Evidence map›Paper›PMID 38602645›Full record

ReviewClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2024

Exploring research progress in studying serum exosomal miRNA-21 as a molecular diagnostic marker for breast cancer.

Hang Li, Xiao-Jing Tie

Abstract readReview
PubMed Publisher
In one paragraph

Review in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
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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

2 authors.

Hang Li *Department of Laboratory Medicine, Kaifeng Central Hospital, 85 HeDao Street, Kaifeng, 475000, China. hang297li@126.com.ORCID http://orcid.org/0009-0000-9518-732X
Xiao-Jing Tie *Department of Oncology, Kaifeng Central Hospital, Kaifeng, 475000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is one of the most prevalent malignancies affecting women globally and poses a significant public health challenge. Early clinical detection plays a pivotal role in providing optimal treatment opportunities and favorable prognoses, crucial for reducing breast cancer mortality and enhancing patients' quality of life. Therefore, the timely identification and diagnosis of breast cancer are imperative. Conventional tumor markers, such as carcinoembryonic antigen (CEA) and carbohydrate antigen 15-3 (CA15-3), serve as reliable methods for actively monitoring disease progression and have become a routine auxiliary diagnostic approach in clinical settings. However, these biomarkers exhibit limitations in sensitivity and specificity, particularly in the early screening and diagnosis of tumors, often yielding results inconsistent with clinical manifestations. In recent years, research has increasingly focused on exosomes released by tumor cells as potential new biomarkers for early stage breast cancer screening. Exosomes carry various components, including tumor-derived proteins, nucleic acids, and lipids. This paper delves into the specific utilization of serum exosomal microRNA-21 (miR-21) as a biomarker for early detection and diagnosis of breast cancer, evaluating its efficacy within this framework.

Indexed as

Biomarkers, TumorBreast NeoplasmsEarly Detection of CancerExosomesMicroRNAsFemaleHumansBiomarkers, TumorMicroRNAsMIRN21 microRNA, humanBreast cancermiR-21Molecular diagnosis

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.