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Updated: Jun 20, 2026
07:41
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Completeness of Common Data Elements for Breast Cancer Clinical Trials in Observational Databases.
Adit Anand1, Yilu Fang1, Chunhua Weng1
1Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.
Summary
Standardizing common data elements (CDEs) in cancer clinical trial eligibility criteria is crucial. However, their completeness varies across observational databases, impacting oncology trial matching efforts.
Area of Science:
- Oncology
- Clinical Informatics
- Data Standardization
Background:
- Clinical trials are vital for oncology research, but inconsistent eligibility criteria hinder data utilization.
- Standardized data is needed for effective oncology trial recruitment tools.
Purpose of the Study:
- To curate common data elements (CDEs) from breast cancer clinical trial eligibility criteria.
- To evaluate the completeness of these CDEs across observational databases within the OMOP Common Data Model.
Main Methods:
- Curated a set of CDEs from breast cancer trial eligibility criteria.
- Assessed CDE completeness across different OMOP databases.
- Analyzed the frequency and completeness of CDEs in relation to database utility for trial matching.
Main Results:
- CDEs are captured with varying completeness across OMOP domains and databases.
- There is a discordance between the frequency of CDEs and their completeness.
- Database utility for oncology trial matching is characterized by this discordance.
Conclusions:
- Inconsistent CDE capture across databases limits their utility for oncology trial matching.
- Standardization efforts are needed to improve data completeness and facilitate trial recruitment.
- Further research should focus on harmonizing data representation for better downstream applications in oncology.
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