Evidence map›Paper›PMID 31177342›Full record

ReviewBreast cancer research and treatment2019

A review of the influence of mammographic density on breast cancer clinical and pathological phenotype.

Michael S Shawky, Cecilia W Huo, Michael A Henderson, Andrew Redfern, Kara Britt, Erik W Thompson

Abstract readReview
PubMed Publisher
In one paragraph

Review in Breast cancer research and treatment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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

6 authors.

Michael S Shawky *Department of Head and Neck and Endocrine Surgery, Faculty of Medicine, University of Alexandria, Alexandria, Egypt.
Cecilia W Huo *Department of Surgery, St Vincent's Hospital, University of Melbourne, Melbourne, VIC, Australia.
Michael A HendersonDepartment of Surgery, St Vincent's Hospital, University of Melbourne, Melbourne, VIC, Australia.
Andrew RedfernSchool of Medicine, University of Western Australia, Perth, WA, Australia.
Kara Britt *Sir Peter MacCallum Department of Oncology, University of Melbourne, Grattan Street, Parkville, Melbourne, VIC, 3010, Australia.
Erik W Thompson *Department of Surgery, St Vincent's Hospital, University of Melbourne, Melbourne, VIC, Australia. e2.thompson@qut.edu.au.ORCID http://orcid.org/0000-0002-9723-4924

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIt is well established that high mammographic density (MD), when adjusted for age and body mass index, is one of the strongest known risk factors for breast cancer (BC), and also associates with higher incidence of interval cancers in screening due to the masking of early mammographic abnormalities. Increasing research is being undertaken to determine the underlying histological and biochemical determinants of MD and their consequences for BC pathogenesis, anticipating that improved mechanistic insights may lead to novel preventative or treatment interventions. At the same time, technological advances in digital and contrast mammography are such that the validity of well-established relationships needs to be re-examined in this context.

methodsWith attention to old versus new technologies, we conducted a literature review to summarise the relationships between clinicopathologic features of BC and the density of the surrounding breast tissue on mammography, including the associations with BC biological features inclusive of subtype, and implications for the clinical disease course encompassing relapse, progression, treatment response and survival. RESULTS AND

conclusionsThere is reasonable evidence to support positive relationships between high MD (HMD) and tumour size, lymph node positivity and local relapse in the absence of radiotherapy, but not between HMD and LVI, regional relapse or distant metastasis. Conflicting data exist for associations of HMD with tumour location, grade, intrinsic subtype, receptor status, second primary incidence and survival, which need further confirmatory studies. We did not identify any relationships that did not hold up when data involving newer imaging techniques were employed in analysis.

Indexed as

Breast DensityPhenotypeBiomarkers, TumorBreast NeoplasmsFemaleHumansImage Processing, Computer-AssistedMass ScreeningNeoplasm GradingNeoplasm InvasivenessNeoplasm MetastasisNeoplasms, Second PrimaryNeoplasm StagingPrognosisPublic Health SurveillanceRisk FactorsBiomarkers, TumorBreast cancerBreast cancer pathologyMammographic densityOestrogen receptor

Identifiers

What OpenQuestion holds

Textmetadata
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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.