Challenges to Using Big Data in Cancer.


Journal

Cancer research
ISSN: 1538-7445
Titre abrégé: Cancer Res
Pays: United States
ID NLM: 2984705R

Informations de publication

Date de publication:
14 04 2023
Historique:
received: 15 04 2022
revised: 29 07 2022
accepted: 05 12 2022
medline: 17 4 2023
pubmed: 11 1 2023
entrez: 10 1 2023
Statut: ppublish

Résumé

Big data in healthcare can enable unprecedented understanding of diseases and their treatment, particularly in oncology. These data may include electronic health records, medical imaging, genomic sequencing, payor records, and data from pharmaceutical research, wearables, and medical devices. The ability to combine datasets and use data across many analyses is critical to the successful use of big data and is a concern for those who generate and use the data. Interoperability and data quality continue to be major challenges when working with different healthcare datasets. Mapping terminology across datasets, missing and incorrect data, and varying data structures make combining data an onerous and largely manual undertaking. Data privacy is another concern addressed by the Health Insurance Portability and Accountability Act, the Common Rule, and the General Data Protection Regulation. The use of big data is now included in the planning and activities of the FDA and the European Medicines Agency. The willingness of organizations to share data in a precompetitive fashion, agreements on data quality standards, and institution of universal and practical tenets on data privacy will be crucial to fully realizing the potential for big data in medicine.

Identifiants

pubmed: 36625843
pii: 712812
doi: 10.1158/0008-5472.CAN-22-1274
pmc: PMC10102837
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

1175-1182

Informations de copyright

©2023 The Authors; Published by the American Association for Cancer Research.

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Auteurs

Shawn M Sweeney (SM)

American Association for Cancer Research, Philadelphia, Pennsylvania.

Natalie Abrams (N)

Division of Cancer Prevention, Early Detection Research Network, National Cancer Institute, Rockville, Maryland.

Stacey J Adam (SJ)

Foundation for the National Institutes of Health, Bethesda, Maryland.

Sara Brenner (S)

Office of In Vitro Diagnostics, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland.

Dana E Connors (DE)

Foundation for the National Institutes of Health, Bethesda, Maryland.

Gerard J Davis (GJ)

Abbott Diagnostics Division, Abbott Laboratories, Lake Forest, Illinois.

Louis Fiore (L)

Boston University School of Medicine, Boston and New England Department of Veterans Affairs, Bedford, Massachusetts.

Susan H Gawel (SH)

Abbott Diagnostics Division, Abbott Laboratories, Lake Forest, Illinois.

Robert L Grossman (RL)

Center for Translational Data Science, The University of Chicago, Chicago, Illinois.

Sean E Hanlon (SE)

Center for Strategic Scientific Initiatives, National Cancer Institute, Bethesda, Maryland.

Karl Hsu (K)

Sanofi, Bridgewater, New Jersey.

Gary J Kelloff (GJ)

Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland.

Ilan R Kirsch (IR)

Adaptive Biotechnologies, Seattle, Washington.

Bill Louv (B)

Project Data Sphere, Morrisville, North Carolina.

Deven McGraw (D)

Ciitizen Platform at Invitae, San Francisco, California.

Frank Meng (F)

Boston University and Veterans Administration Boston Healthcare System, Boston, Massachusetts.

Daniel Milgram (D)

CCS Associates, San Jose, California.

Robert S Miller (RS)

CancerLinQ, American Society of Clinical Oncology, Alexandria, Virginia.

Emily Morgan (E)

Foundation for the National Institutes of Health, Bethesda, Maryland.

Lata Mukundan (L)

CCS Associates, San Jose, California.

Wendy S Rubinstein (WS)

Office of In Vitro Diagnostics, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland.

Liz Salmi (L)

Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.

Teilo Schaller (T)

Project Data Sphere, Morrisville, North Carolina.

George Shi (G)

Abbott Diagnostics Division, Abbott Laboratories, Lake Forest, Illinois.

Caroline C Sigman (CC)

Boston University and Veterans Administration Boston Healthcare System, Boston, Massachusetts.

Sudhir Srivastava (S)

Cancer Biomarkers Research Group, Division of Cancer Prevention, National Cancer Institute, Rockville, Maryland.

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Classifications MeSH