TY - JOUR
T1 - Development of a data model and data commons for germ cell tumors
AU - Ci, Bo
AU - Yang, Donghan M.
AU - Krailo, Mark
AU - Xia, Caihong
AU - Yao, Bo
AU - Luo, Danni
AU - Zhou, Qinbo
AU - Xiao, Guanghua
AU - Xu, Lin
AU - Skapek, Stephen X.
AU - Murray, Matthew J.
AU - Amatruda, James F.
AU - Klosterkemper, Lindsay
AU - Shaikh, Furqan
AU - Faure-Conter, Cecile
AU - Fresneau, Brice
AU - Volchenboum, Samuel L.
AU - Stoneham, Sara
AU - Lopes, Luiz Fernando
AU - Nicholson, James
AU - Lindsay Frazier, A.
AU - Xie, Yang
N1 - Funding Information:
Supported by Grants No. 358099 from St Baldrick’s Foundation, No. 5P30CA142543 and R01GM115473 from the National Institutes of Health, and No. RP180805 from the Cancer Prevention Research Institute of Texas.
Publisher Copyright:
© 2020 American Society of Clinical Oncology. All rights reserved.
PY - 2020
Y1 - 2020
N2 - Germ cell tumors (GCTs) are considered a rare disease but are the most common solid tumors in adolescents and young adults, accounting for 15% of all malignancies in this age group. The rarity of GCTs in some groups, particularly children, has impeded progress in treatment and biologic understanding. The most effective GCT research will result from the interrogation of data sets from historical and prospective trials across institutions. However, inconsistent use of terminology among groups, different sample-labeling rules, and lack of data standards have hampered researchers' efforts in data sharing and across-study validation. To overcome the low interoperability of data and facilitate future clinical trials, we worked with the Malignant Germ Cell International Consortium (MaGIC) and developed a GCT clinical data model as a uniform standard to curate and harmonize GCT data sets. This data model will also be the standard for prospective data collection in future trials. Using the GCT data model, we developed a GCT data commons with data sets from both MaGIC and public domains as an integrated research platform. The commons supports functions, such as data query, management, sharing, visualization, and analysis of the harmonized data, as well as patient cohort discovery. This GCT data commons will facilitate future collaborative research to advance the biologic understanding and treatment of GCTs. Moreover, the framework of the GCT data model and data commons will provide insights for other rare disease research communities into developing similar collaborative research platforms.
AB - Germ cell tumors (GCTs) are considered a rare disease but are the most common solid tumors in adolescents and young adults, accounting for 15% of all malignancies in this age group. The rarity of GCTs in some groups, particularly children, has impeded progress in treatment and biologic understanding. The most effective GCT research will result from the interrogation of data sets from historical and prospective trials across institutions. However, inconsistent use of terminology among groups, different sample-labeling rules, and lack of data standards have hampered researchers' efforts in data sharing and across-study validation. To overcome the low interoperability of data and facilitate future clinical trials, we worked with the Malignant Germ Cell International Consortium (MaGIC) and developed a GCT clinical data model as a uniform standard to curate and harmonize GCT data sets. This data model will also be the standard for prospective data collection in future trials. Using the GCT data model, we developed a GCT data commons with data sets from both MaGIC and public domains as an integrated research platform. The commons supports functions, such as data query, management, sharing, visualization, and analysis of the harmonized data, as well as patient cohort discovery. This GCT data commons will facilitate future collaborative research to advance the biologic understanding and treatment of GCTs. Moreover, the framework of the GCT data model and data commons will provide insights for other rare disease research communities into developing similar collaborative research platforms.
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U2 - 10.1200/CCI.20.00025
DO - 10.1200/CCI.20.00025
M3 - Article
C2 - 32568554
AN - SCOPUS:85086886308
SN - 2473-4276
VL - 4
SP - 555
EP - 566
JO - JCO clinical cancer informatics
JF - JCO clinical cancer informatics
ER -