Evidence map›Paper›PMID 40634684›Full record

SynthesisClinical and experimental medicine2025

Performance of digital breast tomosynthesis with digital mammography for detecting breast cancer in the diagnostic setting: a meta-analysis.

Lei Liu, Chunyang Yu, Qiulan Fan, Baoqi Zeng

Abstract readMeta-Analysis
In one paragraph

Synthesis in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Lei LiuDepartment of Science and Technology, Beijing Shijitan Hospital, Beijing, China.
Chunyang YuDepartment of Ultrasound, Peking University Binhai Hospital (Tianjin Fifth Central Hospital), Tianjin, China.
Qiulan FanDepartment of Ultrasound, Peking University Binhai Hospital (Tianjin Fifth Central Hospital), Tianjin, China.
Baoqi ZengCentral Laboratory, Peking University Binhai Hospital (Tianjin Fifth Central Hospital), Tianjin, China. zengbaoqi@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To systematically determine the diagnostic accuracy of digital breast tomosynthesis (DBT) in combination with digital mammography (DM) compared with DM alone for breast cancer. We searched multiple English and Chinese databases from January 2010 to October 2023. Eligible diagnostic studies comparing DBT/DM with DM alone for breast cancer in women were included. QUADAS-2 tool was used to assess the risk of bias. The summary sensitivity, specificity, and diagnostic odds ratio (DOR) were estimated using a bivariate model. 27 studies with 45,694 individuals and 59,493 breast lesions were included. The pooled sensitivity and specificity of DBT/DM were 87% (95% confidence interval [CI], 84-90%) and 84% (95% CI, 78-88%), respectively. These values were higher than those of DM alone, with pooled sensitivity of 76% (95% CI, 72-79%) and specificity of 80% (95% CI, 73-86%). The pooled DORs for DBT/DM and DM alone were 34.74 (95% CI, 22.18-54.39) and 12.96 (95% CI, 8.80-19.08), respectively. Additionally, adding DBT to DM improved diagnostic performance more significantly in Asians (DORs, 59.47 vs. 16.10) than in Westerners (DORs, 19.48 vs. 10.30). Meta-regression analysis revealed that country, reference standard, and published language were significant factors (P < 0.05) affecting heterogeneity for DBT/DM. This meta-analysis demonstrated that DBT/DM has higher diagnostic accuracy than DM alone for breast cancer. Diagnosing breast cancer with DBT/DM significantly increased sensitivity and slightly increased specificity compared with DM alone. Furthermore, adding DBT to DM increased diagnostic performance more significantly in Asians than in Westerners.

Indexed as

Breast NeoplasmsMammographyFemaleHumansSensitivity and SpecificityBreast cancerDiagnosisDigital breast tomosynthesisDigital mammographyMeta-analysis

Identifiers

PMID40634684
PMCPMC12241149

What OpenQuestion holds

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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.