Evidence map›Paper›PMID 34638289›Full record

ReviewCancers2021

Mammographic Density Changes over Time and Breast Cancer Risk: A Systematic Review and Meta-Analysis.

Arezo Mokhtary, Andreas Karakatsanis, Antonis Valachis

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 3 pooled it
5.9field-weighted citation impact, top 3% 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

26 citing papers in PubMed, 3 syntheses or guidelines pooled it, 49 citations in OpenAlex.

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  10. Breast MRI to Screen Women With Extremely Dense Breasts.Journal of magnetic resonance imaging : JMRI · 2025
    Review
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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

3 authors at 2 institutions in 1 country.

Arezo MokhtaryFaculty of Medicine and Health, School of Medical Sciences, Örebro University, 70182 Örebro, Sweden.
Andreas KarakatsanisDepartment of Surgical Sciences, Uppsala University, 75185 Uppsala, Sweden.ORCID 0000-0003-3622-3575
Antonis ValachisDepartment of Oncology, Faculty of Medicine and Health, Örebro University, 70182 Örebro, Sweden.
Örebro University · SEUppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this meta-analysis was to evaluate the association between mammographic density changes over time and the risk of breast cancer. We performed a systematic literature review based on the PubMed and ISI Web of Knowledge databases. A meta-analysis was conducted by computing extracted hazard ratios (HRs) and 95% confidence intervals (CIs) for cohort studies or odds ratios (ORs) and 95% confidence interval using inverse variance method. Of the nine studies included, five were cohort studies that used HR as a measurement type for their statistical analysis and four were case-control or cohort studies that used OR as a measurement type. Increased breast density over time in cohort studies was associated with higher breast cancer risk (HR: 1.61; 95% CI: 1.33-1.96) whereas decreased breast density over time was associated with lower breast cancer risk (HR: 0.78; 95% CI: 0.71-0.87). Similarly, increased breast density over time was associated with higher breast cancer risk in studies presented ORs (pooled OR: 1.85; 95% CI: 1.29-2.65). Our findings imply that an increase in breast density over time seems to be linked to an increased risk of breast cancer, whereas a decrease in breast density over time seems to be linked to a lower risk of breast cancer.

Indexed as

breast cancer riskbreast densitymammographymeta-analysis

Identifiers

PMID34638289
PMCPMC8507818
OpenAlexW3204565291

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.