Development and Validation of a Predictive Score for Preoperative Diagnosis of Early Stage Epithelial Ovarian Cancer

Abstract

Objective: To develop and validate a simplified multi-parameter risk-based scoring system for preoperative diagnosis<br />of early stage epithelial ovarian cancer. Methods: All women presented with adnexal mass and were scheduled for<br />operation at Phrapokklao hospital during September 2013 – December 2017 were included and categorized according<br />to their histopathologic reports into early stage ovarian cancer groups and benign ovarian tumor groups. Multivariable<br />logistic regression was used to explore for potential predictors. The selected logistic coefficients were transformed<br />into risk-based scoring system. Internal validation was done with bootstrapping procedure. Results: A total of 270<br />participants were included in analysis and predictive model development, 54 in early stage ovarian cancer group and<br />216 in benign ovarian tumor group. Menopausal status, two abnormal ultrasound findings (presence of solid component<br />or ascites), tumor size and serum CA-125 level were used for derivation of the scoring system. The score-based model<br />showed area under ROC of 0.88 (95%CI 0.82-0.93). The developed scoring system ranged from 0 to 51 was classified<br />into 3 subcategories for clinical practicability. The positive predictive values for the presence of early stage ovarian<br />cancer were 2.07 (95%CI 0.43-6.05) for low risk patient, 29.13(95%CI 19.65-41.58) for moderate risk patient, and<br />95.45(95%CI 77.16-99.88) for high risk patient. Conclusion: This simplified risk-based scoring system for preoperative<br />diagnosis of early stage ovarian cancer could aid general physicians or general gynecologists in evaluation of patients<br />presenting with ovarian tumors and help gynecologic oncologists in management planning and prioritization of patients<br />for operation.