Evidence map›Paper›PMID 32755461›Full record

ArticleJCO clinical cancer informatics2020

Linked Entity Attribute Pair (LEAP): A Harmonization Framework for Data Pooling.

Stacy Thomas, Tara Lichtenberg, Kristen Dang, Michael Fitzsimons, Robert L Grossman, Ritika Kundra, Jessica A Lavery, Michele L Lenoue-Newton, Katherine S Panageas, Charles Sawyers and 7 more

Open access · greenAbstract read
In one paragraph

Article in JCO clinical cancer informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 46% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

17 authors at 6 institutions in 1 country.

Stacy ThomasMemorial Sloan Kettering Cancer Center, New York, NY.
Tara LichtenbergCenter for Translational Data Science, University of Chicago, Chicago, IL.
Kristen DangSage Bionetworks, Seattle, WA.
Michael FitzsimonsCenter for Translational Data Science, University of Chicago, Chicago, IL.
Robert L GrossmanCenter for Translational Data Science, University of Chicago, Chicago, IL.
Ritika KundraDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.
Jessica A LaveryDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.
Michele L Lenoue-NewtonVanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN.
Katherine S PanageasDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.
Charles SawyersHuman Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY.
Nikolaus D SchultzDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.
Sahussapont J SirintrapunDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY.
Umit TopalogluCancer Biology, Wake Forest University School of Medicine, Winston Salem, NC.
Angelica WelchInformation Systems, Memorial Sloan Kettering Cancer Center, New York, NY.
Thomas YuSage Bionetworks, Seattle, WA.
Ahmet ZehirDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY.
Stuart GardosInformation Systems, Memorial Sloan Kettering Cancer Center, New York, NY.
Memorial Sloan Kettering Cancer Center · USSage Bionetworks · USUniversity of Chicago · USUniversity of Illinois Chicago · USVanderbilt University Medical Center · USWake Forest University · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Tumor Tissue CoreP30CA012197 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Ruben A. Mesa · 1985 to 2026
$55.4M
NCI NIH HHS P30 CA008748NCI NIH HHS P30 CA012197
6 · The paper itself

Abstract

purposeAs data-sharing projects become increasingly frequent, so does the need to map data elements between multiple classification systems. A generic, robust, shareable architecture will result in increased efficiency and transparency of the mapping process, while upholding the integrity of the data. MATERIALS AND

methodsThe American Association for Cancer Research's Genomics Evidence Neoplasia Information Exchange (GENIE) collects clinical and genomic data for precision cancer medicine. As part of its commitment to open science, GENIE has partnered with the National Cancer Institute's Genomic Data Commons (GDC) as a secondary repository. After initial efforts to submit data from GENIE to GDC failed, we realized the need for a solution to allow for the iterative mapping of data elements between dynamic classification systems. We developed the Linked Entity Attribute Pair (LEAP) database framework to store and manage the term mappings used to submit data from GENIE to GDC.

resultsAfter creating and populating the LEAP framework, we identified 195 mappings from GENIE to GDC requiring remediation and observed a 28% reduction in effort to resolve these issues, as well as a reduction in inadvertent errors. These results led to a decrease in the time to map between OncoTree, the cancer type ontology used by GENIE, and International Classification of Disease for Oncology, 3rd Edition, used by GDC, from several months to less than 1 week.

conclusionThe LEAP framework provides a streamlined mapping process among various classification systems and allows for reusability so that efforts to create or adjust mappings are straightforward. The ability of the framework to track changes over time streamlines the process to map data elements across various dynamic classification systems.

Indexed as

GenomicsNeoplasmsDatabases, FactualHumansInformation DisseminationPrecision MedicineUnited States

Identifiers

PMID32755461
PMCPMC7469618
OpenAlexW3047347765

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.