Evidence map›Paper›PMID 38487727›Full record

ArticleFrontiers in oncology2024

Contrast-enhanced ultrasound for the preoperative prediction of pathological characteristics in breast cancer.

Ling-Ling Li, Quan-Li Su, Yun-Xia Deng, Wen-Wen Guo, Hai-Mei Lun, Qiao Hu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 35% 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

5 citing papers in PubMed, 2 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Ling-Ling Li *Departments of Ultrasound, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
Quan-Li Su *Departments of Ultrasound, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
Yun-Xia DengDepartments of Ultrasound, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
Wen-Wen GuoDepartments of Pathology, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
Hai-Mei LunDepartments of Ultrasound, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
Qiao HuDepartments of Ultrasound, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
The People's Hospital of Guangxi Zhuang Autonomous Region · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We aimed to investigate the value of contrast-enhanced ultrasound (CEUS) in the preoperative prediction of the histological grades and molecular subtypes of breast cancer. Methods: A total of 183 patients with pathologically confirmed breast cancer were included. Contrast enhancement patterns and quantitative parameters were compared in different groups. The receiver operating characteristic (ROC) curve was used to analyze the efficacy of CEUS in the preoperative prediction of pathological characteristics, including histologic grade and molecular subtypes. Results: Heterogeneous enhancement, perfusion defects, and peripheral radial vessels were mostly observed in higher histologic grade (grade III) breast cancer. Heterogeneous enhancement and perfusion defect were the most effective indicators for grade III breast cancer, with the areas under the ROC curve of 0.768 and 0.756, respectively. There were significant differences in the enhancement intensity, post-enhanced margin, perfusion defects, and peripheral radial vessel among the different molecular subtypes of breast cancer (all Conclusion: Qualitative and quantitative perfusion analysis of contrast-enhanced ultrasound may be useful in the non-invasive prediction of the histological grade and molecular subtypes of breast cancers.

Indexed as

breast cancercontrast-enhanced ultrasoundhistological grademolecular subtypesVueBox

Identifiers

PMID38487727
PMCPMC10937469
OpenAlexW4392290328

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.