Evidence map›Paper›PMID 31404664›Full record

ArticleClinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association2020

Use of Narrative Concepts in Electronic Health Records to Validate Associations Between Genetic Factors and Response to Treatment of Inflammatory Bowel Diseases.

Ashwin N Ananthakrishnan, Andrew Cagan, Tianxi Cai, Vivian S Gainer, Guergana Savova, Stanley Y Shaw, Susanne Churchill, Kristin E Burke, Elizabeth W Karlson, Shawn N Murphy and 3 more

Abstract read
In one paragraph

Article in Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Ashwin N AnanthakrishnanDivision of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts. Electronic address: aananthakrishnan@mgh.harvard.edu.
Andrew CaganResearch IS and Computing, Partners HealthCare, Charlestown, Massachusetts.
Tianxi CaiDepartment of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.
Vivian S GainerResearch IS and Computing, Partners HealthCare, Charlestown, Massachusetts.
Guergana SavovaComputational Health Informatic Program, Boston Children's Hospital, Boston, Massachusetts.
Stanley Y ShawHarvard Medical School, Boston, Massachusetts; One Brave Idea, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Susanne ChurchillHarvard Medical School, Boston, Massachusetts; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts.
Kristin E BurkeDivision of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
Elizabeth W KarlsonHarvard Medical School, Boston, Massachusetts; Division of Rheumatology, Allergy and Immunology, Brigham and Women's Hospital, Boston, Massachusetts.
Shawn N MurphyHarvard Medical School, Boston, Massachusetts; Research IS and Computing, Partners HealthCare, Charlestown, Massachusetts; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.
Isaac KohaneHarvard Medical School, Boston, Massachusetts; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts.
Katherine P LiaoHarvard Medical School, Boston, Massachusetts; Division of Rheumatology, Allergy and Immunology, Brigham and Women's Hospital, Boston, Massachusetts.
Ramnik J XavierDivision of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.

Funding

Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer ResearchR35CA197449 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI XIHONG LIN · 2015 to 2026
$10.9M
NCI NIH HHS R35 CA197449
6 · The paper itself

Abstract

Crohn's disease (CD) and ulcerative colitis (UC) are heterogeneous. With availability of therapeutic classes with distinct immunologic mechanisms of action, it has become imperative to identify markers that predict likelihood of response to each drug class. However, robust development of such tools has been challenging because of need for large prospective cohorts with systematic and careful assessment of treatment response using validated indices. Most hospitals in the United States use electronic health records (EHRs) that warehouse a large amount of narrative (free-text) and codified (administrative) data generated during routine clinical care. These data have been used to construct virtual disease cohorts for epidemiologic research as well as for defining genetic basis of disease states or discrete laboratory values.

Indexed as

Colitis, UlcerativeCrohn DiseaseInflammatory Bowel DiseasesElectronic Health RecordsHumansProspective StudiesUnited States

Identifiers

PMID31404664
PMCPMC12476026

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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.