title: Comparison of the risk of malignancy index and self-constructed logistic regression models in preoperative evaluation of adnexal masses.
abstract: OBJECTIVE
  The aim of this study was to evaluate women with adnexal masses in the preoperative period by creating 2 logistic regression models, 1 including sonographic morphologic characteristics and the other including both morphologic and color Doppler characteristics, to compare the diagnostic accuracy of these 2 models with the risk of malignancy index (RMI).
  
  
  METHODS
  This prospective study included 38 malignant, 7 borderline, and 244 benign ovarian masses. The menopausal status, presence of septa, presence of papillary projections, location of the tumor, presence of ascites, presence of metastases, cancer antigen 125 level, tumor volume, septa thickness, and percentage of the solid component were included in the initial analysis. A second regression analysis was performed with the addition of Doppler parameters (location of blood flow and lowest resistive index) in the data set. Diagnostic performance of the 2 regression models and RMI were described and compared by generating receiver operating characteristic curves for each model.
  
  
  RESULTS
  The area under the curve values for the morphologic model (model 1), Doppler model (model 2), and RMI were 0.907, 0.971, and 0.889, respectively. Significance levels of model 1 and the RMI were similar (P = .23), whereas model 2 had a significantly higher area under the curve compared with both model 1 (P = .037) and the RMI (P = .018).
  
  
  CONCLUSIONS
  The addition of Doppler parameters in the regression model significantly increases the predictive performance. Nevertheless, in low-resource settings, the RMI remains the method of choice for distinguishing adnexal masses and referral to gynecologic oncology clinics.
authors.affiliation: Department ofObstetrics and Gynecology, Marmara University, Istanbul, Turkey. pinyoruk@gmail.com. pinyoruk@gmail.com
authors.forename: Pynar
authors.initials: P
authors.lastname: Yörük
authors.forename: Ozgür
authors.initials: O
authors.lastname: Dündar
authors.forename: Begüm
authors.initials: B
authors.lastname: Yildizhan
authors.forename: Levent
authors.initials: L
authors.lastname: Tütüncü
authors.forename: Tanju
authors.initials: T
authors.lastname: Pekin
mesh_terms: D000291:Adnexal Diseases / Q000000981:diagnostic imaging* / Q000453:epidemiology* / Q000601:surgery; D000328:Adult; D005260:Female; D006801:Humans; D008875:Middle Aged; D011300:Preoperative Care / Q000379:methods / Q000706:statistics & numerical data; D015995:Prevalence; D016016:Proportional Hazards Models; D012044:Regression Analysis; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012680:Sensitivity and Specificity; D014421:Turkey / Q000453:epidemiology; D014463:Ultrasonography / Q000706:statistics & numerical data*