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Research article
Mahmood Barati
Iran University of Medical Sciences
Corresponding Author
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Glioblastoma (GBM) is the most malignant glioma cancer with a high morbidity and mortality worldwide. Unfortunately, a routine method is not available for screening or preoperative early detection of GBM. However, early detection in a none-invasive or minimally invasive method could be beneficial and increase the survival rate. In this systematic review and meta-analysis, we aimed to examine the diagnostic accuracy of exosomal RNAs that were extracted from patients’ CSF or serum for GBM diagnosis. We searched Web of Science, Scopus, PubMed (including Medline), Embase and ProQuest (as databases for grey literature) up to December 2019; we also performed backward and forward reference checking of included and relevant studies. Finally, included studies were assessed with QUADAS-2 checklist and their data extracted. We carried out a meta-analysis of included study, regarding to the diagnostic meta-analysis guidelines for obtaining pooled accuracy estimates. In addition, sensitivity analysis and meta-regression were also conducted. We retrived 1730 records from databases, nine of them included in systematic review and qualitative synthesis. Six studies were considered to statistical analysis and performed diagnostic meta-analysis. Our results suggested that the pooled sensitivity and specificity of exosomal biomarkers for GBM were 0.76 and 0.80, respectively. In addition, the pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were 3.7, 0.30 and 12, respectively. The overall area under the curve (AUC) of exosomal biomarkers for GBM diagnosis was found to be 0.85. According to our results, the value of 0.85 for AUC, suggesting that exosomal biomarkers might serve as a high potential and non-invasive diagnostic tool for GBM.
Keywords
Biomarkers, Diagnosis, Exosomes, Extracellular vesicles, Glioblastoma, Meta-analysis
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A new preprint design is coming!
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research article
Mahmood Barati
Iran University of Medical Sciences
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 10 Feb, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Glioblastoma (GBM) is the most malignant glioma cancer with a high morbidity and mortality worldwide. Unfortunately, a routine method is not available for screening or preoperative early detection of GBM. However, early detection in a none-invasive or minimally invasive method could be beneficial and increase the survival rate. In this systematic review and meta-analysis, we aimed to examine the diagnostic accuracy of exosomal RNAs that were extracted from patients’ CSF or serum for GBM diagnosis. We searched Web of Science, Scopus, PubMed (including Medline), Embase and ProQuest (as databases for grey literature) up to December 2019; we also performed backward and forward reference checking of included and relevant studies. Finally, included studies were assessed with QUADAS-2 checklist and their data extracted. We carried out a meta-analysis of included study, regarding to the diagnostic meta-analysis guidelines for obtaining pooled accuracy estimates. In addition, sensitivity analysis and meta-regression were also conducted. We retrived 1730 records from databases, nine of them included in systematic review and qualitative synthesis. Six studies were considered to statistical analysis and performed diagnostic meta-analysis. Our results suggested that the pooled sensitivity and specificity of exosomal biomarkers for GBM were 0.76 and 0.80, respectively. In addition, the pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were 3.7, 0.30 and 12, respectively. The overall area under the curve (AUC) of exosomal biomarkers for GBM diagnosis was found to be 0.85. According to our results, the value of 0.85 for AUC, suggesting that exosomal biomarkers might serve as a high potential and non-invasive diagnostic tool for GBM.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
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