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|dc.description.abstract||Background: To compare diagnostic performance in differentiating benign from malignant ovarian masses between IOTA (the International Ovarian Tumor Analysis) simple rules and subjective sonographic assessment. Materials and Methods: Women scheduled for elective surgery because of ovarian masses were recruited into the study and underwent ultrasound examination within 24 hours of surgery to apply the IOTA simple rules by general gynecologists and to record video clips for subjective assessment by an experienced sonographer. The diagnostic performance of the IOTA rules and subjective assessment for differentiation between benign and malignant masses was compared. The gold standard diagnosis was pathological or operative findings. Results: A total of 150 ovarian masses were covered, comprising 105 (70%) benign and 45 (30%) malignant. Of them, the IOTA simple rules could be applied in 119 (79.3%) and were inconclusive in 31 (20.7%) whereas subjective assessment could be applied in all cases (100%). The sensitivity and the specificity of the IOTA simple rules and subjective assessment were not significantly different, 82.9% vs 86.7% and 94.0% vs 94.3% respectively. The agreement of the two methods in prediction was high with a Kappa index of 0.835. Conclusions: Both techniques had a high diagnostic performance in differentiation between benign and malignant ovarian masses but the IOTA rules had a relatively high rate of inconclusive results. The IOTA rules can be used as an effective screening technique by general gynecologists but when the results are inconclusive they should consult experienced sonographers.||en_US|
|dc.subject||Biochemistry, Genetics and Molecular Biology||en_US|
|dc.title||Comparison of effectiveness in differentiating benign from malignant ovarian masses between IOTA simple rules and subjective sonographic assessment||en_US|
|article.title.sourcetitle||Asian Pacific Journal of Cancer Prevention||en_US|
|article.stream.affiliations||Chiang Mai University||en_US|
|Appears in Collections:||CMUL: Journal Articles|
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