Evidence map›Paper›PMID 39567919›Full record

SynthesisBMC cancer2024

CD147 expression as a clinicopathological and prognostic indicator in breast cancer: a meta-analysis and bioinformatics analysis.

Shuai Shi, Hong-Yan Ma, Yin-Zhou Sang, Ying-Bo Ju, Xing-Guang Wang, Zhi-Gang Zhang

Abstract readMeta-Analysis
In one paragraph

Synthesis in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
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  6. Review
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.

Shuai ShiDepartment of Pathology, Cangzhou People's Hospital, 7 Qingchi Avenue, Cangzhou City, 061000, China.
Hong-Yan MaDepartment of Pathology, Cangzhou People's Hospital, 7 Qingchi Avenue, Cangzhou City, 061000, China.
Yin-Zhou SangDepartment of Pathology, Cangzhou People's Hospital, 7 Qingchi Avenue, Cangzhou City, 061000, China.
Ying-Bo JuDepartment of Pathology, Cangzhou People's Hospital, 7 Qingchi Avenue, Cangzhou City, 061000, China.
Xing-Guang WangDepartment of Pathology, Cangzhou People's Hospital, 7 Qingchi Avenue, Cangzhou City, 061000, China.
Zhi-Gang ZhangDepartment of Pathology, Cangzhou People's Hospital, 7 Qingchi Avenue, Cangzhou City, 061000, China. zhzhg001518@126.com.

Funding

Medical Science Research Project in Hebei Province 20240850
6 · The paper itself

Abstract

backgroundCD147 belongs to the immunoglobulin superfamily, also known as Basigin (BSG), and is a highly glycosylated single transmembrane glycoprotein present in various tissues. Meta and bioinformatic analyses were used to explore the correlation between CD147 expression and the clinicopathological characteristics prognosis of breast cancer.

methodLiterature related to breast cancer was retrieved through PubMed and CNKI databases, and a meta-analysis was conducted using Review Manager 5.2 software.

resultsThe meta-analysis revealed that all articles included data on 522 patients with breast cancer and 492 normal tissues. CD147 expression in breast cancer tissue was higher compared to that in normal tissue([8.92-139.52]; p < 0.00001 I

conclusionThese results indicated that high CD147 expression might be closely linked to the occurrence as well as the development of breast cancer, and can function as a good indicator of prognosis in the future, providing new methods and ideas for the prevention and treatment of breast cancer.

Indexed as

BasiginBiomarkers, TumorBreast NeoplasmsComputational BiologyFemaleGene Expression Regulation, NeoplasticHumansNeoplasm GradingNeoplasm StagingPrognosisBasiginBiomarkers, TumorBSG protein, humanBioinformatic analysisBreast cancerCD147Meta analysisPrognostic

Identifiers

PMID39567919
PMCPMC11577919

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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.