Evidence map›Paper›PMID 34965921›Full record

ArticleCancer prevention research (Philadelphia, Pa.)2022

Weight is More Informative than Body Mass Index for Predicting Postmenopausal Breast Cancer Risk: Prospective Family Study Cohort (ProF-SC).

Zhoufeng Ye, Shuai Li, Gillian S Dite, Tuong L Nguyen, Robert J MacInnis, Irene L Andrulis, Saundra S Buys, Mary B Daly, Esther M John, Allison W Kurian and 11 more

Open access · hybridAbstract read
In one paragraph

Article in Cancer prevention research (Philadelphia, Pa.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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  5. 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

21 authors at 8 institutions in 4 countries.

Zhoufeng YeCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-0884-4246
Shuai LiCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.
Gillian S DiteCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-2448-2548
Tuong L NguyenCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-6597-8363
Robert J MacInnisCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.
Irene L AndrulisDepartments of Molecular Genetics and Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
Saundra S BuysDepartment of Medicine and Huntsman Cancer Institute, University of Utah Health Sciences Center, Salt Lake City, Utah.ORCID 0000-0003-4120-5697
Mary B DalyDepartment of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, Pennsylvania.
Esther M JohnDepartment of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California.ORCID 0000-0003-3259-8003
Allison W KurianDepartment of Medicine (Oncology), Stanford University School of Medicine, Stanford, California.ORCID 0000-0002-6175-9470
Jeanine M GenkingerDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, New York.ORCID 0000-0002-8438-0412
Wendy K ChungDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, New York.
Kelly-Anne PhillipsCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0002-0475-1771
Heather ThorneResearch Department, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Ingrid M WinshipDepartment of Medicine, The University of Melbourne, Melbourne, Victoria, Australia.
Roger L MilneCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0001-5764-7268
Pierre-Antoine DuguéCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0003-2736-3023
Melissa C SoutheyPrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.ORCID 0000-0002-6313-9005
Graham G GilesCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.ORCID 0000-0003-4946-9099
Mary Beth TerryDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, New York.
John L HopperCentre for Epidemiology and Biostatistics, University of Melbourne, Parkville, Victoria, Australia.
The University of Melbourne · AUCity University of New York · USPeter MacCallum Cancer Centre · AUFox Chase Cancer Center · USHuntsman Cancer Institute · USStanford Health Care · USStanford Medicine · USUniversity of Toronto · CA

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Core-001U01CA164920 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Irene Andrulis, Sarah Violet Colonna · 2018 to 2026
$17.0M
Institutional Career Development CoreKL2TR001874 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GENKINGER, JEANINE M., SHIMBO, DAICHI · 2016 to 2025
$13.6M
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
NCATS NIH HHS KL2 TR001874NCATS NIH HHS UL1 TR001873NCI NIH HHS R01 CA159868NCI NIH HHS U01 CA164920NCI NIH HHS UM1 CA164920
6 · The paper itself

Abstract

We considered whether weight is more informative than body mass index (BMI) = weight/height2 when predicting breast cancer risk for postmenopausal women, and if the weight association differs by underlying familial risk. We studied 6,761 women postmenopausal at baseline with a wide range of familial risk from 2,364 families in the Prospective Family Study Cohort. Participants were followed for on average 11.45 years and there were 416 incident breast cancers. We used Cox regression to estimate risk associations with log-transformed weight and BMI after adjusting for underlying familial risk. We compared model fits using the Akaike information criterion (AIC) and nested models using the likelihood ratio test. The AIC for the weight-only model was 6.22 units lower than for the BMI-only model, and the log risk gradient was 23% greater. Adding BMI or height to weight did not improve fit (ΔAIC = 0.90 and 0.83, respectively; both P = 0.3). Conversely, adding weight to BMI or height gave better fits (ΔAIC = 5.32 and 11.64; P = 0.007 and 0.0002, respectively). Adding height improved only the BMI model (ΔAIC = 5.47; P = 0.006). There was no evidence that the BMI or weight associations differed by underlying familial risk (P > 0.2). Weight is more informative than BMI for predicting breast cancer risk, consistent with nonadipose as well as adipose tissue being etiologically relevant. The independent but multiplicative associations of weight and familial risk suggest that, in terms of absolute breast cancer risk, the association with weight is more important the greater a woman's underlying familial risk. PREVENTION RELEVANCE: Our results suggest that the relationship between BMI and breast cancer could be due to a relationship between weight and breast cancer, downgraded by inappropriately adjusting for height; potential importance of anthropometric measures other than total body fat; breast cancer risk associations with BMI and weight are across a continuum.

Indexed as

Breast NeoplasmsBody Mass IndexBody WeightFemaleHumansPostmenopauseProspective StudiesRisk Factors

Identifiers

PMID34965921
PMCPMC8977841
OpenAlexW4200286881

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.