Rajavithi-ovarian cancer predictive score (R-OPS): A new scoring system for predicting ovarian malignancy in women presenting with a pelvic mass

• Multimodal approach represents a suitable method for predicting ovarian cancer.
• R-OPS showed good performance for predicting ovarian cancer.
• R-OPS may proper in countries with high incidence of non-serous carcinoma types.

ObjectiveTo develop a new scoring system based on menopausal status, ultrasound (US) findings, serum cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) to predict ovarian cancer (OC) in women presenting with a pelvic or adnexal mass.MethodsConsecutive female patients aged over 18 years with pelvic or adnexal masses investigated preoperatively by pelvic US, serum CA125 and HE4 who underwent elective surgery were enrolled. The “Rajavithi-Ovarian Cancer Predictive Score (R-OPS)” was developed using data from 2012 and validated using data from 2013 to 2014. The diagnosis of OC was based on pathological findings. Data were analyzed by logistic regression and area under the receiver operating characteristic curve (ROC-AUC).ResultsBased on a development set of 260 women including 74 with OC, menopausal status (M), serum CA125 and HE4, and US findings of solid lesions (U) were identified as significant predictors of OC. R-OPS = M × U × (CA125 × HE4)1/2 revealed good calibration (goodness-of-fit test, p = 0.972) and discrimination (ROC-AUC = 92.8%). Performance validation in 266 women, 82 with OC, showed good discrimination with ROC-AUC of 94.9%. Performance in the validation sample with a cutoff value of R-OPS > 330 revealed sensitivity, specificity, and positive and negative predictive values of 93.9%, 79.9%, 67.5%, and 96.7%, respectively.ConclusionsThe new R-OPS scoring system showed good discrimination between non-cancerous lesions and OC. However, a prospective study in a different setting is required to confirm these preliminary data.