Unilocular adnexal cysts with papillary projections but no other solid components: is there a diagnostic method that can reliably classify them as benign or malignant before surgery?

Aim To develop a logistic regression model for discrimination between benign and malignant unilocular solid cysts with papillary projections but no other solid components, and to compare its diagnostic performance with that of subjective evaluation of ultrasound findings (subjective assessment), CA 125 and the risk of malignancy index (RMI). Methods Among the 3511 adnexal masses in the International Ovarian Tumor Analysis (IOTA) database there were 252 (7%) unilocular solid cysts with papillary projections but no other solid components ('unilocular cysts with papillations'). All had been examined with transvaginal ultrasound using the IOTA standardized research protocol. The ultrasound examiner also classified each mass as certainly or probably benign, unclassifiable, or certainly or probably malignant. A logistic regression model to discriminate between benignity and malignancy was developed for all unilocular cysts with papillations (175 tumors in training set, 77 in test set) and for unilocular cysts with papillations where the ultrasound examiner was not certain about benignity/malignancy (113 tumors in training set, 53 in test set). The gold standard was the histological diagnosis of the surgically removed adnexal mass. Results A model containing six variables was developed for all unilocular cysts with papillations. The model had an area under the receiver operating characteristic curve (AUC) on the test set of 0.83 (95% CI, 0.74-0.93). The optimal risk cutoff as defined on the training set (0.35) resulted in sensitivity 69% (20/29), specificity 83% (40/48), LR+ 4.14 and LR- 0.37 on the test set. The corresponding values for subjective assessment when using the ultrasound examiner's dichotomous classification of the mass as benign or malignant were 97% (28/29), 79% (38/48), 4.63 and 0.04. A model containing four variables was developed for unilocular cysts with papillations where the ultrasound examiner was not certain about benignity/malignancy. The model had an AUC of 0.74 (95% CI, 0.60-0.88) on the test set. The optimal risk cutoff of the model as defined on the training set (0.30) resulted in sensitivity 62% (13/21), specificity 72% (23/32), LR+ 2.20 and LR- 0.53 on the test set. The corresponding values for subjective assessment were 95% (20/21), 78% (25/32), 4.35 and 0.06. CA125 and RMI had virtually no diagnostic ability. Conclusion Even though logistic regression models to predict malignancy in unilocular cysts with papillations can be developed they have at most moderate performance and are not superior to subjective assessment for discrimination between benignity and malignancy.