Fig. 1

Development of the ovarian cancer screening model (model 1). a Work flow of patients for developing prediction model 1. Serum samples were obtained from 3007 subjects, including 428 patients with ovarian tumors and 2759 non-cancer donors. The sample set was divided into two groups, the discovery set and validation set. b ROC curves for detecting cancer patients using a combination of ten miRNAs selected for prediction model 1. c Diagnostic performance of the ten selected miRNAs in the discovery set and validation set. d Diagnostic index using prediction model 1 in the validation set (ovarian cancer, 160; non-cancer A, 109; non-cancer B, 789; non-cancer C, 482; non-epithelial ovarian cancer, 13; borderline ovarian tumor, 66; and benign ovarian tumor, 29). Each diagnostic accuracy (%) is included. p values were calculated by χ² test. e Diagnostic index for each FIGO stage using prediction model 1. Each diagnostic accuracy (%) is indicated. N = stage I, 82; stage II, 33; and stage III–IV, 218. The p value was calculated using Pearson’s correlation analysis