Clinical value of ROMA index in diagnosis of ovarian cancer: meta-analysis
Authors Cui RL, Wang YC, Li Y, Li YG
Received 24 December 2018
Accepted for publication 4 February 2019
Published 28 March 2019 Volume 2019:11 Pages 2545—2551
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Amy Norman
Peer reviewer comments 2
Editor who approved publication: Professor Lu-Zhe Sun
Ranliang Cui,1,* Yichao Wang,2,* Ying Li,3 Yueguo Li1
1Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, China; 2Department of Clinical Laboratory Medicine, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang Province, China; 3The Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin‘s Clinical Research Center for Cancer, Tianjin, China
*These authors contributed equally to this work
Objectives: The role of retrospective analysis has evolved greatly in cancer research. We undertook this network meta-analysis to evaluate retrospectively the diagnostic value of ROMA in ovarian cancer.
Materials and methods: We systematically retrieved 56 relevant articles published about ROMA index from 2009–2018 and about ovarian cancer from China National Knowledge Infrastructure (CNKI), PubMed and EMBASE. Data were comprehensively analyzed by RevMan 5.3 and MetaDisc 12.4 software.
Results: Data of 5,954 cases were retrieved from 23 literatures. Among them, 2,117 cases were in the ovarian cancer group and 3,837 cases in the control group. The pooled estimates for the ROMA index were sensitivity: 0.90 (95% CI: 0.88–0.93), specificity: 0.91 (95% CI: 0.89–0.94), positive predictive: 0.90 (95% CI: 0.88–0.95), negative predictive: 0.93 (95% CI: 0.91–0.95), and area under ROC curve: 0.96, compared to 0.71 (95% CI: 0.56–0.82), 0.87 (95% CI: 0.80–0.92), 0.82 (95% CI: 0.78–0.86), 0.92 (95% CI: 0.90–0.94), and 0.88 of HE4, respectively.
Conclusions: This meta-analysis confirms that the risk of ovarian malignancy algorithm can facilitate the diagnosis of ovarian cancer to some extent.
Keywords: ROMA index, ovarian cancers, meta-analysis
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