Evidence map›Paper›PMID 40226002›Full record

ReviewAmerican journal of translational research2025

Meta-analysis of the synergistic effect of magnetic resonance imaging and mammography in breast cancer detection in women with dense breasts.

Yu-Fei Lian, Dan-Qing Liu, Hui Wang

Abstract readReview
In one paragraph

Review in American journal of translational research, 2025. 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
–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

0 citing papers in PubMed.

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

3 authors.

Yu-Fei LianDepartment of Radiology, Affiliated Beijing Chaoyang Hospital of Capital Medical University (Shijingshan Campus) Beijing 100043, The People's Republic of China.
Dan-Qing LiuDepartment of Radiology, Affiliated Beijing Chaoyang Hospital of Capital Medical University (Shijingshan Campus) Beijing 100043, The People's Republic of China.
Hui WangInstitute of Genetics and Developmental Biology, Chinese Academy of Sciences Beijing 100101, The People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis meta-analysis aimed to evaluate the combined effectiveness of Magnetic Resonance Imaging (MRI) and mammography in detecting breast cancer in women with dense breasts.

methodsA comprehensive search was conducted across PubMed, Web of Science, and EMBASE databases up to December 31, 2023, to identify relevant studies. Studies focusing on breast cancer detection in women with dense breast tissue and providing data on the sensitivity, specificity, or positive predictive value of combined MRI and mammography screening, or the use of MRI following a negative mammogram, were included. The meta-analysis was conducted using Stata 15.0, and study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool.

resultsTen studies, involving 51,602 participants, were included in the meta-analysis. The combined use of MRI and mammography for breast cancer detection in women with dense breasts yielded a pooled sensitivity of 0.87 (95% CI: 0.79-0.92), specificity of 0.95 (95% CI: 0.89-0.97), positive likelihood ratio of 2.55 (95% CI: 1.45-4.46), negative likelihood ratio of 0.11 (95% CI: 0.07-0.17), diagnostic score of 3.18 (95% CI: 2.35-4.02), and diagnostic ratio of 24.14 (95% CI: 10.44-55.81), and an area under the Summary Receiver Operating Characteristic curve of 0.97 (95% CI: 0.95-0.98).

conclusionThis meta-analysis demonstrated that the combination of MRI and mammography enhanced breast cancer detection in women with dense breasts. This synergistic approach significantly improves detection sensitivity in this high-risk group.

Indexed as

Breast cancerdense breast tissueMagnetic Resonance Imaging (MRI)mammographymeta-analysis

Identifiers

PMID40226002
PMCPMC11982899

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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.