Comparison of nine morphological scoring systems to detect ovarian malignancy

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This study prospectively compared nine gray-scale sonographic prediction models in 322 women, finding their diagnostic performances for ovarian malignancy varied with areas under ROC curves from 0.737 to 0.929.

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Abstract

PURPOSE OF INVESTIGATION: The aim of this study was to prospectively compare the diagnostic performances of nine gray-scale sonographic prediction models to detect ovarian malignancy. MATERIALS AND METHODS: Clinical data of 322 women presenting with an adnexal mass were obtained and used in nine scoring systems. For each model a ROC curve demonstrating the capacity of the model to diagnose malignancy was constructed for all cases and for the subgroups of premenopause and postmenopause. The performance of each model was expressed as area under the ROC curve, sensitivity, and specificity. RESULTS: The area under the ROC curve, sensitivity, and specificity of these models in the present study varied between 0.737 and 0.929, 70.7% and 87.9%, 60.2% and 80.3%, respectively. CONCLUSIONS: This study has revealed the usefulness of morphological scoring systems to correctly discriminate between benign and malignant pelvic masses.

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Condition tags

endometriosis

MeSH descriptors

Dysgerminoma Granulosa Cell Tumor Krukenberg Tumor Lymphoma Neoplasms, Cystic, Mucinous, and Serous Ovarian Neoplasms Abscess Abscess Abscess Abscess Adolescent Adult Aged Cystadenoma Cystadenoma Cystadenoma Cystadenoma Dysgerminoma Dysgerminoma Dysgerminoma

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europepmc
last seen: 2026-08-10T06:11:17.106188+00:00
pubmed
last seen: 2026-05-13T22:17:46.044120+00:00
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