Evidence map›Paper›PMID 29138575›Full record

ArticleOncoTargets and therapy2017

MicroRNAs as a novel class of diagnostic biomarkers for the detection of osteosarcoma: a meta-analysis.

Hong Liu, Ping Li, Liang Chen, Chao Jian, Zonghuan Li, Aixi Yu

Abstract read
In one paragraph

Article in OncoTargets and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

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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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. circKMT2D contributes to HExperimental and therapeutic medicine · 2020
    Article
  5. Review
  6. 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

6 authors.

Hong LiuDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, China.
Ping LiDepartment of Surgery, Experimental Surgery and Regenerative Medicine, Ludwig-Maximilians University, München, Germany.
Liang ChenDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, China.
Chao JianDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, China.
Zonghuan LiDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, China.
Aixi YuDepartment of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) have been considered as promising diagnostic biomarkers for many diseases, especially for cancers. Numerous studies have reported the value of miRNAs in the diagnosis of osteosarcoma (OS), but the results vary greatly across different studies. Therefore, we conducted this meta-analysis to assess the prospective diagnostic value of miRNAs in diagnosing OS. All relevant articles from prior to July 28, 2017 were selected from PubMed, EMBASE, Web of Science, Cochrane Library, Chinese National Knowledge Infrastructure, and Wan-fang databases. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was performed to assess the quality of each article. A random-effects model was used to pool the sensitivity and specificity of the positive likelihood ratio (PLR), negative likelihood ratio (NLR) and, diagnostic odds ratio (DOR) together with the area under the curve (AUC) to evaluate diagnostic values. Seventeen studies comprising 2,214 OS patients and 1,534 healthy humans were included in our meta-analysis. The pooled estimations indicated that the miRNAs had a high accuracy for diagnosing OS, with a sensitivity of 0.82, specificity of 0.88, PLR of 10.96, NLR of 0.20, DOR of 54.55, and AUC of 0.93. Twenty-five miRNAs were differentially expressed in OS, including 17 upregulated and 8 downregulated. These miRNAs were correlated with survival time, tumor size, cell differentiation, tumor node metastasis staging, metastasis, tumor/cell invasion, pathological type, and response to radiotherapy and chemotherapy. Several different miRNAs are expressed in OS, and some of them might be potential biomarkers for the early diagnosis of OS.

Indexed as

biomarkerdiagnosismeta-analysismiRNAsosteosarcoma

Identifiers

PMID29138575
PMCPMC5677380

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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.