ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2015
Quality Assurance of Cancer Study Common Data Elements Using A Post-Coordination Approach.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Informatics at the Frontier of Cancer Research.Cancer research · 2025Review
- Common Data Elements for Meaningful Stroke Documentation in Routine Care and Clinical Research: Retrospective Data Analysis.JMIR medical informatics · 2021Article
- Data Quality of Chemotherapy-Induced Nausea and Vomiting Documentation.Applied clinical informatics · 2021Article
- Effect of Age on the Initiation of Biologic Agent Therapy in Patients With Inflammatory Bowel Disease: Korean Common Data Model Cohort Study.JMIR medical informatics · 2020Article
- An ontology-driven tool for structured data acquisition using Web forms.Journal of biomedical semantics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Domain-specific common data elements (CDEs) are emerging as an effective approach to standards-based clinical research data storage and retrieval. A limiting factor, however, is the lack of robust automated quality assurance (QA) tools for the CDEs in clinical study domains. The objectives of the present study are to prototype and evaluate a QA tool for the study of cancer CDEs using a post-coordination approach. The study starts by integrating the NCI caDSR CDEs and The Cancer Genome Atlas (TCGA) data dictionaries in a single Resource Description Framework (RDF) data store. We designed a compositional expression pattern based on the Data Element Concept model structure informed by ISO/IEC 11179, and developed a transformation tool that converts the pattern-based compositional expressions into the Web Ontology Language (OWL) syntax. Invoking reasoning and explanation services, we tested the system utilizing the CDEs extracted from two TCGA clinical cancer study domains. The system could automatically identify duplicate CDEs, and detect CDE modeling errors. In conclusion, compositional expressions not only enable reuse of existing ontology codes to define new domain concepts, but also provide an automated mechanism for QA of terminological annotations for CDEs.
Indexed as
Identifiers
26958201PMC4765658What 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.