Evidence map›Paper›PMID 32575725›Full record

ArticleDiagnostics (Basel, Switzerland)2020

Mammographic Breast Density and Urbanization: Interactions with BMI, Environmental, Lifestyle, and Other Patient Factors.

Nick Perry, Sue Moss, Steve Dixon, Sue Milner, Kefah Mokbel, Charlotte Lemech, Hendrik-Tobias Arkenau, Stephen Duffy, Katja Pinker

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. The epidemiologic factors associated with breast density: A review.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2022
    Review
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

9 authors at 6 institutions in 3 countries.

Nick PerryLondon Breast Institute, Princess Grace Hospital, London W1U 5NY, UK.
Sue MossWolfson Institute, Queen Mary University of London, London EC1M 6BQ, UK.
Steve DixonHCA Healthcare UK, London NW1 6JQ, UK.ORCID 0000-0003-4711-6521
Sue MilnerLondon Breast Institute, Princess Grace Hospital, London W1U 5NY, UK.
Kefah MokbelLondon Breast Institute, Princess Grace Hospital, London W1U 5NY, UK.
Charlotte LemechScientia Clinical Research, Sydney, Australia and Prince of Wales Hospital Clinical School, UNSW, Sydney NSW 2031, Australia.
Hendrik-Tobias ArkenauSarah Cannon Research Institute UK and University College London, London W1G 6AD, UK.
Stephen DuffyWolfson Institute, Queen Mary University of London, London EC1M 6BQ, UK.
Katja PinkerDepartment of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.ORCID 0000-0002-2722-7331
The Princess Grace Hospital · GBQueen Mary University of London · GBInforma Healthcare · GBMemorial Sloan Kettering Cancer Center · USSarah Cannon Research Institute · GBUNSW Sydney · AU

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
HCA (Hospital Corporation of America) Healthcare UK N/ANCI NIH HHS P30 CA008748NIH HHS P30 CA008748
6 · The paper itself

Abstract

Mammographic breast density (MBD) is an important imaging biomarker of breast cancer risk, but it has been suggested that increased MBD is not a genuine finding once corrected for age and body mass index (BMI). This study examined the association of various factors, including both residing in and working in the urban setting, with MBD. Questionnaires were completed by 1144 women attending for mammography at the London Breast Institute in 2012-2013. Breast density was assessed with an automated volumetric breast density measurement system (Volpara) and compared with subjective radiologist assessment. Multivariable linear regression was used to model the relationship between MBD and residence in the urban setting as well as working in the urban setting, adjusting for both age and BMI and other menstrual, reproductive, and lifestyle factors. Urban residence was significantly associated with an increasing percent of MBD, but this association became non-significant when adjusted for age and BMI. This was not the case for women who were both residents in the urban setting and still working. Our results suggest that the association between urban women and increased MBD can be partially explained by their lower BMI, but for women still working, there appear to be other contributing factors.

Indexed as

body mass indexbreast cancer riskbreast densitymammographyurban

Identifiers

PMID32575725
PMCPMC7344692
OpenAlexW3035917759

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.