Pediatric Cancer Data Commons: Federating and Democratizing Data for Childhood Cancer Research. (2021)

• Record Type: Journal Article
• Authors: Plana, Alejandro; Furner, Brian; Palese, Monica; Dussault, Nicole; Birz, Suzi; Graglia, Luca; Kush, Maura; Nicholson, James; Hecker-Nolting, Stefanie; Gaspar, Nathalie; Rasche, Mareike; Bisogno, Gianni; Reinhardt, Dirk; Zwaan, C. Michel; Koscielniak, Ewa; Frazier, A. Lindsay; Janeway, Katherine; S. Hawkins, Douglas; Kolb, E. Anders; Cohn, Susan L.; Pearson, Andrew D. J.; Volchenboum, Samuel L.
• Is Part Of: JCO Clinical Cancer Informatics. Volume 5(2021)
• Publication Date: 2021
• Subjects: 616.994
• DOI: 10.1200/CCI.21.00075
• Languages: English
• ISSNs: 2473-4276

Abstract

Abstract : The international pediatric oncology community has a long history of research collaboration. In the United States, the 2019 launch of the Children's Cancer Data Initiative puts the focus on developing a rich and robust data ecosystem for pediatric oncology. In this spirit, we present here our experience in constructing the Pediatric Cancer Data Commons (PCDC) to highlight the significance of this effort in fighting pediatric cancer and improving outcomes and to provide essential information to those creating resources in other disease areas. The University of Chicago's PCDC team has worked with the international research community since 2015 to build data commons for children's cancers. We identified six critical features of successful data commons design and implementation: (1) establish the need for a data commons, (2) develop and deploy the technical infrastructure, (3) establish and implement governance, (4) make the data commons platform easy and intuitive for researchers, (5) socialize the data commons and create working knowledge and expertise in the research community, and (6) plan for longevity and sustainability. Data commons are critical to conducting research on large patient cohorts that will ultimately lead to improved outcomes for children with cancer. There is value in connecting high-quality clinical and phenotype data to external sources of data such as genomic, proteomics, and imaging data. Next steps for the PCDC include creating an informed and invested data-sharing culture, developing sustainable methods of data collection and sharing, standardizing genetic biomarker reporting, incorporating radiologic and molecular analysis data, and building models for electronic patient consent. The methods and processes described here can be extended to any clinical area and provide a blueprint for others wishing to develop similar resources.