Evidence map›Paper›PMID 36974566›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2023

miRNA-21 as High Potential Prostate Cancer Biomarker in Prostate Cancer Patients in Indonesia.

Regina R Gunawan, Indwiani Astuti, H Raden Danarto

Open access · goldAbstract read
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 8 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.

Regina R GunawanFaculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Indwiani AstutiDepartment of Pharmacology and Therapy, Universitas Gadjah Mada, Yogyakarta, Indonesia.
H Raden DanartoDepartment of Surgery, Division of Urology, Sardjito General Hospital, Indonesia.
Universitas Gadjah Mada · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to explore the diagnostic performance of miRNA-21 to differentiate between Prostate Cancer (PCa) and Benign Prostatic Hyperplasia (BPH) patients in Indonesia.

methodsUrine samples were collected from each PCa and BPH patient. miRNA-21 relative expression against the reference gene was analyzed and compared between the two. miRNA expression was then analyzed using the comparative quantification method to find the fold change. miR-21 validity in identifying PCa patients was performed by quantifying the sensitivity and specificity using samples in this study.

resultThe results of this study indicated that miRNA-21 relative expression against miRNA-16 in PCa and BPH showed 12.95 differences in fold change. Moreover, using prostate biopsy as the gold standard to differentiate PCa and BPH, miRNA-21 Cq expression has 100% sensitivity and 75% specificity in differentiating the two.

conclusionmiRNA-21 relative expression can be used to discriminate PCa from BPH by using a urine sample. Furthermore, the expression of miR-21 has higher sensitivity than PSA; therefore, miR-21 has a high potential to be analyzed and developed further for clinical diagnosis of prostate cancer.

Indexed as

MicroRNAsProstatic HyperplasiaProstatic NeoplasmsBiomarkers, TumorHumansIndonesiaMaleProstateProstate-Specific AntigenBiomarkers, TumorMicroRNAsMIRN16 microRNA, humanMIRN21 microRNA, humanProstate-Specific AntigenBenign prostate hyperplasiaBiomarkermiRNA-21Prostate Cancer

Identifiers

PMID36974566
PMCPMC10334082
OpenAlexW4361214881

What OpenQuestion holds

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LicenceCC BY-NC
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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.