A nomogram including NT-proBNP predicted 3-year major adverse cardiovascular events in renal transplant recipients with AUC 0.838, improving existing risk models.
Does a preoperative nomogram incorporating NT-proBNP improve the prediction of major adverse cardiovascular events in renal transplant recipients?
A preoperative nomogram incorporating NT-proBNP significantly improves the prediction of major adverse cardiovascular events in renal transplant recipients.
Absolute Event Rate: 0% vs 0%
ABSTRACT Background N‐terminal pro‐brain natriuretic peptide (NT‐proBNP) has shown increasing prognostic value in renal transplant recipients (RTRs). This study aimed to develop and validate a preoperative nomogram incorporating NT‐proBNP to predict major adverse cardiovascular events (MACEs) in RTRs. Methods A total of 582 eligible RTRs from The First Affiliated Hospital of Sun Yat‐sen University were enrolled as the training cohort, and 181 RTRs from the Huangpu Branch were included as the validation cohort. The predictive value of NT‐proBNP was assessed through correlation analyses with other cardiovascular risk factors and by comparing existing risk models with and without NT‐proBNP. A least absolute shrinkage and selection operator (LASSO)‐Cox regression approach was used to develop the nomogram, and model performance was rigorously evaluated using receiver operating characteristic curves, concordance index, calibration curves, decision curve analysis, net reclassification improvement, and integrated discrimination improvement. Results The incorporation of NT‐proBNP significantly improved model performance, leading to the development of a new preoperative nomogram that included NT‐proBNP, age, body mass index, diabetes, and retransplantation as predictors. This model achieved a 3‐year area under the receiver operating characteristic curve of 0.838 (95% confidence interval: 0.792–0.884) and demonstrated good discrimination, calibration, and clinical utility in both cohorts. Furthermore, it showed superior predictive performance compared with existing models, as confirmed by the comprehensive evaluation metrics. Conclusions A preoperative nomogram incorporating NT‐proBNP demonstrated good predictive performance for MACEs in RTRs and may also serve as an effective means to enhance existing cardiovascular risk prediction models.
Wu et al. (Thu,) reported a other. A nomogram including NT-proBNP predicted 3-year major adverse cardiovascular events in renal transplant recipients with AUC 0.838, improving existing risk models.