Evidence map›Paper›PMID 29945348›Full record

ArticleCancer biomarkers : section A of Disease markers2018

Identification of serum miR-34a as a potential biomarker in acute myeloid leukemia.

Yiqun Huang, Yong Zou, Luhui Lin, Xudong Ma, Hongpu Chen

Abstract read
In one paragraph

Article in Cancer biomarkers : section A of Disease markers, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 17% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

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  11. Identification of Acute Myeloid Leukemia Bone Marrow Circulating MicroRNAs.International journal of molecular sciences · 2020
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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

5 authors.

Yiqun Huang
Yong Zou
Luhui Lin
Xudong Ma
Hongpu Chen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMicroRNA-34a (miR-34a), as a tumor-suppressive miRNA, has been found to induce cell apoptosis in acute myeloid leukemia (AML). However, the diagnostic and prognostic significance of miR-34a in AML remains largely unknown.

objectiveWe aimed to explore its associations with clinical characteristics and prognosis of AML patients.

methodsThis study detected serum miR-34a level in 117 diagnosed AML patients and 60 control subjects by using qRT-PCR, and results were compared to clinical features and patient outcome. Since cytogenetically-normal AML (CN-AML) has a good uniformity of cytogenetics and provides a perfect platform for detection of AML biomarkers, we further analyzed miR-34a expression in 56 CN-AML subjects.

resultsWe found that miR-34a was significantly downregulated in AML and CN-AML patients. MiR-34a underexpression was commonly observed in AML patients with intermediate/poor risk cytogenetic, and M5 subtype. ROC analysis demonstrated that serum miR-34a could well identify AML/CN-AML patients from healthy individuals. More importantly, miR-34a expression was found negatively correlated with aggressive clinical variable, and served as an independent prognostic indicator. In addition, AML/CN-AML patients with low miR-34a expression displayed shorter overall and recurrence free survival.

conclusionsAltogether, miR-34a might have an application as a diagnostic and prognostic indicator for AML patients.

Indexed as

PrognosisAdultAgedBiomarkers, TumorDisease-Free SurvivalFemaleGene Expression Regulation, LeukemicHumansKaplan-Meier EstimateLeukemia, Myeloid, AcuteMaleMicroRNAsMiddle AgedBiomarkers, TumorMicroRNAsMIRN34 microRNA, humanacute myeloid leukemiabiomarkerdiagnosismiR-34aprognosis

Identifiers

PMID29945348
PMCPMC13078488
OpenAlexW2809477768

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.