Fig. 6.

Construction of a nomogram model based on the OMAG risk signature and clinicopathological characteristics. A The confidence interval under each lambda; B The trajectory of each independent variable: the horizontal axis represents the log value of the independent variable lambda, and the vertical axis represents the coefficient of the independent variable. C Survival difference in high- and low-risk scores of the training set (TCGA-OV); D Survival difference in high- and low-risk scores of the test set (GSE132342); E The prognostic value of the 6-OMAGs signature was evaluated using the ROC curves in the training set (TCGA-OV); F The prognostic value of the 6-OMAGs signature was evaluated using the ROC curves in the test set (GSE132342). G Univariate Cox regression analyses of the 6-OMAGs and clinicopathological data; H Multivariate Cox regression analysis of the 6-OMAGs and clinicopathological data; I The nomogram model was constructed to predict the 3-, 5-, and 10-year survival of ovarian cancer patients. CStatus for person neoplasm cancer status, 0 for tumor free, 1 for with tumor; POutcome for primary therapy outcome success, 1 for complete remission/response, 2 for partial remission/response, 3 for stable disease, 4 for progressive disease. J The calibration curve of the nomogram at 1, 3, and 5 years; K The ROC curve of the nomogram at 5 years