Evidence map›Paper›PMID 17149500›Full record

ArticleMethods of information in medicine2006

The Common Data Elements for cancer research: remarks on functions and structure.

P M Nadkarni, C A Brandt

Abstract read
In one paragraph

Article in Methods of information in medicine, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. QLBMC medical informatics and decision making · 2019
    Article
  13. Article
  14. Review
  15. Unleashing the value of Common Data Elements through the CEDAR Workbench.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019
    Article
  16. Recommendations for Improving the Quality of Rare Disease Registries.International journal of environmental research and public health · 2018
    Article
  17. Article
  18. Article
  19. An exploratory study using an openEHR 2-level modeling approach to represent common data elements.Journal of the American Medical Informatics Association : JAMIA · 2016
    Article
  20. Article
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

2 authors.

P M NadkarniCenter for Medical Informatics, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520-8009, USA. Prakash.Nadkarni@yale.edu
C A Brandt

Funding

DELIVERY OF THE CGN INFORMATION RESOURCE DATABASEU01CA078266 · NCI · YALE UNIVERSITY · PI NADKARNI, PRAKASH M. · 1998 to 2006
$1.9M
DESIGN AND IMPLEMENTATION OF PHARMACOGENETIC DATABASEU01ES010867 · NIEHS · YALE UNIVERSITY · PI NADKARNI, PRAKASH M. · 2000 to 2002
$1.4M
ROBUST QUERY OF HETEROGENEOUS CLINICAL DATABASESR01LM006843 · NLM · YALE UNIVERSITY · PI NADKARNI, PRAKASH M. · 2000 to 2002
$878k
VOCABULARY MANAGEMENT FOR CLINICAL RESEARCH DATABASESK23RR016042 · NCRR · YALE UNIVERSITY · PI BRANDT, CYNTHIA ANN · 2001 to 2005
$605k
NCI NIH HHS U01 CA078266NCI NIH HHS U01 CA78266NCRR NIH HHS K23 RR016042NCRR NIH HHS K23 RR16042NIEHS NIH HHS U01 ES010867NIEHS NIH HHS U01 ES10867NLM NIH HHS R01 LM006843NLM NIH HHS R01 LM06843
6 · The paper itself

Abstract

objectivesThe National Cancer Institute (NCI) has developed the Common Data Elements (CDE) to serve as a controlled vocabulary of data descriptors for cancer research, to facilitate data interchange and inter-operability between cancer research centers. We evaluated CDE's structure to see whether it could represent the elements necessary to support its intended purpose, and whether it could prevent errors and inconsistencies from being accidentally introduced. We also performed automated checks for certain types of content errors that provided a rough measure of curation quality.

methodsEvaluation was performed on CDE content downloaded via the NCI's CDE Browser, and transformed into relational database form. Evaluation was performed under three categories: 1) compatibility with the ISO/IEC 11179 metadata model, on which CDE structure is based, 2) features necessary for controlled vocabulary support, and 3) support for a stated NCI goal, set up of data collection forms for cancer research.

resultsVarious limitations were identified both with respect to content (inconsistency, insufficient definition of elements, redundancy) as well as structure--particularly the need for term and relationship support, as well as the need for metadata supporting the explicit representation of electronic forms that utilize sets of common data elements.

conclusionsWhile there are numerous positive aspects to the CDE effort, there is considerable opportunity for improvement. Our recommendations include review of existing content by diverse experts in the cancer community; integration with the NCI thesaurus to take advantage of the latter's links to nationally used controlled vocabularies, and various schema enhancements required for electronic form support.

Indexed as

Cancer Care FacilitiesInterdisciplinary CommunicationNeoplasmsVocabulary, ControlledBiomedical ResearchDatabase Management SystemsHumansNational Institutes of Health (U.S.)Pilot ProjectsRegistriesSoftwareUnited States

Identifiers

PMID17149500
PMCPMC2980785

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.