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Hormonal biomarkers for the noninvasive diagnosis of endometriosis: A protocol for a network meta-analysis of diagnostic test accuracy.

MEDICINE(2018)

Cited 2|Views5
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Abstract
Background: Endometriosis is a major cause of disability and compromised the quality of life in women and teenage girls. The gold standard for diagnosis ofendometriosis is laparoscopy with histology of excised endometriosis lesions. However, women can suffer for 8 to 12 years before obtaining a correct diagnosis. Several biomarkers showed good diagnostic value for endometriosis, but no studies directly or indirectly compare the diagnostic value of different biomarkers. We perform this network meta-analysis (NMA) to assess the diagnostic accuracy of hormonal biomarkers, and to find a most effective hormonal biomarker for the diagnosis of endometriosis. Methods: A systematic search will be performed using PubMed, EMBASE, Cochrane Library and Chinese Biomedicine Literature to identify relevant studies from inception to August 2018. We will include random controlled trials, cross-sectional studies, case-control studies, and cohort studies that evaluated the diagnostic accuracy of hormonal markers for endometriosis. The Quality Assessment of Diagnostic Accuracy Studies 2 quality assessment tool will be used to assess the risk of bias in each study. Standard pairwise meta-analysis and NMA will be performed using STATA V. 12.0, MetaDiSc 1.40 and R 3.4.1 software to compare the diagnostic efficacy of different hormonal biomarkers. Results: The results of this study will be published in a peer-reviewed journal. Conclusion: This study will summarize the direct and indirect evidence to determine the diagnostic accuracy of the hormonal biomarkers for endometriosis and attempt to find a most effective biomarker for the diagnosis of endometriosis. Ethics and dissemination: Ethics approval and patient consent are not required as this study is a meta-analysis based on published studies. PROSPERO registration number: CRD42018105126.
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Key words
diagnostic test accuracy,endometriosis,hormonal biomarkers,network meta-analysis
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