Evidence map›Paper›PMID 38498102›Full record

ArticleBreast cancer research and treatment2024

The distribution of breast density in women aged 18 years and older.

Dilukshi Perera, Sarah Pirikahu, Jane Walter, Gemma Cadby, Ellie Darcey, Rachel Lloyd, Martha Hickey, Christobel Saunders, Michael Hackmann, David D Sampson and 3 more

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

Article in Breast cancer research and treatment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.4field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Understanding and targeting the tumour matrisome.Nature reviews. Clinical oncology · 2026
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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

13 authors at 6 institutions in 4 countries.

Dilukshi PereraGenetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia.
Sarah PirikahuGenetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia.
Jane WalterUniversity Health Network, Toronto, ON, Canada.
Gemma CadbyGenetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia.
Ellie DarceyGenetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia.
Rachel LloydGenetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia.
Martha HickeyDepartment of Obstetrics and Gynaecology, University of Melbourne and the Royal Women's Hospital, Melbourne, VIC, Australia.
Christobel SaundersDepartment of Surgery, Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.
Michael HackmannSchool of Human Sciences, The University of Western Australia, Perth, WA, Australia.
David D SampsonSurry Biophotonics, Advanced Technology Institute and School of Biosciences and Medicine, The University of Surrey, Guildford, Surrey, UK.
John ShepherdEpidemiology and Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
Lothar LilgeUniversity Health Network, Toronto, ON, Canada.
Jennifer StoneGenetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, 35 Stirling Highway M431, Perth, WA, 6009, Australia. Jennifer.stone@uwa.edu.au.ORCID http://orcid.org/0000-0001-5077-0124
The University of Western Australia · AUUniversity Health Network · CARoyal Women's Hospital · AUThe Royal Melbourne Hospital · AUUniversity of Hawaiʻi at Mānoa · USUniversity of Surrey · GB

Funding

Cancer Australia APP1147677National Breast Cancer Foundation PS-15-040-1597582
6 · The paper itself

Abstract

purposeAge and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI.

methodsBreast density measures were estimated for 1,961 Australian women aged 18-97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI.

resultsThe mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI.

conclusionThis unique study describes the distribution of breast density measures for women aged 18-97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.

Indexed as

Absorptiometry, PhotonBody Mass IndexBreast DensityBreast NeoplasmsMammographyAdolescentAdultAgedAged, 80 and overAge FactorsAustraliaBreastCross-Sectional StudiesFemaleHumansMiddle AgedBreast cancerBreast densityMeasurementRisk factor

Identifiers

PMID38498102
PMCPMC11101556
OpenAlexW4392911941

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.