Evidence map›Paper›PMID 38264749›Full record

SynthesisFrontiers in oncology2023

A systematic review and meta-analysis comparing the diagnostic capability of automated breast ultrasound and contrast-enhanced ultrasound in breast cancer.

Haoyu Zhang, Jingyi Hu, Rong Meng, Fangfang Liu, Fan Xu, Min Huang

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2023. 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

6 authors.

Haoyu Zhang *Department of Clinic Medicine, Chengdu Medical College, Sichuan, China.
Jingyi Hu *Department of Clinic Medicine, Chengdu Medical College, Sichuan, China.
Rong MengDepartment of Public Health, Chengdu Medical College, Sichuan, China.
Fangfang LiuArt College, Southwest Minzu University, Sichuan, China.
Fan XuDepartment of Public Health, Chengdu Medical College, Sichuan, China.
Min HuangDepartment of Physiology, School of Basic Medicine, Chengdu Medical College, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To compare the diagnostic performance of automated breast ultrasound (ABUS) and contrast-enhanced ultrasound (CEUS) in breast cancer. Methods: Published studies were collected by systematically searching the databases PubMed, Embase, Cochrane Library and Web of Science. The sensitivities, specificities, likelihood ratios and diagnostic odds ratio (DOR) were confirmed. The symmetric receiver operator characteristic curve (SROC) was used to assess the threshold of ABUS and CEUS. Fagan's nomogram was drawn. Meta-regression and subgroup analyses were applied to search for sources of heterogeneity among the included studies. Results: A total of 16 studies were included, comprising 4115 participants. The combined sensitivity of ABUS was 0.88 [95% CI (0.73-0.95)], specificity was 0.93 [95% CI (0.82-0.97)], area under the SROC curve (AUC) was 0.96 [95% CI (0.94-0.96)] and DOR was 89. The combined sensitivity of CEUS was 0.88 [95% CI (0.84-0.91)], specificity was 0.76 [95% CI (0.66-0.84)], AUC was 0.89 [95% CI (0.86-0.92)] and DOR was 24. The Deeks' funnel plot showed no existing publication bias. The prospective design, partial verification bias and blinding contributed to the heterogeneity in specificity, while no sources contributed to the heterogeneity in sensitivity. The post-test probability of ABUS in BC was 75%, and the post-test probability of CEUS in breast cancer was 48%. Conclusion: Compared with CEUS, ABUS showed higher specificity and DOR for detecting breast cancer. ABUS is expected to further improve the accuracy of BC diagnosis.

Indexed as

automated breast ultrasound (ABUS)breast cancercontrast-enhanced ultrasound (CEUS)diagnosismeta-analysis

Identifiers

PMID38264749
PMCPMC10803446

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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.