Evidence map›Paper›PMID 25367880›Full record

SynthesisMolecular neurobiology2015

Circulating MicroRNA as Potential Source for Neurodegenerative Diseases Biomarkers.

Ying Zi, Zhongmin Yin, Weizhong Xiao, Xinwei Liu, Zhixiang Gao, Li Jiao, Lianfu Deng

Abstract readMeta-AnalysisReview
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 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 36% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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 at 7 institutions in 1 country.

Ying ZiShanghai Key Laboratory for Bone and Joint Disease Shanghai Institute of Traumatology and Orthopaedics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin No. 2 Road, Shanghai, 200025, China.
Zhongmin YinDepartment of Neurosurgery, 463rd Hospital of PLA, Shenyang, 110042, China.
Weizhong XiaoDepartment of Neurology, Shanghai Pudong Hospital, Fudan University, Shanghai, 201399, China.
Xinwei LiuDepartment of Orthopedics, General Hospital of Shenyang Military Area Command of PLA, Rescue Center of Severe Wound and Trauma of PLA, Shenyang, 110016, China.
Zhixiang GaoDepartment of Pharmacy, Changhai Hospital, Second Military Medical University, Shanghai, 200433, China.
Li JiaoDepartment of Urology, Changhai Hospital, Second Military Medical University, 168 Changhai Road, Shanghai, 200433, China. jiaoli_smmu@hotmail.com.
Lianfu DengShanghai Key Laboratory for Bone and Joint Disease Shanghai Institute of Traumatology and Orthopaedics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin No. 2 Road, Shanghai, 200025, China. lianfu_deng@hotmail.com.
Changhai Hospital · CNGeneral Hospital of Shenyang Military Region · CNPudong Medical Center · CNRuijin Hospital · CNSecond Military Medical University · CNShanghai Jiao Tong University · CNShenyang 242 Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An increasing number of circulating micro-ribonucleic acids (microRNAs, miRNAs) have been discovered its potential as biomarkers to diagnose neurodegenerative diseases (NDs) by many researchers. However, there were obvious inconsistencies among previous studies, and thus we performed this meta-analysis to evaluate whether miRNA is an effective biomarker with high accuracy to diagnose the NDs. PubMed, MEDLINE, EMBASE, the Cochrane Library, and other related databases were used to search eligible articles. The data of sensitivity and specificity were employed to plot the summary receiver operator characteristic (SROC) curve and calculate the area under the SROC curve (AUC). I (2) test were used to estimate the heterogeneity among different studies. In addition, the possible sources of heterogeneity were further explored by subgroup analyses and meta-regression. All analyses were performed by STATA 12.0 software. In this meta-analysis, eight publications with 459 NDs patients and 340 healthy controls were included to investigate the diagnostic performance of circulating miRNAs for NDs. The overall sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ration (NLR), and diagnostic odds ratio (DOR) were 0.83 (95% confidence interval (CI) 0.77-0.88), 0.87 (95% CI 0.83-0.89), 6.2 (95% CI 4.9-7.9), 0.19 (95% CI 0.14-0.27), 33 (95% CI 20-52), and 0.91 (95% CI: 0.88-0.93), respectively. The overall SROC curve was plotted with AUC of 0.91 (95% CI 0.88-0.93), which indicated an excellent diagnostic performance of circulating miRNA for NDs. Subgroup analysis based on miRNA profile demonstrated that multiple-miRNA assay had higher diagnostic accuracy for NDs when compared with single-miRNA assay. In conclusion, the circulating miRNAs may be the potential biomarkers in the clinical diagnosis of NDs, and the diagnostic accuracy would be better by using multiple-miRNA assay. However, large-scale studies are still needed to explore the relation between the circulating miRNA dysregulation and the pathological mechanism of NDs.

Indexed as

BiomarkersHumansMicroRNAsNeurodegenerative DiseasesPredictive Value of TestsPublication BiasROC CurveSensitivity and SpecificityWhite PeopleBiomarkersMicroRNAsCirculatingMeta-analysisMicroRNAsMolecular markerNeurodegenerative diseases

Identifiers

PMID25367880
OpenAlexW2076222342

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.