Evidence map›Paper›PMID 32442341›Full record

ArticleHuman mutation2020

Mutation prevalence tables for hereditary cancer derived from multigene panel testing.

Steven N Hart, Eric C Polley, Amal Yussuf, Siddhartha Yadav, David E Goldgar, Chunling Hu, Holly LaDuca, Laura P Smith, June Fujimoto, Shuwei Li and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Human mutation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 7% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
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  15. Hereditary determinants of gynecological cancer and recommendations.Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2021
    Article
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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

12 authors at 4 institutions in 1 country.

Steven N HartDepartment of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.ORCID 0000-0001-7714-2734
Eric C PolleyDepartment of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.
Amal YussufAmbry Genetics, Aliso Viejo, California.
Siddhartha YadavDepartment of Medical Oncology, Mayo Clinic, Rochester, Minnesota.
David E GoldgarDepartment of Dermatology, University of Utah, Salt Lake City, Utah.
Chunling HuDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
Holly LaDucaAmbry Genetics, Aliso Viejo, California.
Laura P SmithAmbry Genetics, Aliso Viejo, California.
June FujimotoAmbry Genetics, Aliso Viejo, California.
Shuwei LiAmbry Genetics, Aliso Viejo, California.
Fergus J CouchDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
Jill S DolinskyAmbry Genetics, Aliso Viejo, California.
Ambry Genetics (United States) · USMayo Clinic · USMayo Clinic in Florida · USUniversity of Utah · US

Funding

The Role of CHFR in Tumorigenesis and Paclitaxel-Sensitivity in Breast CancerP50CA116201 · NCI · MAYO CLINIC ROCHESTER · PI PETER C LUCAS · 2005 to 2026
$49.9M
NCI NIH HHS P50 CA116201
6 · The paper itself

Abstract

Multigene panel testing for cancer predisposition mutations is becoming routine in clinical care. However, the gene content of panels offered by testing laboratories vary significantly, and data on mutation detection rates by gene and by the panel is limited, causing confusion among clinicians on which test to order. Using results from 147,994 multigene panel tests conducted at Ambry Genetics, we built an interactive prevalence tool to explore how differences in ethnicity, age of onset, and personal and family history of different cancers affect the prevalence of pathogenic mutations in 31 cancer predisposition genes, across various clinically available hereditary cancer gene panels. Over 13,000 mutation carriers were identified in this high-risk population. Most were non-Hispanic white (74%, n = 109,537), but also Black (n  = 10,875), Ashkenazi Jewish (n  = 10,464), Hispanic (n  = 10,028), and Asian (n  = 7,090). The most prevalent cancer types were breast (50%), ovarian (6.6%), and colorectal (4.7%), which is expected based on genetic testing guidelines and clinician referral for testing. The Hereditary Cancer Multi-Gene Panel Prevalence Tool presented here can be used to provide insight into the prevalence of mutations on a per-gene and per-multigene panel basis, while conditioning on multiple custom phenotypic variables to include race and cancer type.

Indexed as

Genetic Predisposition to DiseaseGenetic TestingHumansInternetMutationNeoplastic Syndromes, HereditarySoftwareUser-Computer InterfaceBRCA1BRCA2cancer mutation prevalencecarriermutation risk

Identifiers

PMID32442341
PMCPMC7418063
OpenAlexW3027442050

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.