Shen Minghui, Gao Ya, Ma Xueni, Wang Bo, Wu Jiarui, Wang Jiancheng, Li Jipin, Tian Jinhui, Jia Junhai
Department of Clinical Laboratory, Second Hospital of Lanzhou University.
Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University.
Medicine (Baltimore). 2018 Oct;97(42):e12898. doi: 10.1097/MD.0000000000012898.
Endometriosis is a major cause of disability and compromised the quality of life in women and teenage girls. The gold standard for diagnosis of endometriosis 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.
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.
The results of this study will be published in a peer-reviewed journal.
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 approval and patient consent are not required as this study is a meta-analysis based on published studies.
CRD42018105126.
子宫内膜异位症是导致女性和少女残疾及生活质量下降的主要原因。子宫内膜异位症诊断的金标准是腹腔镜检查及对切除的子宫内膜异位症病灶进行组织学检查。然而，女性在获得正确诊断之前可能要忍受8至12年的病痛。几种生物标志物对子宫内膜异位症显示出良好的诊断价值，但尚无研究直接或间接比较不同生物标志物的诊断价值。我们进行这项网络荟萃分析（NMA）以评估激素生物标志物的诊断准确性，并寻找用于诊断子宫内膜异位症的最有效激素生物标志物。
将使用PubMed、EMBASE、Cochrane图书馆和中国生物医学文献数据库进行系统检索，以识别从开始到2018年8月期间的相关研究。我们将纳入评估激素标志物对子宫内膜异位症诊断准确性的随机对照试验、横断面研究、病例对照研究和队列研究。将使用诊断准确性研究质量评估2质量评估工具评估每项研究中的偏倚风险。将使用STATA V.12.0、MetaDiSc 1.40和R 3.4.1软件进行标准的成对荟萃分析和NMA，以比较不同激素生物标志物的诊断效能。
本研究结果将发表在同行评审期刊上。
本研究将总结直接和间接证据，以确定激素生物标志物对子宫内膜异位症的诊断准确性，并尝试寻找用于诊断子宫内膜异位症的最有效生物标志物。
由于本研究是基于已发表研究的荟萃分析，因此无需伦理批准和患者同意。
PROSPERO注册号：CRD42018105126。
