Evidence map›Paper›PMID 30390716›Full record

ArticleBreast cancer research : BCR2018

Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC).

John L Hopper, Gillian S Dite, Robert J MacInnis, Yuyan Liao, Nur Zeinomar, Julia A Knight, Melissa C Southey, Roger L Milne, Wendy K Chung, Graham G Giles and 14 more

Abstract read
In one paragraph

Article in Breast cancer research : BCR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

51 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  9. Early breast cancer in youngTherapeutic advances in medical oncology · 2025
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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

24 authors.

John L HopperCentre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC, Australia. j.hopper@unimelb.edu.au.ORCID 0000-0002-8567-173X
Gillian S DiteCentre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC, Australia.
Robert J MacInnisCentre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC, Australia.
Yuyan LiaoDepartment of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, 7th Floor, New York, NY, USA.
Nur ZeinomarDepartment of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, 7th Floor, New York, NY, USA.
Julia A KnightLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Melissa C SoutheyDepartment of Pathology, Genetic Epidemiology Laboratory, The University of Melbourne, Parkville, VIC, Australia.
Roger L MilneCentre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC, Australia.
Wendy K ChungHerbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.
Graham G GilesCentre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC, Australia.
Jeanine M GenkingerDepartment of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, 7th Floor, New York, NY, USA.
Sue-Anne McLachlanDepartment of Medicine, St Vincent's Hospital, The University of Melbourne, Parkville, VIC, Australia.
Michael L FriedlanderPrince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia.
Antonis C AntoniouDepartment of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK.
Prue C WeidemanCentre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC, Australia.
Gord GlendonLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Stephanie NesciDivision of Cancer Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
kConFab Investigators
Irene L AndrulisLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Saundra S BuysDepartment of Medicine and Huntsman Cancer Institute, University of Utah Health Sciences Center, Salt Lake City, UT, USA.
Mary B DalyDepartment of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA.
Esther M JohnDepartment of Medicine and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
Kelly Anne PhillipsCentre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC, Australia.
Mary Beth TerryDepartment of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, 7th Floor, New York, NY, USA. mt146@cumc.columbia.edu.

Funding

True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MATTHEW S PERZANOWSKI · 1998 to 2026
$44.7M
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
Cancer Research UK 20861Cancer Research UK C12292/A20861NCATS NIH HHS TL1 TR001875NCI NIH HHS R01 CA159868NCI NIH HHS UM1 CA164920NIEHS NIH HHS P30 ES009089
6 · The paper itself

Abstract

backgroundThe association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk.

methodsWe conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline.

resultsThe strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk.

conclusionsThe greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.

Indexed as

Body Mass IndexAdultAgedAge FactorsAustraliaBreast NeoplasmsCanadaFemaleFollow-Up StudiesHumansIncidenceMedical History TakingMiddle AgedNew ZealandPostmenopausePremenopauseBody mass indexBreast and Ovarian Analysis of Disease Incidence and Carrier Estimation AlgorithmBreast cancerFamilial riskGene–environment interaction

Identifiers

PMID30390716
PMCPMC6215632

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Registered trials

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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.