ArticleJournal of biomedical informatics2021
A knowledge base of clinical trial eligibility criteria.
Article in Journal of biomedical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- OMOP CDM Can Facilitate Data-Driven Studies for Cancer Prediction: A Systematic Review.International journal of molecular sciences · 2022Pooled it
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- Completeness of Common Data Elements for Breast Cancer Clinical Trials in Observational Databases.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Review
- Natural Language Processing in Support of Evidence-based Medicine: A Scoping Review.Findings of ACL. ACL · 2025Article
- Fast and effective assessment for individuals with special needs form optimization and prediction models.BMC psychology · 2025Article
- Reusing data from HL7 CDA-based shared EHR systems for clinical trial conduct: a method for analyzing feasibility.BMC medical informatics and decision making · 2025Article
- Artificial intelligence for optimizing recruitment and retention in clinical trials: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Clinical Research Informatics: a Decade-in-Review.Yearbook of medical informatics · 2024Review
- Article
- Review
- Evaluation of Eligibility Criteria Relevance for the Purpose of IT-Supported Trial Recruitment: Descriptive Quantitative Analysis.JMIR formative research · 2024Article
- Recommending Clinical Trials for Online Patient Cases using Artificial Intelligence.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- A review of research on eligibility criteria for clinical trials.Clinical and experimental medicine · 2023Review
- A data-driven approach to optimizing clinical study eligibility criteria.Journal of biomedical informatics · 2023Article
- Clinical research staff perceptions on a natural language processing-driven tool for eligibility prescreening: An iterative usability assessment.International journal of medical informatics · 2023Article
- Artificial Intelligence Applied to clinical trials: opportunities and challenges.Health and technology · 2023Review
- Text Classification of Cancer Clinical Trial Eligibility Criteria.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing.Yearbook of medical informatics · 2022Article
- Clinical Research Informatics.Yearbook of medical informatics · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectiveWe present the Clinical Trial Knowledge Base, a regularly updated knowledge base of discrete clinical trial eligibility criteria equipped with a web-based user interface for querying and aggregate analysis of common eligibility criteria. MATERIALS AND
methodsWe used a natural language processing (NLP) tool named Criteria2Query (Yuan et al., 2019) to transform free text clinical trial eligibility criteria from ClinicalTrials.gov into discrete criteria concepts and attributes encoded using the widely adopted Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and stored in a relational SQL database. A web application accessible via RESTful APIs was implemented to enable queries and visual aggregate analyses. We demonstrate CTKB's potential role in EHR phenotype knowledge engineering using ten validated phenotyping algorithms.
resultsAt the time of writing, CTKB contained 87,504 distinctive OMOP CDM standard concepts, including Condition (47.82%), Drug (23.01%), Procedure (13.73%), Measurement (24.70%) and Observation (5.28%), with 34.78% for inclusion criteria and 65.22% for exclusion criteria, extracted from 352,110 clinical trials. The average hit rate of criteria concepts in eMERGE phenotype algorithms is 77.56%.
conclusionCTKB is a novel comprehensive knowledge base of discrete eligibility criteria concepts with the potential to enable knowledge engineering for clinical trial cohort definition, clinical trial population representativeness assessment, electronical phenotyping, and data gap analyses for using electronic health records to support clinical trial recruitment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.