Evidence map›Paper›PMID 42317849›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2026

Completeness of Common Data Elements for Breast Cancer Clinical Trials in Observational Databases.

Adit Anand, Yilu Fang, Chunhua Weng, Karthik Natarajan

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PubMed Full text at PMC
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Adit AnandDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.
Yilu FangDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.
Chunhua WengDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.
Karthik NatarajanDepartment of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical trials serve as a gold standard for data that shapes the healthcare landscape in oncology, but variance in clinical trial eligibility criteria presents challenges for using the data in downstream applications. Identifying common data elements (CDEs) present in cancer trials' eligibility criteria is critical to achieve standardized representations of healthcare data and thus develop trial recruitment tools that generalize to oncology. In this study, we curate a set of CDEs contained in the eligibility criteria of breast cancer clinical trials and evaluate their completeness across different observational databases represented in the Observational Medical Outcomes Partnership (OMOP) Common Data Model. We show that between databases, CDEs are captured with differing levels of completeness across OMOP domains and that there is discordance between the frequency of eligibility criteria CDEs and their completeness in observational databases, which characterizes these databases' utility for subsequent oncology trial matching efforts.

Identifiers

PMID42317849
PMCPMC13274301

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.