卵巢恶性肿瘤风险算法在女性盆腔肿块良恶性鉴别诊断价值的荟萃分析  

Diagnostic accuracy of ROMA index in diagnosing ovarian malignancy in pelvic mass patients

作　　者：罗琰 王沂峰[1] 陈高文[1] Luo Yan;Wang Yifeng;Chen Gaowen(Department of Obstetrics and Gynecology, Zhujiang Hospital of Southern Medical University, Guangzhou 510280, China)

机构地区：[1]南方医科大学珠江医院,广州510280

出　　处：《中华医学杂志》2019年第27期2141-2144,共4页National Medical Journal of China

摘　　要：目的通过循证医学方法探索卵巢恶性肿瘤风险算法(ROMA)在鉴别卵巢良恶性肿瘤的诊断效能。方法从PubMed、ISI Web of Science及Cochrane literature数据库检索,检索时间从建库至2017年12月。使用Meta-Disc进行荟萃分析,绘制受试者工作曲线(SROC)。通过STATA进行发表偏移分析及绘制漏斗图。结果共纳入8篇文献。ROMA共有8项研究纳入分析,包括3 725例病例,汇总敏感度为86%(95%CI为84%~88%);特异度为77%(95%CI为76%~79%);AUC为0.899。结论荟萃分析显示,在卵巢良恶性肿瘤鉴别诊断中ROMA的敏感度及特异度均较高,具有临床意义。Objective To evaluate ROMA in assessing malignancy risk of pelvic mass with Meta-analysis. Methods PubMed, ISI Web of Science, and Cochrane literature were searched until December 2017. Combine and analyse sensitivity, specificity, positive likelihoodratio, negative likelihood ratio, diagonistic odd ratio and AUC. Results Data of ROMA was retrieved from 8 studies, sensitivity and specificity were 86% and 77% respectively, and AUC was 0.899. Conclusion According to Meta analysis of previous studies, sensitivity and specificity of ROMA are high enough to be used as an index in setting of ovarian cancer diagnosis.

关 键 词：卵巢恶性肿瘤风险算法(ROMA) 卵巢肿瘤 鉴别诊断 

分 类 号：R737.31[医药卫生—肿瘤]