Reflections on Sharing Clinical Trial Data Challenges and a Way Forward: Proceedings of a Workshop (2020) / Chapter Skim
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5 Data Interoperability and Platform Usability
5 Data Interoperability and Platform Usability
Pages 47-60
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From page 47... ...
(Hawk) • Data sharing prior to trial completion and pooling of data across studies can amplify potential safety signals.
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The session was moderated by Timothy Coetzee, chief advocacy, services, and research officer at the National Multiple Sclerosis Society, and Dina Paltoo, assistant director of Policy Development at the National Library of Medicine at the National Institutes of Health. WORKING WITH POPULATION DATA Ernest Hawk, Vice President and Head, Division of Cancer Prevention and Population Sciences, MD Anderson Hawk discussed issues of data interoperability and platform usability in the context of cancer prevention trials.
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External Validity of Trial Samples External validity is the extent to which the trial population represents the broader population the trial intends to serve. Hawk pointed out that the underrepresentation of women and minorities in cancer clinical trials persists, despite years of efforts intended to address this issue.
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, provider recommendation to a trial, and availability of culturally appropriate materials. Governance and Data Sharing Hawk's final example demonstrated the importance of data sharing prior to trial completion to amplify potential safety signals.
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Li explained that the student proposed to conduct a systematic review and IPD-NMA on competing treatments for advanced prostate cancer, and to explore whether treatment effect differs by patient characteristics for two tumor types. Wang identified relevant clinical trials that claimed to share IPD on four data-sharing platforms: Vivli, the Yale University Open Data Access (YODA)
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Although she sent each platform a similar proposal, her experience aried (e.g., v some granted permission based on the application as submitted while others required multiple iterations providing additional detail about the research plan)
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There is also a need for a "single, searchable database that catalogs all IPD available across different platforms," and Li offered the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP)
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Another program is focused on training machine-learning algorithms to augment radiologist interpretation of cancer progression in images from oncology clinical trials. All the research projects funded by Project Data Sphere are "leveraging the consolidation of data to do something that is not available otherwise," Louv said.
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and generally exist in different formats and ontologies. Raw imaging and genomic data are often collected in central specialty laboratories that have different data structures, data stewards (who might have different priorities for data sharing)
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Louv observed that there is still much work to be done on the infrastructure for data sharing, which requires funding, and he expressed hesitancy to form organizations in the absence of a sustainable structure. In response to a question from Hawk, Louv elaborated that Project Data Sphere is a not-for-profit organization that is sustained by its membership structure as well as grants and contracts.
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Data Quality Paltoo asked panelists to elaborate on data quality challenges relative to interoperability and usability. Louv reiterated that a key challenge is the "perishability" of clinical trial data.
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Sonali Kochhar suggested that funding infrastructure development could include the development of basic criteria to facilitate harmonization and data comparability (e.g., core outcomes, core data points to collect for each outcome, basic metadata requirements) , and funders could encourage academic and industry trial sponsors to follow these basic criteria.
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Few randomized controlled trials exist for rare tumors, for example, and Project Data Sphere is developing rare tumor registries to collect high-quality data. Data Sharing Impacts the Design and Conduct of Future Trials Tianjing Li added to the comment by Maguire that the IDDO datasharing platforms inform their research agendas and that their standardization efforts inform prospective data collection.
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