Evidence map›Paper›PMID 33411577›Full record

ArticleThe British journal of radiology2021

Digital breast tomosynthesis: sensitivity for cancer in younger symptomatic women.

Patsy Whelehan, Kulsam Ali, Sarah Vinnicombe, Graham Ball, Julie Cox, Paul Farry, Maggie Jenkin, Keith Lowry, Stuart A McIntosh, Rachel Nutt and 9 more

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in The British journal of radiology, 2021. 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
0.7field-weighted citation impact, top 29% 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

0 citing papers in PubMed, 9 citations in OpenAlex.

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

19 authors at 11 institutions in 1 country.

Patsy WhelehanSchool of Medicine, University of Dundee, Mailbox 4, Ninewells Hospital & Medical School, Dundee, UK.ORCID https://orcid.org/0000-0001-8336-945X
Kulsam AliSchool of Medicine, University of Dundee, Mailbox 4, Ninewells Hospital & Medical School, Dundee, UK.
Sarah VinnicombeGloucestershire Hospitals NHS Foundation Trust, Cheltenham, UK.
Graham BallNottingham Trent University, Nottingham, UK & Intelligent OMICS Ltd, Nottingham, UK.
Julie CoxSouth Tyneside and Sunderland NHS Foundation Trust, Sunderland, UK.
Paul FarryWestern Health and Social Care Trust, Londonderry, UK.
Maggie JenkinDerriford Hospital, Plymouth, UK.
Keith LowryBelfast Health and Social Care Trust, Belfast, UK.
Stuart A McIntoshQueen's University, Belfast, UK.
Rachel NuttSchool of Medicine, University of Dundee, Mailbox 4, Ninewells Hospital & Medical School, Dundee, UK.
Rachel OeppenUniversity Hospital Southampton NHS Foundation Trust, Southampton, UK.
Michael ReillyWestern Health and Social Care Trust, Londonderry, UK.
Michaela StahnkeUniversity Hospital Southampton NHS Foundation Trust, Southampton, UK.
Jim SteelDerriford Hospital, Plymouth, UK.
Yee Ting SimNHS Tayside, Dundee, UK.
Violet WarwickSchool of Medicine, University of Dundee, Mailbox 4, Ninewells Hospital & Medical School, Dundee, UK.
Louise WilkinsonOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Dimitrios ZafeirisNottingham Trent University, Nottingham, UK & Intelligent OMICS Ltd, Nottingham, UK.
Andrew J EvansSchool of Medicine, University of Dundee, Mailbox 4, Ninewells Hospital & Medical School, Dundee, UK.
University of Dundee · GBDerriford Hospital · GBNottingham Trent University · GBUniversity Hospital Southampton NHS Foundation Trust · GBWestern Health and Social Care Trust · GBBelfast Health and Social Care Trust · GBGloucestershire Hospitals NHS Foundation Trust · GBNHS Tayside · GBOxford University Hospitals NHS Trust · GBQueen's University Belfast · GBSouth Tyneside and Sunderland NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveFull-field digital mammography (FFDM) has limited sensitivity for cancer in younger women with denser breasts. Digital breast tomosynthesis (DBT) can reduce the risk of cancer being obscured by overlying tissue. The primary study aim was to compare the sensitivity of FFDM, DBT and FFDM-plus-DBT in women under 60 years old with clinical suspicion of breast cancer.

methodsThis multicentre study recruited 446 patients from UK breast clinics. Participants underwent both standard FFDM and DBT. A blinded retrospective multireader study involving 12 readers and 300 mammograms (152 malignant and 148 benign cases) was conducted.

resultsSensitivity for cancer was 86.6% with FFDM [95% CI (85.2-88.0%)], 89.1% with DBT [95% CI (88.2-90%)], and 91.7% with FFDM+DBT [95% CI (90.7-92.6%)]. In the densest breasts, the maximum sensitivity increment with FFDM +DBT over FFDM alone was 10.3%, varying by density measurement method. Overall specificity was 81.4% with FFDM [95% CI (80.5-82.3%)], 84.6% with DBT [95% CI (83.9-85.3%)], and 79.6% with FFDM +DBT [95% CI (79.0-80.2%)]. No differences were detected in accuracy of tumour measurement in unifocal cases.

conclusionsWhere available, DBT merits first-line use in the under 60 age group in symptomatic breast clinics, particularly in women known to have very dense breasts. ADVANCES IN KNOWLEDGE: This study is one of very few to address the accuracy of DBT in symptomatic rather than screening patients. It quantifies the diagnostic gains of DBT in direct comparison with standard digital mammography, supporting informed decisions on appropriate use of DBT in this population.

Indexed as

AdultAge FactorsBreastBreast NeoplasmsFemaleHumansMammographyMiddle AgedReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityUnited KingdomYoung Adult

Identifiers

PMID33411577
PMCPMC8011263
OpenAlexW3118367166

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.