Evidence map›Paper›PMID 29273109›Full record

ArticleThe journal of investigative dermatology. Symposium proceedings2018

Big Data Reveal Insights into Alopecia Areata Comorbidities.

Chean Ping Lim, Rachel K Severin, Lynn Petukhova

Abstract read
In one paragraph

Article in The journal of investigative dermatology. Symposium proceedings, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
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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

3 authors.

Chean Ping LimDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.
Rachel K SeverinDepartment of Dermatology, College of Physicians and Surgeons, Columbia University, New York, New York, USA.
Lynn PetukhovaDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA; Department of Dermatology, College of Physicians and Surgeons, Columbia University, New York, New York, USA. Electronic address: lynn.petukhova@columbia.edu.

Funding

OMOP information model for eMERGE phenotypingU01HG008680 · NHGRI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Wendy K Chung, GEORGE M HRIPCSAK · 2015 to 2026
$13.3M
Project 1: Translational Science of Alopecia AreataP50AR070588 · NIAMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CHRISTIANO, ANGELA M · 2016 to 2021
$8.0M
Translational and Precision Medicine Resources Core (TRAP)P30AR069632 · NIAMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BICKERS, DAVID RINSEY · 2016 to 2020
$3.9M
Research conference titled "Building and Crossing the Translational Bridge in Alopecia Areata"R13AR071266 · NIAMS · NATIONAL ALOPECIA AREATA FOUNDATION · PI CHRISTIANO, ANGELA M · 2016 to 2016
$15k
NHGRI NIH HHS U01 HG008680NIAMS NIH HHS P30 AR069632NIAMS NIH HHS P50 AR070588NIAMS NIH HHS R13 AR071266
6 · The paper itself

Abstract

Autoimmune diseases create a substantial burden of disease, and alopecia areata is among the more prevalent forms. Comorbidities are medical conditions that tend to occur together and may provide etiologic insights, suggest novel therapeutic strategies, and help patients and family members understand the risk of other health conditions. It is well established that having one autoimmune disease increases risk for others because of an underlying shared biology. Precision medicine initiatives are creating vast amounts of data that allow us to efficiently identify comorbidities. A survey across various datasets suggests that patients with autoimmune disease, and patients with alopecia areata in particular, may have comorbid neuropsychiatric and metabolic conditions.

Indexed as

Alopecia AreataAnimalsAutoimmune DiseasesBig DataComorbidityFemaleHumansMaleMental DisordersMetabolic DiseasesMiceRisk Factors

Identifiers

PMID29273109
PMCPMC5862393

What OpenQuestion holds

Textmetadata
LicenceTDM
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.