Fig. 8

Development of the diagnostic nomogram model and efficacy assessment. A The nomogram was constructed based on the diagnostic biomarkers. B–D The ROC curve for the diagnostic performance of each candidate biomarker including SLPI (B), and MMP9 (C) and the nomogram model (D) constructed for CKD-related CAVD. E The calibration curve of nomogram model prediction in CKD-related CAVD. The dash line is marked as “Ideal”, which represents the standard curve, and is on behalf of the perfect prediction of the ideal model. The dotted line is marked as “Apparent”, which indicates the uncalibrated prediction curve, while the solid line is marked as “Bias-corrected” and represents the calibrated prediction curve. F DCA for the nomogram model. The black line is marked as “None”, which stands for the net benefit of the assumption that no patients have CAVD. The grey line is marked as “All”, which indicates the net benefit of the assumption that all patients have CAVD, and the purple line is marked as “Nomogram”, and represents the net benefit of the assumption that CKD-related CAVD are identified according to the diagnostic value of CAVD predicted by the nomogram model. G The ROC curve for the diagnostic performance of our nomogram model in predicting patients with sclerotic aortic valve from the GEO database. ROC receiver operating characteristic, DCA decision curve analysis, CAVD calcific aortic valve disease