ArticleBMC cancer2008
The development and deployment of Common Data Elements for tissue banks for translational research in cancer - an emerging standard based approach for the Mesothelioma Virtual Tissue Bank.
Article in BMC cancer, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- REDCap and the National Mesothelioma Virtual Bank-a scalable and sustainable model for rare disease biorepositories.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Validation of deep learning natural language processing algorithm for keyword extraction from pathology reports in electronic health records.Scientific reports · 2020Article
- Composite CDE: modeling composite relationships between common data elements for representing complex clinical data.BMC medical informatics and decision making · 2020Article
- Common data elements of breast cancer for research databases: A systematic review.Journal of family medicine and primary care · 2020Review
- Workshop summary: Potential usefulness and feasibility of a US National Mesothelioma Registry.American journal of industrial medicine · 2020Article
- Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned.Briefings in bioinformatics · 2017Article
- Development of an Integrated Biospecimen Database among the Regional Biobanks in Korea.Healthcare informatics research · 2016Article
- Unifying screening processes within the PROSPR consortium: a conceptual model for breast, cervical, and colorectal cancer screening.Journal of the National Cancer Institute · 2015Article
- A call to standardize preanalytic data elements for biospecimens.Archives of pathology & laboratory medicine · 2014Article
- Automated Tools for Clinical Research Data Quality Control using NCI Common Data Elements.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2014Article
- Linkage of data from diverse data sources (LDS): a data combination model provides clinical data of corresponding specimens in biobanking information system.Journal of medical systems · 2013Article
- National Mesothelioma Virtual Bank: A Platform for Collaborative Research and Mesothelioma Biobanking Resource to Support Translational Research.Lung cancer international · 2013Article
- Application of proteomics to soft tissue sarcomas.International journal of proteomics · 2012Article
- Data standards in diabetes patient registries.Journal of diabetes science and technology · 2011Article
- Proteomic characterization of non-small cell lung cancer in a comprehensive translational thoracic oncology database.Journal of clinical bioinformatics · 2011Article
- Design and utilization of the colorectal and pancreatic neoplasm virtual biorepository: An early detection research network initiative.Journal of pathology informatics · 2010Article
- A decade of experience in the development and implementation of tissue banking informatics tools for intra and inter-institutional translational research.Journal of pathology informatics · 2010Article
- The tissue microarray OWL schema: An open-source tool for sharing tissue microarray data.Journal of pathology informatics · 2010Article
- [RD] PRISM Library: Patient Registry Item Specifications and Metadata for Rare Diseases.Journal of library metadata · 2010Article
- An informatics supported web-based data annotation and query tool to expedite translational research for head and neck malignancies.BMC cancer · 2009Article
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Authors and funding
16 authors.
Funding
Abstract
backgroundRecent advances in genomics, proteomics, and the increasing demands for biomarker validation studies have catalyzed changes in the landscape of cancer research, fueling the development of tissue banks for translational research. A result of this transformation is the need for sufficient quantities of clinically annotated and well-characterized biospecimens to support the growing needs of the cancer research community. Clinical annotation allows samples to be better matched to the research question at hand and ensures that experimental results are better understood and can be verified. To facilitate and standardize such annotation in bio-repositories, we have combined three accepted and complementary sets of data standards: the College of American Pathologists (CAP) Cancer Checklists, the protocols recommended by the Association of Directors of Anatomic and Surgical Pathology (ADASP) for pathology data, and the North American Association of Central Cancer Registry (NAACCR) elements for epidemiology, therapy and follow-up data. Combining these approaches creates a set of International Standards Organization (ISO) - compliant Common Data Elements (CDEs) for the mesothelioma tissue banking initiative supported by the National Institute for Occupational Safety and Health (NIOSH) of the Center for Disease Control and Prevention (CDC).
methodsThe purpose of the project is to develop a core set of data elements for annotating mesothelioma specimens, following standards established by the CAP checklist, ADASP cancer protocols, and the NAACCR elements. We have associated these elements with modeling architecture to enhance both syntactic and semantic interoperability. The system has a Java-based multi-tiered architecture based on Unified Modeling Language (UML).
resultsCommon Data Elements were developed using controlled vocabulary, ontology and semantic modeling methodology. The CDEs for each case are of different types: demographic, epidemiologic data, clinical history, pathology data including block level annotation, and follow-up data including treatment, recurrence and vital status. The end result of such an effort would eventually provide an increased sample set to the researchers, and makes the system interoperable between institutions.
conclusionThe CAP, ADASP and the NAACCR elements represent widely established data elements that are utilized in many cancer centers. Herein, we have shown these representations can be combined and formalized to create a core set of annotations for banked mesothelioma specimens. Because these data elements are collected as part of the normal workflow of a medical center, data sets developed on the basis of these elements can be easily implemented and maintained.
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