Evaluating the incremental diagnostic value of systemic inflammatory response markers and estimating the ma-lignant probability in patients with ovarian masses: development of a diagnostic nomogram

Purpose To investigate the incremental value of systemic inflammatory response markers in the differential diagnosis of ovarian masses and develop a nomogram integrating systemic inflammatory markers and ultrasound features to predict ovarian malignancy in patients with ovarian masses.Methods 1087 eligible women with ovarian masses were randomly allocated to a training cohort (N=761) and validation cohort (N=326).

The LASSO logistic regression was implemented to select the most significant ovarian cancer-related predictors. Multivariable logistic regressions were then performed to build different prediction models. The model with best performance was presented as a nomogram and compared with reference ovarian cancer prediction tools in terms of discrimination ability.Results Seven variables including age, CA125, HE4, fibrinogen (FIB), monocyte-to-lymphocyte ratio (MLR), the presence of solid areas and strong blood flow signal were identified as significant predictors.