Evidence map›Paper›PMID 33560999›Full record

ReviewDiabetes care2020

Monogenic Diabetes: From Genetic Insights to Population-Based Precision in Care. Reflections From a

Matthew C Riddle, Louis H Philipson, Stephen S Rich, Annelie Carlsson, Paul W Franks, Siri Atma W Greeley, John J Nolan, Ewan R Pearson, Philip S Zeitler, Andrew T Hattersley

Open access · greenAbstract readReview
In one paragraph

Review in Diabetes care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 2 pooled it
12.7field-weighted citation impact, top 1% 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

70 citing papers in PubMed, 2 syntheses or guidelines pooled it, 99 citations in OpenAlex.

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10 more citing papers are in PubMed but not listed here.

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

10 authors at 9 institutions in 4 countries.

Matthew C RiddleDivision of Endocrinology, Diabetes, & Clinical Nutrition, Oregon Health & Science University, Portland, OR riddlem@ohsu.edu.ORCID 0000-0003-1169-3036
Louis H PhilipsonSection of Adult and Pediatric Endocrinology, Diabetes, and Metabolism, Department of Medicine, The University of Chicago, Chicago, IL.
Stephen S RichCenter for Public Health Genomics, University of Virginia, Charlottesville, VA.ORCID 0000-0003-3872-7793
Annelie CarlssonDepartment of Clinical Sciences, Lund University/Clinical Research Centre, Skåne University Hospital, Lund, Sweden.
Paul W FranksHarvard T.H. Chan School of Public Health, Boston, MA.ORCID 0000-0002-0520-7604
Siri Atma W GreeleySection of Adult and Pediatric Endocrinology, Diabetes, and Metabolism, Department of Medicine, The University of Chicago, Chicago, IL.ORCID 0000-0002-0741-3567
John J NolanSchool of Medicine, Trinity College Dublin, Dublin, Ireland.ORCID 0000-0003-3648-1590
Ewan R PearsonDivision of Population Health and Genomics, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, Scotland, U.K.ORCID 0000-0001-9237-8585
Philip S ZeitlerChildren's Hospital Colorado and University of Colorado School of Medicine, Aurora, CO.
Andrew T HattersleyInstitute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0001-5620-473X
University of Chicago · USChildren's Hospital Colorado · USHarvard University · USLund University · SENinewells Hospital · GBOregon Health & Science University · USTrinity College Dublin · IEUniversity of Exeter · GBUniversity of Virginia · US

Funding

Pilot and Feasibility ProgramP30DK020595 · NIDDK · UNIVERSITY OF CHICAGO · PI Raghavendra G Mirmira · 2013 to 2026
$20.9M
Monogenic Diabetes: Next Generation Diagnosis, Treatment and ComplicationsR01DK104942 · NIDDK · UNIVERSITY OF CHICAGO · PI GREELEY, SIRI ATMA W., PHILIPSON, LOUIS H. · 2016 to 2024
$4.7M
NIDDK NIH HHS P30 DK020595NIDDK NIH HHS R01 DK104942Wellcome Trust 102820/Z/13/Z
6 · The paper itself

Abstract

Individualization of therapy based on a person's specific type of diabetes is one key element of a "precision medicine" approach to diabetes care. However, applying such an approach remains difficult because of barriers such as disease heterogeneity, difficulties in accurately diagnosing different types of diabetes, multiple genetic influences, incomplete understanding of pathophysiology, limitations of current therapies, and environmental, social, and psychological factors. Monogenic diabetes, for which single gene mutations are causal, is the category most suited to a precision approach. The pathophysiological mechanisms of monogenic diabetes are understood better than those of any other form of diabetes. Thus, this category offers the advantage of accurate diagnosis of nonoverlapping etiological subgroups for which specific interventions can be applied. Although representing a small proportion of all diabetes cases, monogenic forms present an opportunity to demonstrate the feasibility of precision medicine strategies. In June 2019, the editors of

Indexed as

Precision MedicineCongresses as TopicDiabetes MellitusEndocrinologyExpert TestimonyHumansPatient-Centered Care

Identifiers

PMID33560999
PMCPMC8162450
OpenAlexW3106034474

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.