Evidence map›Paper›PMID 31487201›Full record

ArticleJCO clinical cancer informatics2019

Clinical Molecular Marker Testing Data Capture to Promote Precision Medicine Research Within the Cancer Research Network.

Andrea N Burnett-Hartman, Natalia Udaltsova, Lawrence H Kushi, Christine Neslund-Dudas, Alanna Kulchak Rahm, Pamala A Pawloski, Douglas A Corley, Sarah Knerr, Heather Spencer Feigelson, Jessica Ezzell Hunter and 6 more

Open access · greenAbstract read
In one paragraph

Article in JCO clinical cancer informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 50% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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 at 8 institutions in 1 country.

Andrea N Burnett-HartmanInstitute for Health Research, Kaiser Permanente Colorado, Aurora, CO.
Natalia UdaltsovaKaiser Permanente Northern California, Oakland, CA.
Lawrence H KushiKaiser Permanente Northern California, Oakland, CA.
Christine Neslund-DudasHenry Ford Health System, Detroit, MI.
Alanna Kulchak RahmGenomic Medicine Institute, Geisinger, Danville, PA.
Pamala A PawloskiHealthPartners Institute, Bloomington, MN.
Douglas A CorleyKaiser Permanente Northern California, Oakland, CA.
Sarah KnerrUniversity of Washington and Kaiser Permanente Washington Health Research Institute, Seattle, WA.
Heather Spencer FeigelsonInstitute for Health Research, Kaiser Permanente Colorado, Aurora, CO.
Jessica Ezzell HunterKaiser Permanente Northwest, Portland, OR.
David C TabanoInstitute for Health Research, Kaiser Permanente Colorado, Aurora, CO.
Mara M EpsteinUniversity of Massachusetts Medical School, Worcester, MA.
Stacey A HondaKaiser Permanente Hawaii, Honolulu, HI.
Monica Ter-MinassianKaiser Permanente Mid-Atlantic States, Rockville, MD.
Julie A LynchDepartment of Veterans Affairs Salt Lake City Health System, Salt Lake City, UT.
Christine Y LuHarvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA.
Kaiser Permanente · USResearch Network (United States) · USHarvard Pilgrim Health Care · USHealthPartners · USHenry Ford Health System · USKaiser Permanente Washington Health Research Institute · USUniversity of Massachusetts Chan Medical School · USVA Salt Lake City Healthcare System · US

Funding

CRN4: Cancer Research Resources & Collaboration in Integrated Health Care SystemsU24CA171524 · NCI · KAISER FOUNDATION RESEARCH INSTITUTE · PI KUSHI, LAWRENCE H · 2012 to 2016
$16.0M
University of Massachusetts Center for Clinical and Translational ScienceTL1TR001454 · NCATS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI LEWIS, BRIAN C · 2015 to 2024
$3.6M
NCATS NIH HHS TL1 TR001454NCI NIH HHS U24 CA171524
6 · The paper itself

Abstract

purposeTo evaluate health care systems for the availability of population-level data on the frequency of use and results of clinical molecular marker tests to inform precision cancer care.

methodsWe assessed cancer-related molecular marker test data availability across 12 US health care systems in the Cancer Research Network. Overall, these systems provide care to a diverse population of more than 12 million people in the United States. We performed qualitative analyses of test data availability for five blood-based protein, nine germline, and 14 tissue-based tumor marker tests in each health care system's electronic health record and tumor registry using key informants, test code lists, and manual review of data types and output. We then performed quantitative analyses to estimate the proportion of patients with cancer with test utilization data and results for specific molecular marker tests.

resultsHealth systems were able to systematically capture population-level data on all five blood protein markers, six of 14 tissue-based tumor markers, and none of the nine germline markers. Successful, systematic data capture was achievable for tests with electronic data feeds for test results (blood protein markers) or through prior manual abstraction by tumor registrars (select tumor-based markers). For test results stored in scanned image files (particularly germline and tumor marker tests), information on which test was performed and test results was not readily accessible in an electronic format.

conclusionEven in health care systems with sophisticated electronic health records, there were few codified data elements available for evaluating precision cancer medicine test use and results at the population level. Health care organizations should establish standards for electronic reporting of precision medicine tests to expedite cancer research and facilitate the implementation of precision medicine approaches.

Indexed as

Electronic Health RecordsBiomarkers, TumorData CollectionDelivery of Health CareDisease ManagementHumansLiquid BiopsyMolecular Diagnostic TechniquesNeoplasmsPrecision MedicinePublic Health SurveillanceResearchUnited StatesBiomarkers, Tumor

Identifiers

PMID31487201
PMCPMC6874000
OpenAlexW2971804126

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.