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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: METHODS, RESULTS. Meshes: Adult, Algorithms, Biomarkers, Tumor, CA-125 Antigen, Cross-Sectional Studies, Female, Humans, Middle Aged, Ovarian Neoplasms, Pelvic Neoplasms, Predictive Value of Tests, Proteins, Risk, Ultrasonography.
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Is the Risk of Ovarian Malignancy Algorithm Better Than Other Tests for Predicting Ovarian Malignancy in Women with Pelvic Masses? Context: Pelvic US, serum CA125 and HE4 levels were investigated preoperatively in consecutively enrolled Thai women over 18 years with clinically diagnosed pelvic or adnexal masses who were undergoing elective surgery at a super tertiary hospital in Thailand in 2012. ROMA, RMI and Sassone US score were calculated. Of 260 women who were evaluated, 74 had OC. Areas under the receiver operating characteristic curve (AUC) in predicting OC were ROMA, 86.2%; RMI, 87.6%; CA125, 80.6%; HE4, 82.4%; and Sassone score, 77.1%. ROMA and RMI performed similarly well (AUCs 84.4 and 85.6%) in premenopausal women but RMI outperformed ROMA in postmenopausal women (AUCs 87.9 and 84.0%, respectively). At the conventional cutoff value, ROMA and CA125 showed the highest sensitivity (83.8%) but HE4 had the highest specificity (86.0%).
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ROMA was comparable to RMI in predicting OC. Either ROMA or RMI can be applied to women with pelvic masses, stratified into low- and high-risk groups for OCs.