↓ Skip to main content

Development and validation of a new algorithm for the reclassification of genetic variants identified in the BRCA1 and BRCA2 genes

Overview of attention for article published in Breast Cancer Research and Treatment, August 2014
Altmetric Badge

About this Attention Score

  • In the top 25% 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 (98th percentile)

Mentioned by

news
2 news outlets
twitter
2 X users
patent
2 patents
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
55 Mendeley
Title
Development and validation of a new algorithm for the reclassification of genetic variants identified in the BRCA1 and BRCA2 genes
Published in
Breast Cancer Research and Treatment, August 2014
DOI 10.1007/s10549-014-3065-9
Pubmed ID
Authors

Dmitry Pruss, Brian Morris, Elisha Hughes, Julie M. Eggington, Lisa Esterling, Brandon S. Robinson, Aric van Kan, Priscilla H. Fernandes, Benjamin B. Roa, Alexander Gutin, Richard J. Wenstrup, Karla R. Bowles

Abstract

BRCA1 and BRCA2 sequencing analysis detects variants of uncertain clinical significance in approximately 2 % of patients undergoing clinical diagnostic testing in our laboratory. The reclassification of these variants into either a pathogenic or benign clinical interpretation is critical for improved patient management. We developed a statistical variant reclassification tool based on the premise that probands with disease-causing mutations are expected to have more severe personal and family histories than those having benign variants. The algorithm was validated using simulated variants based on approximately 145,000 probands, as well as 286 BRCA1 and 303 BRCA2 true variants. Positive and negative predictive values of ≥99 % were obtained for each gene. Although the history weighting algorithm was not designed to detect alleles of lower penetrance, analysis of the hypomorphic mutations c.5096G>A (p.Arg1699Gln; BRCA1) and c.7878G>C (p.Trp2626Cys; BRCA2) indicated that the history weighting algorithm is able to identify some lower penetrance alleles. The history weighting algorithm is a powerful tool that accurately assigns actionable clinical classifications to variants of uncertain clinical significance. While being developed for reclassification of BRCA1 and BRCA2 variants, the history weighting algorithm is expected to be applicable to other cancer- and non-cancer-related genes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 54 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 22%
Student > Ph. D. Student 10 18%
Student > Bachelor 6 11%
Student > Doctoral Student 4 7%
Student > Master 4 7%
Other 9 16%
Unknown 10 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 27%
Biochemistry, Genetics and Molecular Biology 13 24%
Medicine and Dentistry 7 13%
Nursing and Health Professions 1 2%
Business, Management and Accounting 1 2%
Other 5 9%
Unknown 13 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 01 November 2022.
All research outputs
#1,225,807
of 23,016,919 outputs
Outputs from Breast Cancer Research and Treatment
#146
of 4,681 outputs
Outputs of similar age
#13,171
of 230,438 outputs
Outputs of similar age from Breast Cancer Research and Treatment
#1
of 51 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,681 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has done particularly well, scoring higher than 96% 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 230,438 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 51 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.