The Construction and Validation of a New Ovarian Malignancy Probability Score (OMPS) for Prediction of Ovarian Malignancy

Background: The best management for an ovarian mass is provided by appropriate prediction of malignancy. The aim of our study is to construct and validate a new Malignancy Probability Score based on four simple sonographic findings and age. Methods: In a cross sectional study; histopathological files of 3303 ovarian mass patients and tertiary hospitals, have reviewed within 6 years (2000-2006). Pathology, age, sonographic findings including solid area, ascetic, size and bilateralism were recorded. Logistic multivariate regression analysis SPSS18 has used to create malignancy probability scoring model. Our ovarian Malignancy Probability Score (OMPS) has constructed based on 80% of samples in a logistic regression model and has validated using the remainder of the cases. Results: Ovarian malignancy probability score (OMPS) has calculated as follow: age x 0.062 + Tumor size (cm) x 0.012+1.172(if the tumor is solid) + 1.289(if ascites is present) + 0.758(if the tumor is bilateral) Sensitivity of OMPS in prediction of malignancy with cutoff value of 3.65 score number was 77.9% and its specificity was 72.9% with Area under Curve (AUC) of 83% in ROC curve. Conclusion: OMPS is designed and tested in our research, to be proved as a simple and accurate clinical tool for ovarian malignancy prediction.