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Consensus Statement on next-generation-sequencing-based diagnostic testing of hereditary phaeochromocytomas and paragangliomas

Overview of attention for article published in Nature Reviews Endocrinology, November 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

news
1 news outlet
twitter
47 tweeters
patent
1 patent
facebook
4 Facebook pages

Citations

dimensions_citation
133 Dimensions

Readers on

mendeley
96 Mendeley
Title
Consensus Statement on next-generation-sequencing-based diagnostic testing of hereditary phaeochromocytomas and paragangliomas
Published in
Nature Reviews Endocrinology, November 2016
DOI 10.1038/nrendo.2016.185
Pubmed ID
Authors

Rodrigo A. Toledo, Nelly Burnichon, Alberto Cascon, Diana E. Benn, Jean-Pierre Bayley, Jenny Welander, Carli M. Tops, Helen Firth, Trish Dwight, Tonino Ercolino, Massimo Mannelli, Giuseppe Opocher, Roderick Clifton-Bligh, Oliver Gimm, Eamonn R. Maher, Mercedes Robledo, Anne-Paule Gimenez-Roqueplo, Patricia L. M. Dahia

Abstract

Phaeochromocytomas and paragangliomas (PPGLs) are neural-crest-derived tumours of the sympathetic or parasympathetic nervous system that are often inherited and are genetically heterogeneous. Genetic testing is recommended for patients with these tumours and for family members of patients with hereditary forms of PPGLs. Due to the large number of susceptibility genes implicated in the diagnosis of inherited PPGLs, next-generation sequencing (NGS) technology is ideally suited for carrying out genetic screening of these individuals. This Consensus Statement, formulated by a study group comprised of experts in the field, proposes specific recommendations for the use of diagnostic NGS in hereditary PPGLs. In brief, the study group recommends target gene panels for screening of germ line DNA, technical adaptations to address different modes of disease transmission, orthogonal validation of NGS findings, standardized classification of variant pathogenicity and uniform reporting of the findings. The use of supplementary assays, to aid in the interpretation of the results, and sequencing of tumour DNA, for identification of somatic mutations, is encouraged. In addition, the study group launches an initiative to develop a gene-centric curated database of PPGL variants, with annual re-evaluation of variants of unknown significance by an expert group for purposes of reclassification and clinical guidance.

Twitter Demographics

The data shown below were collected from the profiles of 47 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 1%
Unknown 95 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 15%
Researcher 13 14%
Other 13 14%
Student > Bachelor 10 10%
Student > Postgraduate 9 9%
Other 23 24%
Unknown 14 15%
Readers by discipline Count As %
Medicine and Dentistry 32 33%
Biochemistry, Genetics and Molecular Biology 24 25%
Agricultural and Biological Sciences 5 5%
Engineering 3 3%
Psychology 2 2%
Other 11 11%
Unknown 19 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 39. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 May 2020.
All research outputs
#639,861
of 17,362,547 outputs
Outputs from Nature Reviews Endocrinology
#204
of 2,005 outputs
Outputs of similar age
#20,812
of 398,069 outputs
Outputs of similar age from Nature Reviews Endocrinology
#10
of 56 outputs
Altmetric has tracked 17,362,547 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,005 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.7. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 398,069 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.