Evidence map›Paper›PMID 35145999›Full record

ReviewFrontiers in molecular biosciences2022

Triple-Negative Breast Cancer: A Brief Review About Epidemiology, Risk Factors, Signaling Pathways, Treatment and Role of Artificial Intelligence.

Nahlah Makki Almansour

Abstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 236 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
236citing papers in PubMed, 5 pooled it
–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

236 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  4. Association of tumor-infiltrating lymphocytes with clinical outcomes in patients with triple-negative breast cancer receiving neoadjuvant chemotherapy: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
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176 more citing papers are in PubMed but not listed here.

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

1 author.

Nahlah Makki AlmansourDepartment of Biology, College of Science, University of Hafr Al Batin, Hafr Al Batin, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is a kind of breast cancer that lacks estrogen, progesterone, and human epidermal growth factor receptor 2. This cancer is responsible for more than 15-20% of all breast cancers and is of particular research interest as it is therapeutically challenging mainly because of its low response to therapeutics and highly invasive nature. The non-availability of specific treatment options for TNBC is usually managed by conventional therapy, which often leads to relapse. The focus of this review is to provide up-to-date information related to TNBC epidemiology, risk factors, metastasis, different signaling pathways, and the pathways that can be blocked, immune suppressive cells of the TNBC microenvironment, current and investigation therapies, prognosis, and the role of artificial intelligence in TNBC diagnosis. The data presented in this paper may be helpful for researchers working in the field to obtain general and particular information to advance the understanding of TNBC and provide suitable disease management in the future.

Indexed as

artificial intelligenceprognosisrisk factorsignaling pathwaystriple negative breast cancer

Identifiers

PMID35145999
PMCPMC8824427

What OpenQuestion holds

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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.