Evidence map›Paper›PMID 31528166›Full record

ArticleIranian journal of pathology2019

Clinical Value of Serum S100A8/A9 and CA15-3 in the Diagnosis of Breast Cancer.

Samaneh Khorrami, Masoumeh Tavakoli, Elahe Safari

Open access · goldAbstract read
In one paragraph

Article in Iranian journal of pathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 23% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 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

3 authors at 1 institution in 1 country.

Samaneh KhorramiImmunology Research Center, Iran University of Medical Sciences, Tehran, Iran.
Masoumeh TavakoliDepartment of Biochemistry, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Elahe SafariImmunology Research Center, Iran University of Medical Sciences, Tehran, Iran.
Iran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveS100A8/A9 is a heterodimer calcium-binding protein which is involved in tumor cell proliferation, adhesion and invasion, and is proposed as a biomarker for better diagnosis and prognosis in many cancers. The aim of this study was to evaluate the simultaneous serum-based level of S100A8/A9 and CA15-3 as well-illustrated cancer biomarkers, as well as their prognostic value in breast cancer patients and healthy matched controls. MATERIAL AND

methodsThirty breast cancer patients at different stages of disease and healthy matched controls with no history of inflammatory, autoimmune diseases, or cancer, were enrolled in the study. The levels of S100A8/A9 and CA15-3 were assessed serologically using the Enzyme-linked immunosorbent assay (ELISA) method, and the relevance of these markers with patients' clinicopathological features were subsequently assessed.

resultsBased on our data, the serum levels of both S100A8/A9 and CA15-3 were significantly higher in patients compared to the healthy controls, and thus positively correlated with tumor size. Also, statistical analysis shows that the serum level of S100A8/A9 has 100% specificity and sensitivity (AUC = 1.00, 95% CI) for the diagnosis of breast cancer patients.

conclusionAccording to our data as well as other observations, the S100A8/A9 heterodimer can be considered as a potential biomarker for the proper diagnosis and prognosis of breast cancer.

Indexed as

Breast cancerEnzyme-linkedimmunosorbent assaySerumTumor marker

Identifiers

PMID31528166
PMCPMC6679667
OpenAlexW2958399300

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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.