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Review
. 2023 Apr 14;83(8):1183-1190.
doi: 10.1158/0008-5472.CAN-22-1277.

Case Studies for Overcoming Challenges in Using Big Data in Cancer

Shawn M Sweeney  1 , Hisham K Hamadeh  2 , Natalie Abrams  3 , Stacey J Adam  4 , Sara Brenner  5 , Dana E Connors  4 , Gerard J Davis  6 , Louis D Fiore  7 , Susan H Gawel  6 , Robert L Grossman  8 , Sean E Hanlon  9 , Karl Hsu  10 , Gary J Kelloff  11 , Ilan R Kirsch  12 , Bill Louv  13 , Deven McGraw  14 , Frank Meng  15 , Daniel Milgram  16 , Robert S Miller  17 , Emily Morgan  4 , Lata Mukundan  16 , Thomas O'Brien  18 , Paul Robbins  18 , Eric H Rubin  19 , Wendy S Rubinstein  5 , Liz Salmi  20 , Teilo H Schaller  13 , George Shi  6 , Caroline C Sigman  15 , Sudhir Srivastava  21
Affiliations
Review

Case Studies for Overcoming Challenges in Using Big Data in Cancer

Shawn M Sweeney et al. Cancer Res. .

Abstract

The analysis of big healthcare data has enormous potential as a tool for advancing oncology drug development and patient treatment, particularly in the context of precision medicine. However, there are challenges in organizing, sharing, integrating, and making these data readily accessible to the research community. This review presents five case studies illustrating various successful approaches to addressing such challenges. These efforts are CancerLinQ, the American Association for Cancer Research Project GENIE, Project Data Sphere, the National Cancer Institute Genomic Data Commons, and the Veterans Health Administration Clinical Data Initiative. Critical factors in the development of these systems include attention to the use of robust pipelines for data aggregation, common data models, data deidentification to enable multiple uses, integration of data collection into physician workflows, terminology standardization and attention to interoperability, extensive quality assurance and quality control activity, incorporation of multiple data types, and understanding how data resources can be best applied. By describing some of the emerging resources, we hope to inspire consideration of the secondary use of such data at the earliest possible step to ensure the proper sharing of data in order to generate insights that advance the understanding and the treatment of cancer.

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