Evidence map›Paper›PMID 18397527›Full record

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.

Sambit K Mohanty, Amita T Mistry, Waqas Amin, Anil V Parwani, Andrew K Pople, Linda Schmandt, Sharon B Winters, Erin Milliken, Paula Kim, Nancy B Whelan and 6 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
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  4. Review
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  8. Article
  9. A call to standardize preanalytic data elements for biospecimens.Archives of pathology & laboratory medicine · 2014
    Article
  10. 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 · 2014
    Article
  11. Article
  12. Article
  13. Application of proteomics to soft tissue sarcomas.International journal of proteomics · 2012
    Article
  14. Data standards in diabetes patient registries.Journal of diabetes science and technology · 2011
    Article
  15. Article
  16. Article
  17. Article
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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

16 authors.

Sambit K MohantyDepartment of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. mohantys2@upmc.edu
Amita T Mistry
Waqas Amin
Anil V Parwani
Andrew K Pople
Linda Schmandt
Sharon B Winters
Erin Milliken
Paula Kim
Nancy B Whelan
Ghada Farhat
Jonathan Melamed
Emanuela Taioli
Rajiv Dhir
Harvey I Pass
Michael J Becich

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR000005 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$50.8M
Mesothelioma Virtual Bank for Translational ResearchU19OH009077 · OH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BECICH, MICHAEL JOHN · 2006 to 2007
$2.0M
NCATS NIH HHS UL1 TR000005NIOSH CDC HHS 1U19OH009077-01NIOSH CDC HHS U19 OH009077
6 · The paper itself

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.

Indexed as

Medical Informatics ApplicationsMesotheliomaPleural NeoplasmsTissue BanksComputational BiologyDatabases as TopicHumansSoftwareSystems Integration

Identifiers

PMID18397527
PMCPMC2329649

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.