Evidence map›Paper›PMID 25081587›Full record

SynthesisMolecular neurobiology2015

MicroRNAs as Potential Biomarkers for Diagnosing Cancers of Central Nervous System: a Meta-analysis.

Dong Wei, Qun Wan, Li Li, Haifeng Jin, Yonghong Liu, Yangang Wang, Guangyun Zhang

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Molecular neurobiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 3 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

23 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  8. Liquid Biomarkers for Improved Diagnosis and Classification of CNS Tumors.International journal of molecular sciences · 2021
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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

7 authors.

Dong WeiDepartment of Neurology, Xijing Hospital, The Fourth Military Medical University, 127 Changle Western Road, Xi'an, Shaanxi Province, 710032, China.
Qun Wan
Li Li
Haifeng Jin
Yonghong Liu
Yangang Wang
Guangyun Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies have shown abnormal microRNA (miRNA) expression levels in the central nervous system (CNS) of cancer patients, suggesting that miRNAs may serve as promising biomarkers for cancers of CNS. However, other studies have arrived at conflicting results. Therefore, this meta-analysis aims to systematically measure the potential diagnostic value of miRNAs for CNS cancers. Electronic databases as well as other sources were searched until to April 12, 2014 for relevant articles. Data from different studies were pooled using the random-effects model. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative LR (NLR), diagnostic odds ratio (DOR), together with the summary receiver operator characteristic (SROC) curve, and area under the SROC curve (AUC) value were used to estimate overall diagnostic performance. Twenty-three studies from 6 articles were included in the current meta-analysis with a total of 299 CNS cancer patients and 418 controls. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.85 (95% CI, 0.80-0.89), 0.83 (95% CI, 0.76-0.88), 5.1 (95% CI, 3.4-7.5), 0.18 (95% CI, 0.12-0.26), 28 (95% CI, 14-58), and 0.91 (95% CI, 0.88-0.93), respectively. Subgroup analyses showed that cerebrospinal fluid (CSF)-based miRNAs assays yielded more accurate results and seemed to be more sensitive in diagnosing of primary central nervous system lymphoma (PCNSL). In conclusion, miRNAs may be suitable for serving as noninvasive biomarkers for CNS cancers detection. However, further validation based on a larger sample of patients and controls is still required.

Indexed as

Biomarkers, TumorCentral Nervous System NeoplasmsHumansMicroRNAsROC CurveSensitivity and SpecificityBiomarkers, TumorMicroRNAs

Identifiers

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.