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Five common tumor biomarkers and CEA for diagnosing early gastric cancer: A protocol for a network meta-analysis of diagnostic test accuracy

BACKGROUND: Although surgical resection is the recommended treatment for the patients with gastric cancer, lots of patients show advanced or metastatic gastric cancer at the time of diagnosis. Detection of gastric cancer at early stages is a huge challenge because of lack of appropriate detection te...

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Detalles Bibliográficos
Autores principales: Shen, Minghui, Wang, Hui, Wei, Kongyuan, Zhang, Jianling, You, Chongge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5959440/
https://www.ncbi.nlm.nih.gov/pubmed/29742692
http://dx.doi.org/10.1097/MD.0000000000010577
Descripción
Sumario:BACKGROUND: Although surgical resection is the recommended treatment for the patients with gastric cancer, lots of patients show advanced or metastatic gastric cancer at the time of diagnosis. Detection of gastric cancer at early stages is a huge challenge because of lack of appropriate detection tests. Unfortunately, existing clinical guidelines focusing on early diagnosis of gastric cancer do not provide consistent and prudent evidence. Serum carcinoembryonic antigen was considered as a complementary test, although it is not good enough to diagnose early gastric cancer. There are no other tumor markers recommended for diagnosing early gastric cancer. This study aims to evaluate and compare the diagnostic accuracy of 5 common tumor biomarkers (CA19–9, CA125, PG, IncRNA, and DNA methylation) and CEA and their combinations for diagnosing gastric cancer through network meta-analysis method, and to rank these tests using a superiority index. METHODS: PubMed, EMBASE.com, and the Cochrane Central Register of Controlled Trials (CENTRAL) will be searched from their inception to March 2018. We will include diagnostic tests which assessed the accuracy of the above-mentioned tumor biomarkers and CEA for diagnosing gastric cancer. The risk of bias for each study will be independently assessed as low, moderate, or high using criteria adapted from Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Network meta-analysis will be performed using STATA 12.0 and R 3.4.1 software. The competing diagnostic tests will be ranked by a superiority index. RESULTS: This study is ongoing and will be submitted to a peer-reviewed journal for publication. CONCLUSION: This study will provide systematically suggestions to select different tumor biomarkers for detecting the early gastric cancer.