Evidence map›Paper›PMID 31584660›Full record

ArticleJournal of the National Cancer Institute2020

Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results.

Robert J MacInnis, Yuyan Liao, Julia A Knight, Roger L Milne, Alice S Whittemore, Wendy K Chung, Nicole Leoce, Richard Buchsbaum, Nur Zeinomar, Gillian S Dite and 16 more

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

Article in Journal of the National Cancer Institute, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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 10 institutions in 3 countries.

Robert J MacInnisCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
Yuyan LiaoDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York.
Julia A KnightLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Roger L MilneCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
Alice S WhittemoreDepartments of Health Research and Policy and Biomedical Data Science, Stanford University School of Medicine, Stanford.
Wendy K ChungHerbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York.
Nicole LeoceDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York.
Richard BuchsbaumDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York.
Nur ZeinomarDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York.
Gillian S DiteCentre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
Melissa C SoutheyCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
David GoldgarDepartment of Medicine and Huntsman Cancer Institute, University of Utah Health, Salt Lake City, UT.
Graham G GilesCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
Sue-Anne McLachlanDepartment of Medicine, St Vincent's Hospital, The University of Melbourne, Parkville, Victoria, Australia.
Prue C WeidemanCentre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
Stephanie NesciDepartment of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Michael L FriedlanderPrince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia.
Gord GlendonLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
kConFab Investigators
Irene L AndrulisLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Esther M JohnDepartment of Medicine and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA.
Mary B DalyDepartment of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA.
Saundra S BuysDepartment of Medicine and Huntsman Cancer Institute, University of Utah Health, Salt Lake City, UT.
Kelly Anne PhillipsCentre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
John L HopperCentre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, The University of Melbourne, Parkville, Victoria, Australia.
Mary Beth TerryDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York.
The University of Melbourne · AUColumbia University · USColumbia University Irving Medical Center · USFox Chase Cancer Center · USLunenfeld-Tanenbaum Research Institute · CAPeter MacCallum Cancer Centre · AUStanford University · USUniversity of Toronto · CAUniversity of Utah · USUNSW Sydney · AU

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Breast Cancer Family Registry CohortUM1CA164920 · NCI · CANCER PREVENTION INSTIT OF CALIFORNIA · PI ANDRULIS, IRENE, BUYS, SAUNDRA S · 2012 to 2017
$12.7M
Genes, environment and breast cancer risk: The 15 year follow-up of the Prof-SC (Diversity Supplement)R01CA159868 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HOPPER, JOHN L, TERRY, MARY BETH · 2011 to 2015
$9.0M
NRSA Training CoreTL1TR001875 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SPANN, MARISA N, TAYLOR, JACQUELYN Y · 2016 to 2025
$8.9M
NCATS NIH HHS TL1 TR001875NCATS NIH HHS UL1 TR001863NCI NIH HHS R01 CA159868NCI NIH HHS UM1 CA164920
6 · The paper itself

Abstract

The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models.

Indexed as

Models, StatisticalAdultAgedAustraliaBRCA1 ProteinBRCA2 ProteinBreast NeoplasmsCanadaFemaleHumansMiddle AgedMutationRiskUnited StatesYoung AdultBRCA1 ProteinBRCA1 protein, humanBRCA2 ProteinBRCA2 protein, human

Identifiers

PMID31584660
PMCPMC7156937
OpenAlexW2978240649

What OpenQuestion holds

Textmetadata
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.