Evidence map›Paper›PMID 27557519›Full record

SynthesisOncotarget2016

The accuracy of microRNA-210 in diagnosing lung cancer: a systematic review and meta-analysis.

Huqin Yang, Huijuan Wang, Chao Zhang, Zhaohui Tong

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
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

4 authors.

Huqin YangDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
Huijuan WangDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
Chao ZhangDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
Zhaohui TongDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies examining the diagnostic value of microRNA-210 for lung cancer have yielded inconsistent results. Here, we performed a meta-analysis to assess the diagnostic accuracy of microRNA-210 for lung cancer. Nine eligible studies involving 993 patients (554 lung cancer patients and 439 non-cancer patients) were independently identified, and the quality of these studies was assessed according to Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) guidelines. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.66 (95% CI, 0.57 to 0.75), 0.82 (95% CI, 0.72 to 0.89), 3.64 (95% CI, 2.54 to 5.21), 0.41 (95% CI, 0.34 to 0.51) and 8.78 (95% CI, 6.10 to 12.66), respectively. The area under the summary receiver operator characteristic curve was 0.80 (95% CI, 0.76 to 0.83). These results indicated that microRNA-210 had moderate diagnostic value for lung cancer. Additional prospective studies are needed to confirm the diagnostic value of microRNA-210.

Indexed as

Gene Expression Regulation, NeoplasticHumansLung NeoplasmsMicroRNAsOdds RatioPredictive Value of TestsPrognosisProspective StudiesRegression AnalysisReproducibility of ResultsROC CurveSensitivity and SpecificityMicroRNAsMIRN210 microRNA, humandiagnosislung cancermeta-analysismicroRNA-210systematic review

Identifiers

PMID27557519
PMCPMC5325363

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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.