A scoping review of OMOP CDM adoption for cancer research using real world data

Liwei Wang; Andrew Wen; Sunyang Fu; Xiaoyang Ruan; Ming Huang; Rui Li; Qiuhao Lu; Heather Lyu; Andrew E. Williams; Hongfang Liu

doi:10.1038/s41746-025-01581-7

npj Digital Medicine (Apr 2025)

A scoping review of OMOP CDM adoption for cancer research using real world data

Liwei Wang,
Andrew Wen,
Sunyang Fu,
Xiaoyang Ruan,
Ming Huang,
Rui Li,
Qiuhao Lu,
Heather Lyu,
Andrew E. Williams,
Hongfang Liu

Affiliations

Liwei Wang: McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston
Andrew Wen: McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston
Sunyang Fu: McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston
Xiaoyang Ruan: McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston
Ming Huang: McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston
Rui Li: McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston
Qiuhao Lu: McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston
Heather Lyu: Department of Surgical Oncology, Division of Surgery, The University of Texas MD Anderson Cancer Center
Andrew E. Williams: Clinical and Translational Science Institute, Tufts Medical Center
Hongfang Liu: McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston

DOI: https://doi.org/10.1038/s41746-025-01581-7
Journal volume & issue: Vol. 8, no. 1
pp. 1 – 11

Abstract

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Abstract The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) supports large-scale research by enabling distributed network analyses. However, the breadth of its adoption in cancer research is not well understood. We conducted a scoping review to describe the adoption of the OMOP CDM in cancer research. A total of 49 unique articles were included in the review, with 30 on the data analysis theme, and 20 on the infrastructure theme. This review highlighted that while the OMOP CDM ecosystem has enabled successful data support for cancer research, particularly for collaborative studies, ongoing model development and iterative improvement remain needed to fulfill additional research data needs. Expanding disease sites, specifically for rare cancers, integrating more diverse types of data sources, improving data quality, adopting advanced analytics methodology, and increasing multisite evaluations serve as important opportunities to facilitate secondary usage of observational data in future cancer research.

Published in npj Digital Medicine

ISSN: 2398-6352 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics
Website: https://www.nature.com/npjdigitalmed/

About the journal