Evidence map›Paper›PMID 32170000›Full record

ArticleJournal of medical genetics2020

Cancer Variant Interpretation Group UK (CanVIG-UK): an exemplar national subspecialty multidisciplinary network.

Alice Garrett, Alison Callaway, Miranda Durkie, Cankut Cubuk, Mary Alikian, George J Burghel, Rachel Robinson, Louise Izatt, Sabrina Talukdar, Lucy Side and 16 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of medical genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
5.8field-weighted citation impact, top 4% 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

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. UK recommendations forJournal of medical genetics · 2023
    Article
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

26 authors at 16 institutions in 1 country.

Alice Garrett *Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK.ORCID 0000-0001-8942-283X
Alison Callaway *Wessex Regional Genetics Laboratory, Salisbury Hospital NHS Foundation Trust, Salisbury, UK.
Miranda Durkie *Sheffield Diagnostic Genetics Service, Sheffield Children's NHS Foundation Trust, Sheffield, UK.
Cankut CubukDivision of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK.
Mary AlikianDivision of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK.
George J BurghelManchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University NHS Foundation Trust, Manchester, UK.ORCID 0000-0001-9360-8194
Rachel RobinsonYorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Louise IzattDepartment of Clinical Genetics, Guy's and Saint Thomas' NHS Foundation Trust, London, UK.
Sabrina TalukdarDepartment of Clinical Genetics, Saint George's University Hospitals NHS Foundation Trust, London, UK.
Lucy SideWessex Clinical Genetics Service, Princess Anne Hospital, Southampton, UK.
Treena CranstonOxford Molecular Genetics Laboratory, Churchill Hospital, Oxford, UK.
Sheila Palmer-SmithInstitute of Medical Genetics, University Hospital of Wales, Cardiff, UK.
Diana BaralleFaculty of Medicine, University of Southampton, Southampton, UK.
Ian R BerryYorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Leeds, UK.ORCID 0000-0002-9710-4724
James DrummondEast Anglian Medical Genetics Service, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Andrew J WallaceManchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University NHS Foundation Trust, Manchester, UK.
Gail NorburyRegional Genetics Service, Guy's and Saint Thomas' NHS Foundation Trust, London, UK.
Diana M EcclesFaculty of Medicine, University of Southampton, Southampton, UK.ORCID 0000-0002-9935-3169
Sian EllardDepartment of Molecular Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK.
Fiona LallooManchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University NHS Foundation Trust, Manchester, UK.
D Gareth EvansManchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University NHS Foundation Trust, Manchester, UK.ORCID 0000-0002-8482-5784
Emma WoodwardManchester Centre for Genomic Medicine and NW Laboratory Genetics Hub, Manchester University NHS Foundation Trust, Manchester, UK.
Marc TischkowitzDepartment of Medical Genetics, National Institute for Health, Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK.
Helen HansonDivision of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK.
Clare TurnbullDivision of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK clare.turnbull@icr.ac.uk.ORCID 0000-0002-1734-5772
CanVIG-UK
Institute of Cancer Research · GBManchester University NHS Foundation Trust · GBGuy's and St Thomas' NHS Foundation Trust · GBLeeds Teaching Hospitals NHS Trust · GBUniversity of Manchester · GBUniversity of Southampton · GBCambridge University Hospitals NHS Foundation Trust · GBChurchill Hospital · GBPrincess Anne Hospital · GBRoyal Devon & Exeter NHS Foundation Trust · GBRoyal Marsden NHS Foundation Trust · GBSheffield Children's NHS Foundation Trust · GBSt George’s University Hospitals NHS Foundation Trust · GBUniversity Hospital of Wales · GBUniversity of Cambridge · GBWessex Regional Genetics Laboratory · GB

Funding

Cancer Research UK 27223Cancer Research UK C61296/A27223Department of Health RP-2016-07-011
6 · The paper itself

Abstract

Advances in technology have led to a massive expansion in the capacity for genomic analysis, with a commensurate fall in costs. The clinical indications for genomic testing have evolved markedly; the volume of clinical sequencing has increased dramatically; and the range of clinical professionals involved in the process has broadened. There is general acceptance that our early dichotomous paradigms of variants being pathogenic-high risk and benign-no risk are overly simplistic. There is increasing recognition that the clinical interpretation of genomic data requires significant expertise in disease-gene-variant associations specific to each disease area. Inaccurate interpretation can lead to clinical mismanagement, inconsistent information within families and misdirection of resources. It is for this reason that 'national subspecialist multidisciplinary meetings' (MDMs) for genomic interpretation have been articulated as key for the new NHS Genomic Medicine Service, of which Cancer Variant Interpretation Group UK (CanVIG-UK) is an early exemplar. CanVIG-UK was established in 2017 and now has >100 UK members, including at least one clinical diagnostic scientist and one clinical cancer geneticist from each of the 25 regional molecular genetics laboratories of the UK and Ireland. Through CanVIG-UK, we have established national consensus around variant interpretation for cancer susceptibility genes via monthly national teleconferenced MDMs and collaborative data sharing using a secure online portal. We describe here the activities of CanVIG-UK, including exemplar outputs and feedback from the membership.

Indexed as

Genetic TestingGenomicsFemaleGenetic VariationHigh-Throughput Nucleotide SequencingHumansIrelandMaleNeoplasmsUnited Kingdomclinical geneticsgeneticsguidelinesmolecular geneticsoncology

Identifiers

PMID32170000
PMCPMC7691806
OpenAlexW3006340694

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.