Figure 5. Construction and assessment of MAGs-nomogram for predicting progression. (A) Univariate- and multivariate Cox regression analysis for screening appropriate and significant features into final nomogram model. (B) Ultilizing the glm regression algorithm, the MAGs-nomogram incorporating these four variables was developed and the TCGA-KIRC cohort was classified into high and low groups according to the median of MAGs-nomogram scores. (C) Calibration curve was drawn to depict the well curve fitting between predicted 1-year or 3-year progression events and actual observed outcomes. (D, E) Meanwhile, the AUCs of MAGs-nomogram in predicting 1-year and 3-year progression outcomes were up to 0.848 and 0.837, respectively. Survival analysis also suggested that the MAGs-nomogram was determined to be a significant predictor in PFS of ccRCC with P = 0.