositories do not apply a fee for uploading, storage or access to data. None of the repositories completely demonstrated all the items included in the indicator set, but three repositories (Dryad, Drum, EASY) met – fully or partially – all items. Flexibility of data-access modalities appears to be limited, being lacking in half of the repositories.ConclusionsOur evaluation, though often hampered by the lack of sufficient information, can help researchers to find a suitable repository for their datasets. Some repositories are more mature because of their support for clinical dataset preparation, contractual agreements, metadata and identifiers, different modalities of access, and long-term preservation of data. Further work is now required to achieve a more robust and accurate system for evaluation, which in turn may encourage the sharing of clinical study data.Trial registrationStudy protocol available at https://zenodo.org/record/1438261#.W64kW9Egrcs.Electronic supplementary materialThe online version of this article (10.1186/s13063-019-3253-3) contains supplementary material, which is available to authorized users.

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“…For instance, how data were collected or processed can affect the way they are shared. Sharing initiatives concerning data collected from human subjects are influenced by informed consent (Spence et al, 2018;White et al, 2020). This can also be affected by processing activities such as anonymization, de-identification, and pseudonymization.…”

Section: What Does An Idg Framework For Neuroscience Look Like?mentioning

confidence: 99%

International data governance for neuroscience

Eke

Bernard

Bjaalie

et al. 2022

Neuron

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As neuroscience projects increase in scale and cross international borders, different ethical principles, national and international laws, regulations, and policies for data sharing must be considered. These concerns are part of what is collectively called data governance. Whereas neuroscience data transcend borders, data governance is typically constrained within geopolitical boundaries. An international data governance framework and accompanying infrastructure can assist investigators, institutions, data repositories, and funders with navigating disparate policies. Here, we propose principles and operational considerations for how data governance in neuroscience can be navigated at an international scale and highlight gaps, challenges, and opportunities in a global brain data ecosystem. We consider how to approach data governance in a way that balances data protection requirements and the need for open science, so as to promote international collaboration through federated constructs such as the International Brain Initiative (IBI). ll

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Patient consent to publication and data sharing in industry and NIH-funded clinical trials

Cited by 14 publications

References 16 publications

Status, use and impact of sharing individual participant data from clinical trials: a scoping review

Status, use and impact of sharing individual participant data from clinical trials: a scoping review

Evaluation of repositories for sharing individual-participant data from clinical studies

International data governance for neuroscience

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