scholarly journals Evaluation of Clinical Trial Data Sharing Policy in Leading Medical Journals

2020 ◽  
Author(s):  
Valentin Danchev ◽  
Yan Min ◽  
John Borghi ◽  
Mike Baiocchi ◽  
John P.A. Ioannidis
Keyword(s):  
Clinical Trials ◽  
New England ◽  
Data Sharing ◽  
Clinical Trial Data ◽  
International Committee ◽  
Data Reuse ◽  
Data Availability ◽  
Medical Journals ◽  
Pubmed Search ◽  
Materials Used

AbstractBackgroundThe benefits from responsible sharing of individual-participant data (IPD) from clinical studies are well recognized, but stakeholders often disagree on how to align those benefits with privacy risks, costs, and incentives for clinical trialists and sponsors. Recently, the International Committee of Medical Journal Editors (ICMJE) required a data sharing statement (DSS) from submissions reporting clinical trials effective July 1, 2018. We set out to evaluate the implementation of the policy in three leading medical journals (JAMA, Lancet, and New England Journal of Medicine (NEJM)).MethodsA MEDLINE/PubMed search of clinical trials published in the three journals between July 1, 2018 and April 4, 2020 identified 487 eligible trials (JAMA n = 112, Lancet n = 147, NEJM n = 228). Two reviewers evaluated each of the 487 articles independently. Captured outcomes were declared data availability, data type, access, conditions and reasons for data (un)availability, and funding sources.Findings334 (68.6%, 95% confidence interval (CI), 64.1%–72.5%) articles declared data sharing, with non-industry NIH-funded trials exhibiting the highest rates of declared data sharing (88.9%, 95% CI, 80.0%–97.8) and industry-funded trials the lowest (61.3%, 95% CI, 54.3%–68.3). However, only two IPD datasets were actually deidentified and publicly available as of April 10, 2020. The remaining were supposedly accessible via request to authors (42.8%, 143/334), repository (26.6%, 89/334), and company (23.4%, 78/334). Among the 89 articles declaring to store IPD in repositories, only 17 articles (19.1%) deposited data, mostly due to embargo and regulatory approval. Embargo was set in 47.3% (158/334) of data-sharing articles, and in half of them the period exceeded 1 year or was unspecified.InterpretationMost trials published in JAMA, Lancet, and NEJM after the implementation of the ICMJE policy declared their intent to make clinical data available. However, a wide gap between declared and actual data sharing exists. To improve transparency and data reuse, journals should promote the use of unique pointers to dataset location and standardized choices for embargo periods and access requirements. All data, code, and materials used in this analysis are available on OSF at https://osf.io/s5vbg/.

scholarly journals Status of the data sharing policies of scholarly journals published in Brazil, France, and Korea and listed in both the 2018 Scimago Journal and Country Ranking and the Web of Science

2020 ◽  
Vol 7 (2) ◽  
pp. 136-141 ◽  
Author(s):  
Geum Hee Jeong
Keyword(s):  
Clinical Trial ◽  
Data Sharing ◽  
Web Of Science ◽  
Clinical Trial Data ◽  
International Committee ◽  
Trial Data ◽  
Data Availability ◽  
Current Status ◽  
Standard Description ◽  
Scholarly Journals

Purpose: The present study analyzed the current status of the data sharing policies of journals published in Brazil, France, and Korea that were listed in the 2018 Scimago Journal and Country Ranking and Web of Science Core Collection.Methods: Web of Science journals were selected from the 2018 Scimago Journal and Country Ranking. The homepages of all target journals were searched for the presence of statements on data sharing policies, including clinical trial data sharing policies, the level of the policies, and actual statements of data availability in articles.Results: Out of 565 journals from these three countries, 118 (20.9%) had an optional data sharing policy, and one had a mandatory data sharing policy. Harvard Dataverse was the repository of one journal. The number of journals that had adopted a data sharing policy was 11 (6.7%) for Brazil, 64 (27.6%) for France, and 44 (25.9%) for Korea. One journal from Brazil and 20 journals from Korea had adopted clinical trial data sharing policies in accordance with the International Committee of Medical Journal Editors. Statements of data sharing were found in articles from two journals.Conclusion: Journals from France and Korea adopted data sharing policies more actively than those from Brazil. However, the actual implementation of these policies through descriptions of data availability in articles remains rare. In many journals that appear to have data sharing policies, those policies may just reflect a standard description by the publisher, especially in France. Actual data sharing was not found to be frequent.

scholarly journals Clinical Trial Data Sharing for COVID-19–Related Research

10.2196/26718 ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. e26718
Author(s):  
Louis Dron ◽  
Alison Dillman ◽  
Michael J Zoratti ◽  
Jonas Haggstrom ◽  
Edward J Mills ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Data Sharing ◽  
Statistical Power ◽  
Meta Analysis ◽  
False Negative ◽  
Clinical Trial Data ◽  
Control Group ◽  
Scientific Cooperation ◽  
Substantial Impact

This paper aims to provide a perspective on data sharing practices in the context of the COVID-19 pandemic. The scientific community has made several important inroads in the fight against COVID-19, and there are over 2500 clinical trials registered globally. Within the context of the rapidly changing pandemic, we are seeing a large number of trials conducted without results being made available. It is likely that a plethora of trials have stopped early, not for statistical reasons but due to lack of feasibility. Trials stopped early for feasibility are, by definition, statistically underpowered and thereby prone to inconclusive findings. Statistical power is not necessarily linear with the total sample size, and even small reductions in patient numbers or events can have a substantial impact on the research outcomes. Given the profusion of clinical trials investigating identical or similar treatments across different geographical and clinical contexts, one must also consider that the likelihood of a substantial number of false-positive and false-negative trials, emerging with the increasing overall number of trials, adds to public perceptions of uncertainty. This issue is complicated further by the evolving nature of the pandemic, wherein baseline assumptions on control group risk factors used to develop sample size calculations are far more challenging than those in the case of well-documented diseases. The standard answer to these challenges during nonpandemic settings is to assess each trial for statistical power and risk-of-bias and then pool the reported aggregated results using meta-analytic approaches. This solution simply will not suffice for COVID-19. Even with random-effects meta-analysis models, it will be difficult to adjust for the heterogeneity of different trials with aggregated reported data alone, especially given the absence of common data standards and outcome measures. To date, several groups have proposed structures and partnerships for data sharing. As COVID-19 has forced reconsideration of policies, processes, and interests, this is the time to advance scientific cooperation and shift the clinical research enterprise toward a data-sharing culture to maximize our response in the service of public health.

scholarly journals A survey of researchers' needs and priorities for data sharing

2021 ◽  
Author(s):  
Iain Hrynaszkiewicz ◽  
James Harney ◽  
Lauren Cadwallader
Keyword(s):  
Data Sharing ◽  
Research Impact ◽  
Open Science ◽  
Research Data ◽  
Data Reuse ◽  
Data Availability ◽  
Data Repositories ◽  
Use Of Data ◽  
Share Data ◽  
Do So

PLOS has long supported Open Science. One of the ways in which we do so is via our stringent data availability policy established in 2014. Despite this policy, and more data sharing policies being introduced by other organizations, best practices for data sharing are adopted by a minority of researchers in their publications. Problems with effective research data sharing persist and these problems have been quantified by previous research as a lack of time, resources, incentives, and/or skills to share data. In this study we built on this research by investigating the importance of tasks associated with data sharing, and researchers’ satisfaction with their ability to complete these tasks. By investigating these factors we aimed to better understand opportunities for new or improved solutions for sharing data. In May-June 2020 we surveyed researchers from Europe and North America to rate tasks associated with data sharing on (i) their importance and (ii) their satisfaction with their ability to complete them. We received 728 completed and 667 partial responses. We calculated mean importance and satisfaction scores to highlight potential opportunities for new solutions to and compare different cohorts.Tasks relating to research impact, funder compliance, and credit had the highest importance scores. 52% of respondents reuse research data but the average satisfaction score for obtaining data for reuse was relatively low. Tasks associated with sharing data were rated somewhat important and respondents were reasonably well satisfied in their ability to accomplish them. Notably, this included tasks associated with best data sharing practice, such as use of data repositories. However, the most common method for sharing data was in fact via supplemental files with articles, which is not considered to be best practice.We presume that researchers are unlikely to seek new solutions to a problem or task that they are satisfied in their ability to accomplish, even if many do not attempt this task. This implies there are few opportunities for new solutions or tools to meet these researcher needs. Publishers can likely meet these needs for data sharing by working to seamlessly integrate existing solutions that reduce the effort or behaviour change involved in some tasks, and focusing on advocacy and education around the benefits of sharing data. There may however be opportunities - unmet researcher needs - in relation to better supporting data reuse, which could be met in part by strengthening data sharing policies of journals and publishers, and improving the discoverability of data associated with published articles.

scholarly journals Clinical Trial Data Sharing for COVID-19–Related Research (Preprint)

2020 ◽  
Author(s):  
Louis Dron ◽  
Alison Dillman ◽  
Michael J Zoratti ◽  
Jonas Haggstrom ◽  
Edward J Mills ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Data Sharing ◽  
Statistical Power ◽  
Meta Analysis ◽  
False Negative ◽  
Clinical Trial Data ◽  
Control Group ◽  
Scientific Cooperation ◽  
Substantial Impact

UNSTRUCTURED This paper aims to provide a perspective on data sharing practices in the context of the COVID-19 pandemic. The scientific community has made several important inroads in the fight against COVID-19, and there are over 2500 clinical trials registered globally. Within the context of the rapidly changing pandemic, we are seeing a large number of trials conducted without results being made available. It is likely that a plethora of trials have stopped early, not for statistical reasons but due to lack of feasibility. Trials stopped early for feasibility are, by definition, statistically underpowered and thereby prone to inconclusive findings. Statistical power is not necessarily linear with the total sample size, and even small reductions in patient numbers or events can have a substantial impact on the research outcomes. Given the profusion of clinical trials investigating identical or similar treatments across different geographical and clinical contexts, one must also consider that the likelihood of a substantial number of false-positive and false-negative trials, emerging with the increasing overall number of trials, adds to public perceptions of uncertainty. This issue is complicated further by the evolving nature of the pandemic, wherein baseline assumptions on control group risk factors used to develop sample size calculations are far more challenging than those in the case of well-documented diseases. The standard answer to these challenges during nonpandemic settings is to assess each trial for statistical power and risk-of-bias and then pool the reported aggregated results using meta-analytic approaches. This solution simply will not suffice for COVID-19. Even with random-effects meta-analysis models, it will be difficult to adjust for the heterogeneity of different trials with aggregated reported data alone, especially given the absence of common data standards and outcome measures. To date, several groups have proposed structures and partnerships for data sharing. As COVID-19 has forced reconsideration of policies, processes, and interests, this is the time to advance scientific cooperation and shift the clinical research enterprise toward a data-sharing culture to maximize our response in the service of public health.

scholarly journals Clinical trial data transparency and GDPR compliance: Implications for data sharing and open innovation

2020 ◽  
Author(s):  
Timo Minssen ◽  
Neethu Rajam ◽  
Marcel Bogers
Keyword(s):  
Clinical Trials ◽  
Data Sharing ◽  
Open Innovation ◽  
Clinical Trial Data ◽  
Public Access ◽  
General Data Protection Regulation ◽  
Policy Goals ◽  
General Data ◽  
Data Transparency ◽  
Privacy Issues

Abstract Recent European Union (EU) initiatives and legislation have considerably increased public access to clinical trials data (CTD). These developments are generally much welcomed for the enhancement of science, trust, and open innovation. However, they also raise many questions and concerns, not least at the interface between CTD transparency and other areas of evolving EU law on the protection of trade secrets, IPRs, and privacy. This article focuses on privacy issues and on the interrelation between developments in transparency and the EU’s new General Data Protection Regulation 2016/679 (GDPR). More specifically, this article examines: (1) the origins and rationales of EU transparency regulations, including the incidents and concerns that have shaped them; (2) the features and implications of the GDPR which are relevant in the context of clinical trials; and (3) the risk for tensions between the GDPR and the policy goals of CTD transparency, as well as implications for data sharing and open innovation. Ultimately, we elaborate on factors that should be carefully considered and addressed to reap the full benefits of CTD transparency.

scholarly journals Data Sharing Statements for Clinical Trials — A Requirement of the International Committee of Medical Journal Editors

2017 ◽  
Vol 376 (23) ◽  
pp. 2277-2279 ◽  
Author(s):  
Darren B. Taichman ◽  
Peush Sahni ◽  
Anja Pinborg ◽  
Larry Peiperl ◽  
Christine Laine ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Medical Journal ◽  
Data Sharing ◽  
International Committee ◽  
Journal Editors

scholarly journals Clinical trial data reuse – overcoming complexities in trial design and data sharing

Trials ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Toby Wilkinson ◽  
Siddharth Sinha ◽  
Niels Peek ◽  
Nophar Geifman
Keyword(s):  
Clinical Trial ◽  
Data Sharing ◽  
Trial Design ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Data Reuse

scholarly journals Data Sharing Statements for Clinical Trials: A Requirement of the International Committee of Medical Journal Editors

PLoS Medicine ◽  
2017 ◽  
Vol 14 (6) ◽  
pp. e1002315 ◽  
Author(s):  
Darren B. Taichman ◽  
Peush Sahni ◽  
Anja Pinborg ◽  
Larry Peiperl ◽  
Christine Laine ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Medical Journal ◽  
Data Sharing ◽  
International Committee ◽  
Journal Editors

scholarly journals Statement of Data Sharing Goals for Nonprofit Funders of Clinical Trials (Preprint)

2020 ◽  
Author(s):  
Timothy Coetzee ◽  
Mad Price Ball ◽  
Marc Boutin ◽  
Abby Bronson ◽  
David T. Dexter ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Data Sharing ◽  
Clinical Trial Data ◽  
Original Research ◽  
Data Sets ◽  
Research Participants ◽  
Starting Point ◽  
Disease Advocacy ◽  
New Research

UNSTRUCTURED Sharing clinical trial data can provide value to research participants and communities by accelerating the development of new knowledge and therapies as investigators merge data sets to conduct new analyses, reproduce published findings to raise standards for original research, and learn from the work of others to generate new research questions. As a voice for the perspective of participants in clinical trials, nonprofit funders – including disease advocacy and patient-focused organizations – play a pivotal role in the promotion and implementation of data sharing policies. Funders are uniquely positioned to promote and support a culture of data sharing by serving as trusted liaisons between potential research participants and investigators who wish to access these participant networks for clinical trial recruitment. In short, nonprofit funders can drive policies and influence research culture. The purpose of this statement is to detail a set of aspirational goals and forward-thinking, collaborative solutions to data sharing for nonprofit funders to fold into existing funding policies. The goals in this statement convey the complexity of the opportunities and challenges facing nonprofit funders and the appropriate prioritization of data sharing within their organizations and may serve as a starting point for a data sharing “toolkit” for nonprofit funders of clinical trials, to provide the clarity of mission and mechanisms to enforce the data sharing practices their communities already expect are happening.

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