Evidence map›Paper›PMID 33971915›Full record

ArticleOrphanet journal of rare diseases2021

Rare disease patient matchmaking: development and outcomes of an internet case-finding strategy in the Undiagnosed Diseases Network.

Kimberly LeBlanc, Emily Glanton, Anna Nagy, Jorick Bater, Tala Berro, Molly A McGuinness, Courtney Studwell, Undiagnosed Diseases Network, Matthew Might

Registry-linked trialOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Orphanet journal of rare diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02450851 (Clinical and Genetic Evaluation of Patients With Undiagnosed Disorders Through the Undiagnosed Diseases Network), which is not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 22% 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.

NCT02450851 recruitingnot on this map

Clinical and Genetic Evaluation of Patients With Undiagnosed Disorders Through the Undiagnosed Diseases Network

TypeobservationalSponsorNational Human Genome Research Institute (NHGRI)Ran2015 to 2028Enrolled20,000ConditionsGenetic Disease
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Patients as Partners in Rare Disease Diagnosis and Research.The Yale journal of biology and medicine · 2021
    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

9 authors at 4 institutions in 1 country.

Kimberly LeBlancDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. kimberly_leblanc@hms.harvard.edu.ORCID http://orcid.org/0000-0003-3828-9447
Emily GlantonDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Anna NagyDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Jorick BaterDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Tala BerroDepartment of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Molly A McGuinnessBass Center for Childhood Cancer and Blood Diseases, Stanford Children's Health, Palo Alto, CA, USA.
Courtney StudwellDepartment of Pathology, Brigham and Women's Hospital, Boston, MA, USA.
Undiagnosed Diseases Network
Matthew MightHugh Kaul Precision Medicine Institute, University of Alabama at Birmingham, Birmingham, AL, USA.
Harvard University · USBrigham and Women's Hospital · USUniversity of Alabama at Birmingham · USLucile Packard Children's Hospital · US

Funding

The Harvard Clinical and Translational Science CenterUL1TR002541 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2018 to 2022
$93.0M
Coordinating Center for the Undiagnosed Diseases NetworkU01HG007530 · NHGRI · HARVARD MEDICAL SCHOOL · PI KOHANE, ISAAC S. · 2014 to 2022
$30.2M
NCATS NIH HHS UL1 TR002541NHGRI NIH HHS U01 HG007530NIH HHS U01HG007530
6 · The paper itself

Abstract

backgroundAlthough clinician, researcher, and patient resources for matchmaking exist, finding similar patients remains an obstacle for rare disease diagnosis. The goals of this study were to develop and test the effectiveness of an Internet case-finding strategy and identify factors associated with increased matching within a rare disease population.

methodsPublic web pages were created for consented participants. Matches made, time to each inquiry and match, and outcomes were recorded and analyzed using descriptive statistics. A Poisson regression model was run to identify characteristics associated with matches.

results385 participants were referred to the project and 158 had pages posted. 579 inquiries were received; 89.0% were from the general public and 24.7% resulted in a match. 81.6% of pages received at least one inquiry and 15.0% had at least one patient match. Primary symptom category of neurology, diagnosis, gene page, and photo were associated with increased matches (p ≤ 0.05).

conclusionsThis Internet case-finding strategy was of interest to patients, families, and clinicians, and similar patients were identified using this approach. Extending matchmaking efforts to the general public resulted in matches and suggests including this population in matchmaking activities can improve identification of similar patients.

Indexed as

Rare DiseasesUndiagnosed DiseasesHumansInternetPhenotypeData sharingDiagnostic odysseyGene discoveryMatchmakingRare disease

Identifiers

PMID33971915
PMCPMC8108446
OpenAlexW3160967182

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.