Evidence map›Paper›PMID 30201732›Full record

ArticleJournal of medical genetics2018

Bayesian approach to determining penetrance of pathogenic SDH variants.

Diana E Benn, Ying Zhu, Katrina A Andrews, Mathilda Wilding, Emma L Duncan, Trisha Dwight, Richard W Tothill, John Burgess, Ashley Crook, Anthony J Gill and 14 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 pooled it
6.2field-weighted citation impact, top 3% 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

35 citing papers in PubMed, 3 syntheses or guidelines pooled it, 63 citations in OpenAlex.

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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

24 authors at 8 institutions in 3 countries.

Diana E BennHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Ying ZhuHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Katrina A AndrewsDepartment of Medical Genetics, University of Cambridge and NIHR Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Centre and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, UK.
Mathilda WildingDepartment of Cancer Services, Northern Sydney Local Health District Familial Cancer Service, Royal North Shore Hospital, Saint Leonards, New South Wales, Australia.
Emma L DuncanSchool of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Trisha DwightHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Richard W TothillDepartment of Oncology, The Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
John BurgessFaculty of Medicine, University of Tasmania, Hobart, Tasmania, Australia.
Ashley CrookDepartment of Cancer Services, Northern Sydney Local Health District Familial Cancer Service, Royal North Shore Hospital, Saint Leonards, New South Wales, Australia.
Anthony J GillDepartment of Medicine, University of Sydney, Sydney, New South Wales, Australia.
Rodney J HicksDepartment of Oncology, The Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Edward KimHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Catherine LuxfordHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Helen MarfanGenetic Health Queensland, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
Anne Louise RichardsonHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Bruce RobinsonHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Arran SchlosbergDepartment of Medicine, University of Sydney, Sydney, New South Wales, Australia.
Rachel SusmanGenetic Health Queensland, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
Lyndal TaconHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Alison TrainerDepartment of Oncology, The Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Katherine TuckerDepartment of Clinical Genetics, Prince of Wales Hospital, Randwick, New South Wales, Australia.
Eamonn R MaherDepartment of Medical Genetics, University of Cambridge and NIHR Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Centre and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, UK.ORCID 0000-0002-6226-6918
Michael FieldDepartment of Cancer Services, Northern Sydney Local Health District Familial Cancer Service, Royal North Shore Hospital, Saint Leonards, New South Wales, Australia.
Roderick J Clifton-BlighHormones and Cancer, Cancer Genetics Laboratory, Kolling Institute, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
The University of Sydney · AURoyal North Shore Hospital · AUThe University of Melbourne · AURoyal Brisbane and Women's Hospital · AUUniversity of Cambridge · GBPrince of Wales Hospital · AUQueensland University of Technology · AUUniversity of Tasmania · AU

Funding

British Heart Foundation PG/12/7/29365
6 · The paper itself

Abstract

backgroundUntil recently, determining penetrance required large observational cohort studies. Data from the Exome Aggregate Consortium (ExAC) allows a Bayesian approach to calculate penetrance, in that population frequencies of pathogenic germline variants should be inversely proportional to their penetrance for disease. We tested this hypothesis using data from two cohorts for succinate dehydrogenase subunits A, B and C (

methodsTwo cohorts were 575 unrelated Australian subjects and 1240 unrelated UK subjects, respectively, with PC/PGL in whom genetic testing had been performed. Penetrance of pathogenic

resultsPathogenic

conclusionPathogenic variants in

Indexed as

Bayes TheoremGenetic Association StudiesGenetic Predisposition to DiseaseGenetic VariationPenetranceAlgorithmsAllelesAustraliaGenotypeHumansIsoenzymesModels, GeneticPhenotypeSuccinate DehydrogenaseUnited KingdomIsoenzymesSuccinate Dehydrogenaseparagangliomapathogenic variantpenetrancepheochromocytomasuccinate dehydrogenase

Identifiers

PMID30201732
PMCPMC6252366
OpenAlexW2890786943

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.