Evidence map›Paper›PMID 39618080›Full record

ArticleAnnals of medicine2024

HER-2 expression is correlated with multimodal imaging features in breast cancer: a pilot study.

Xiao-Dan Zhang, Min Kou, Wei-Yan Zou, Xu Duan, Gui-Xin Di, Wei Qin, Li-Hui Bian, Ze-Peng Ma

Abstract read
In one paragraph

Article in Annals of medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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

8 authors.

Xiao-Dan ZhangDepartment of Ultrasound, Affiliated Hospital of Hebei University, Baoding, China.
Min KouDepartment of Ultrasound, Affiliated Hospital of Hebei University, Baoding, China.
Wei-Yan ZouDepartment of Ultrasound, Affiliated Hospital of Hebei University, Baoding, China.
Xu DuanDepartment of Ultrasound, Affiliated Hospital of Hebei University, Baoding, China.
Gui-Xin DiDepartment of Ultrasound, Affiliated Hospital of Hebei University, Baoding, China.
Wei QinDepartment of Integrated Chinese and Western Medicine, Affiliated Hospital of Hebei University, Baoding, China.
Li-Hui BianDepartment of Pathology, Affiliated Hospital of Hebei University, Baoding, China.
Ze-Peng MaDepartment of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveA pilot study to evaluate the correlation between multimodal imaging features and the expression of the human epidermal growth factor receptor type 2 (HER-2) in breast cancer to provide a basis for clinical treatment and prognosis evaluation.

methodsWe included a total of 62 patients with breast cancer admitted to the Affiliated Hospital of Hebei University between 2018 and 2022. All of them underwent the relevant investigations, including ultrasound, mammography, and enhanced magnetic resonance imaging (MRI), in the hospital within one month before surgery or biopsy. HER-2 expression level was divided into negative and positive by immunohistochemistry(IHC). Using SPSS 24.0 statistical software to analyze the differences in imaging features between the HER-2 positive and the HER-2 negative groups.

resultsThere was a statistically significant difference between the HER-2 positive and the HER-2 negative groups (

conclusionA combination of multimodal imaging features and HER-2 gene expression can provide more valuable information for clinical diagnosis and therapeutic schedule in breast cancer.

Indexed as

Breast NeoplasmsErb-b2 Receptor Tyrosine KinasesMagnetic Resonance ImagingMultimodal ImagingAdultAgedFemaleHumansImmunohistochemistryMammographyMiddle AgedPilot ProjectsSensitivity and SpecificityERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesADCbreast cancerHER-2hyperechoic halomultimodal imaging

Identifiers

PMID39618080
PMCPMC11613333

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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.