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Privacy and Publication: challenges and opportunities for clinical data
Varsha Khodiyar discusses challenges and opportunities for sharing clinical trial data. Withholding data impacts human health by allowing reporting bias. There is increasing support for data transparency from funders, regulators, legislation, and journals. Journals are implementing stronger data sharing policies like mandating open data submission. While researchers generally support sharing de-identified data through repositories, concerns around patient privacy and inappropriate secondary analysis remain. Better solutions involve data use agreements and controlled access environments for requesting and reviewing data. Repositories should provide robust mechanisms for hosting and managing access to non-public clinical data.
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Privacy and Publication: challenges and opportunities for clinical data
- 1. Privacy and Publication:challenges and opportunities for clinical data Varsha Khodiyar, PhD Data Curation Editor, Scientific Data Nature Publishing Group [email protected] @varsha_khodiyar @scientificdata Big Data Opportunities Using the NDA, 17th October 2015
- 2. Reporting bias impactshuman health Oseltamvir: “only...effective...for the prevention and treatment of symptoms of influenza” Cochrane Database Syst Rev. 2012 DOI: 10.1002/14651858.CD008965.pub3 Reboxetine: “overall an ineffective and potentially harmful antidepressant” BMJ 2010;341:c4737 Statins: “beneficial effect…on atrial fibrillation...is not supported by a comprehensive review of published and unpublished evidence” BMJ 2011;342:d1250
- 3. 3 Withholding data impactshuman health
- 4. Increasing support fordata transparency • Funder/institution policy and mandates1 • Regulatory agencies (EMA) • Legislation (FDAAA) • Non-governmental/academic (IOM, YODA) • Industry (CSDR) • Journals and ICMJE2 4 1. Hahnel, Mark (2015): Global funders who require data archiving as a condition of grants. figshare. http://dx.doi.org/10.6084/m9.figshare.1281141 2. http://www.icmje.org/news-and-editorials/principles_data_sharing_jan2014.html
- 5. Publishers/journals and dataaccess • More reliable evidence – and papers • Journal mission/goals • Help community derive maximum benefit from research • Content innovation (facilitate more use and reuse) • Reliability (peer review) • Discoverability and visibility (bibliographic databases) • Linking and licensing content (open access) • Permanence (content and links) • Credit/incentives (article types and citations) • Encouraging and implementing good practice and policies 5
- 6. Journal data policies •Willingness to share stated (Annals Internal Medicine) • Data sharing implied by submission (BioMed Central*) • Data sharing implied as a condition of publication (Nature*) • Mandated data sharing with statement in paper (PLOS, BMJ - for clinical trials) • Mandated data sharing with statement and link to data (non- medical journals e.g. ecology, animal genomics) • Mandated open data as a condition of submission (Scientific Data, GigaScience, F1000Research) *Minimum requirement – some disciplines/journals may mandate 6 STRONGER 1. Vines, T. H. et al. Mandated data archiving greatly improves access to research data. FASEB J. fj.12–218164– (2013). doi:10.1096/fj.12-218164
- 7. Data sharing viasupplementary files 7 Sandercock et al: The International Stroke Trial database. Trials 2011, 12:101 doi:10.1186/1745-6215-12-101
- 8. Data sharing viarepository links 8
- 9. Data sharing viarepository links 9
- 10. Data sharing viarepository links 10
- 11. Role of datajournals/articles • Data peer review • Outlet for ‘unpublishable’ data • Data discoverability • Data reusability • Permanence of datasets • Robust links with repositories • Credit/reward data generators • “Intelligently open data” 11
- 12.
- 13. Scientific Data peerreview Peer review focuses on: • Completeness (can others reproduce?) • Consistency (were community standards followed?) • Integrity (are data in the best repository?) • Experimental rigour and technical quality (were the methods sound?) Does not focus on: • Perceived impact/importance • Size/complexity of data
- 14. An example DataDescriptor 14 Human readable representation of study i.e. article (HTML & PDF) Human readable representation of study i.e. article (HTML & PDF) Machine readable representation of study i.e. metadata
- 15. Scientific Data structuredmetadata In-house curation team: • assists users to submit the structured content via simple templates and an internal authoring tool • performs value-added semantic annotation of the experimental metadata analysis method script Data file or record in a database
- 16. Data on (reasonable)request - issues 16 • Meta-analysis fails to launch when <40% IPD available – unanswered requests and refusal to share Systematic Reviews 2014, 3:97 doi:10.1186/2046-4053-3-97 • Poor availability of psychological research data (only 64/249 datasets available) American Psychologist 2006, 61(7) doi:10.1037/0003-066X.61.7.726 • Data received from 1/10 authors publishing in PLOS Medicine and PLOS Clinical Trials PLoS ONE 2009, 4(9): doi:10.1371/journal.pone.0007078 • 38% of 394 requested datasets received from APA journal authors Collabra 2015, 1(1): doi:10.1525/collabra.13
- 17. Clinical researchers supportsharing 17 Rathi V, Dzara K, Gross CP, Hrynaszkiewicz I, Joffe S, Krumholz HM, Strait KM, Ross JS: Sharing of clinical trial data among trialists: a cross sectional survey. BMJ 2012;345:e7570 • Sharing de-identified data via repositories should be required (236 respondents, 74%) • Investigators should share de-identified data on request (229 respondents, 72%)
- 18. What are researchers’concerns? 18 Reproduced from: Rathi V, Dzara K, Gross CP, Hrynaszkiewicz I, Joffe S, Krumholz HM, Strait KM, Ross JS: Sharing of clinical trial data among trialists: a cross sectional survey. BMJ 2012;345:e7570
- 19. Better ways toshare on request 19 Yale Open Data Access (YODA) & Clinical Study Data Request (CSDR) projects: • Data Use Agreements (DUAs) • Controlled access environment • Scientific validity of reanalysis checked • Independent governance • Data anonymisation checks http://yoda.yale.edu/ https://www.clinicalstudydatarequest.com/
- 20. Better way topublish data on request 20 • Sensitive data repositories (e.g. UKDA) Permanence, curation, persistent identifiers, versioning • Data-on-request services (e.g. YODA) Independent governance, scientific review and transparency of access requests, DUAs • Journals/publishers Peer review, visibility, credit/citations, robust links+ =
- 21. A robust data-on-requestworkflow? 21 Hrynaszkiewicz, I., Khodiyar, V., Hufton, A. & Sansone, S. A. Publishing descriptions of non-public clinical datasets: guidance for researchers, repositories, editors and funding organisations. BioRxiv http://dx.doi.org/10.1101/021667 (2015).
- 22. Open access DataDescriptor 22 http://www.nature.com/articles/sdata201531
- 23. Open access DataDescriptor 23 http://www.nature.com/articles/sdata201531
- 24. Linked to restrictedaccess data http://dx.doi.org/10.7910/DVN/25833 All approved repositories: http://www.nature.com/sdata/data-policies/repositories
- 25. Key recommendations 25 • Clinicalresearchers: Prepare to share on request, with short embargoes • Repositories: Develop mechanisms to host clinical data non-publicly and manage access requests; collaborate with journals • Editors and publishers: Check policy compliance for every submission and facilitate peer reviewer access to data; collaborate with repositories • Sponsors and funders: Partner with trusted repositories and ensure that data access requests are proportionately reviewed without introducing unnecessary barriers
- 26. Repositories for non-publicdata should 26 • Provide stable identifiers for metadata records • Allows access to data with the minimum of restrictions, codified in DUAs • Ideally be independent of the study sponsors • Have a transparent and persistent system for requesting access to data and reviewing requests to access data • Allow access to data in a timely manner • Ensure long-term preservation of data in their non-public form
- 27. Visit nature.com/sdata Email [email protected] Tweet@ScientificData Honorary Academic Editor Susanna-Assunta Sansone Managing Editor Andrew L. Hufton Data Curation Editor Varsha K. Khodiyar Advisory Panel and Editorial Board including senior researchers, funders, librarians and curators Supported by
Editor's Notes
- #17 Data on request policies do not result in data sharing