Evidence map›Paper›PMID 37649088›Full record

ReviewJournal of translational medicine2023

Breast stiffness, a risk factor for cancer and the role of radiology for diagnosis.

Sofia M Tarchi, Monica Pernia Marin, Md Murad Hossain, Mary Salvatore

Open access · goldAbstract readReview
In one paragraph

Review in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
5.3field-weighted citation impact, top 4% 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

11 citing papers in PubMed, 22 citations in OpenAlex.

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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

4 authors at 3 institutions in 2 countries.

Sofia M TarchiDepartment of Radiology, Columbia University Irving Medical Center, New York, NY, USA.
Monica Pernia MarinDepartment of Radiology, Columbia University Irving Medical Center, New York, NY, USA. monicapernia.md@gmail.com.ORCID http://orcid.org/0000-0002-1197-3831
Md Murad HossainDepartment of Biomedical Engineering, Columbia University, New York, NY, USA.
Mary SalvatoreDepartment of Radiology, Columbia University Irving Medical Center, New York, NY, USA.
Columbia University Irving Medical Center · USColumbia University · USHumanitas University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last five decades, breast density has been associated with increased risk of developing breast cancer. Mammographically dense breasts are considered those belonging to the heterogeneously dense breasts, and extremely dense breasts subgroups according to the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS). There is a statistically significant correlation between the increased mammographic density and the presence of more glandular tissue alone. However, the strength of this correlation is weak. Although the mechanisms driving breast density-related tumor initiation and progression are still unknown, there is evidence suggesting that certain molecular pathways participating in epithelial-stromal interactions may play a pivotal role in the deposition of fibrillar collagen, increased matrix stiffness, and cell migration that favor breast density and carcinogenesis. This article describes these molecular mechanisms as potential "landscapers" for breast density-related cancer. We also introduce the term "Breast Compactness" to reflect collagen density of breast tissue on chest CT scan and the use of breast stiffness measurements as imaging biomarkers for breast cancer screening and risk stratification.

Indexed as

Breast NeoplasmsRadiologyBreastFemaleHumansRisk FactorsTomography, X-Ray Computed

Identifiers

PMID37649088
PMCPMC10466778
OpenAlexW4386289997

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.