Evidence map›Paper›PMID 42690734›Full record

ArticleThe breast journal2026

Assessing the Effect of Breast Density on Screening Performance in a Population-Based Program.

Chirag Mistry, Richard Walton, Matthew Warner-Smith, Kan Ren, David Roder, Bronwyn Morley, Tracey O'Brien

Abstract read
In one paragraph

Article in The breast journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Chirag MistryCancer Institute NSW, Sydney, New South Wales, Australia.ORCID https://orcid.org/0009-0003-8540-6615
Richard WaltonCancer Institute NSW, Sydney, New South Wales, Australia.ORCID https://orcid.org/0009-0002-0520-0135
Matthew Warner-SmithCancer Institute NSW, Sydney, New South Wales, Australia.ORCID https://orcid.org/0009-0003-7056-2551
Kan RenCancer Institute NSW, Sydney, New South Wales, Australia.
David RoderCancer Epidemiology & Population Health, Adelaide University, Adelaide, South Australia, Australia, adelaide.edu.au.ORCID https://orcid.org/0000-0001-6442-4409
Bronwyn MorleyCancer Institute NSW, Sydney, New South Wales, Australia.
Tracey O'BrienCancer Institute NSW, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-5759-6162

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast density is both an independent risk factor for breast cancer and a major determinant of mammographic diagnostic performance. However, its impact on overall screening performance within population-based screening programs is less well understood.

methodsThis retrospective cohort study included women aged 50-74 years screened through BreastScreen NSW between 1 January 2016 and 31 December 2017, excluding first-time screeners above 70. Breast density was assessed using Lunit INSIGHT MMG (v1.1.7) generating an ordinal density score (1-10) and corresponding BI-RADS category (A-D). Screen-detected and interval cancers were ascertained via the NSW BreastScreen Information System and the NSW Cancer Registry. Standard screening performance metrics were calculated stratified by age, breast density and screening round.

resultsThe cohort comprised 564,681 screening episodes, with 4758 cancers diagnosed (3756 screen-detected; 1002 interval). Cancer incidence rates and screening performance varied by breast density. The proportion of cancers that were interval cancers increased markedly with increasing density, from 10.9% of cancers in category A (least dense) to 46.6% in category D. Recall rates followed an N-shaped pattern, peaking in density category C, while specificity mirrored this relationship.

conclusionThe effectiveness of conventional two-dimensional mammography is strongly dependent on breast density, with reduced sensitivity and increased interval cancer rates for clients with extremely dense breasts. By utilising a more granular measure of breast density in a large population screening cohort, this study identified nonlinear relationships between breast density and screening performance metrics, providing evidence to support future evaluation of more individualised screening approaches.

Indexed as

Breast DensityBreast NeoplasmsEarly Detection of CancerMammographyAgedFemaleHumansMass ScreeningMiddle AgedNew South WalesRetrospective Studiesbreast cancerbreast densitycancer incidencediagnostic performanceinterval cancerspopulation-based screeningscreening mammography

Identifiers

PMID42690734
PMCPMC13540992

What OpenQuestion holds

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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.