文献类型：期刊文献

英文题名：CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC) A protocol for a network meta-analysis of diagnostic test accuracy

作者：Zhang, Yi[1];Ni, Jinman[1];Wei, Kongyuan[2];Tian, Jinhui[3];Sun, Shaobo[4]

第一作者：Zhang, Yi

通信作者：Ni, JM[1]

机构：[1]Lanzhou Univ, Sch Basic Med Sci, 199 Dong Gang West Rd, Lanzhou, Gansu, Peoples R China;[2]Lanzhou Univ, Affiliated Hosp 1, Dept Gen Surg, Lanzhou, Gansu, Peoples R China;[3]Lanzhou Univ, Evidence Based Med Ctr, Sch Basic Med Sci, Lanzhou, Gansu, Peoples R China;[4]Lanzhou Univ, Gansu Univ Chinese Med, Lanzhou, Gansu, Peoples R China

第一机构：Lanzhou Univ, Sch Basic Med Sci, 199 Dong Gang West Rd, Lanzhou, Gansu, Peoples R China

通信机构：[1]corresponding author), Lanzhou Univ, Sch Basic Med Sci, 199 Dong Gang West Rd, Lanzhou, Gansu, Peoples R China.

年份：2018

卷号：97

期号：38

外文期刊名：MEDICINE

收录：;Scopus(收录号：2-s2.0-85054023772);WOS:【SCI-EXPANDED(收录号:WOS:000449338200053)】；

语种：英文

外文关键词：CT; F-18 FDG PET; MRI; network meta-analysis; non-small-cell lung cancer; sensitivity; specificity

摘要：Background: Non-small-cell lung cancer (NSCLC) is a rare cancer in lung carcinomas and has been widely known as a difficult curable disease among all the tumors. However, early detection of malignant potential in patients with NSCLC has still been a huge challenge all around the world. CT, MRI, and F-18 FDG PET are all considered as good tests for diagnosing malignant NSCLC efficiently, but no recommended suggestion presents that which test among the 3 is the prior one in diagnose. We perform this study through network meta-analysis method, and to rank these tests using a superiority index. Methods and analysis: 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 CT, MRI, and F-18 FDG PET for diagnosing NSCLC. 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 diagnostic measures for detecting the early NSCLC. Ethics and dissemination: Ethical approval and patient consent are not required since this study is a network meta-analysis based on published studies. The results of this network meta-analysis will be submitted to a peer-reviewed journal for publication.