title: Usefulness of diagnostic indices comprising clinical, sonographic, and biomarker data for discriminating benign from malignant ovarian masses.
abstract: The objective of this study was to review the accuracy of indices combining several diagnostic variables, in comparison to other models, sonography alone, and biomarker assays, for predicting benign or malignant ovarian lesions. Different single modalities were reviewed. The most useful complex models were International Ovarian Tumor Analysis (IOTA) sonographic logistic regression model 2 (area under the curve, 0.949), risk of malignancy index-cancer antigen 125-human epididymis protein 4 (0.950), risk of malignancy algorithm (0.953), pelvic mass score (0.960), non-IOTA logistic regression model (0.970), and histoscanning score logistic regression model (0.970). None of the indices was superior to an expert subjective sonographic assessment (0.968). For women with adnexal tumors, indices with high accuracy are available that are applicable in clinical practice and comparable to an expert subjective sonographic assessment for discriminating benign from malignant masses.
authors.affiliation: Department of Gynecological Oncology, Gdynia Oncology Center, Gdynia, Poland (M.S., M.D.); Information Technology Department, Business Consulting Center, Gdansk, Poland (K.R.); and Department of Gynecology and Gynecological Oncology, Kliniken-Essen-Mitte, Essen, Germany (J.P.G.). maciej.stukan@gmail.com.
authors.forename: Maciej
authors.initials: M
authors.lastname: Stukan
authors.affiliation: Department of Gynecological Oncology, Gdynia Oncology Center, Gdynia, Poland (M.S., M.D.); Information Technology Department, Business Consulting Center, Gdansk, Poland (K.R.); and Department of Gynecology and Gynecological Oncology, Kliniken-Essen-Mitte, Essen, Germany (J.P.G.).
authors.forename: Miroslaw
authors.initials: M
authors.lastname: Dudziak
authors.affiliation: Department of Gynecological Oncology, Gdynia Oncology Center, Gdynia, Poland (M.S., M.D.); Information Technology Department, Business Consulting Center, Gdansk, Poland (K.R.); and Department of Gynecology and Gynecological Oncology, Kliniken-Essen-Mitte, Essen, Germany (J.P.G.).
authors.forename: Karol
authors.initials: K
authors.lastname: Ratajczak
authors.affiliation: Department of Gynecological Oncology, Gdynia Oncology Center, Gdynia, Poland (M.S., M.D.); Information Technology Department, Business Consulting Center, Gdansk, Poland (K.R.); and Department of Gynecology and Gynecological Oncology, Kliniken-Essen-Mitte, Essen, Germany (J.P.G.).
authors.forename: Jacek P
authors.initials: JP
authors.lastname: Grabowski
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000097:blood*; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008875:Middle Aged; D015588:Observer Variation; D010051:Ovarian Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000453:epidemiology*; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014463:Ultrasonography / Q000706:statistics & numerical data*; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor
keywords: algorithm; gynecologic ultrasound; index; ovarian neoplasm; risk of malignancy; score; sonography