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Background To develop and validate predictive nomograms for 5-year graft survival in kidney transplant recipients (KTRs) with easily-available laboratory data derived markers and clinical variables within the first year post-transplant. Methods The clinical and routine laboratory data from within the first year post-transplant of 1289 KTRs was collected to generate candidate predictors. Univariate and multivariate Cox analyses and LASSO were conducted to select final predictors. X-tile analysis was applied to identify optimal cutoff values to transform potential continuous factors into category variables and stratify patients. C-index, calibration curve, dynamic time-dependent AUC, decision curve analysis, and Kaplan-Meier curves were used to evaluate models' predictive accuracy and clinical utility. Results Two predictive nomograms were constructed by using 0-6- and 0-12- month laboratory data, and showed good predictive performance with C-indexes of 0.78 and 0.85, respectively, in the training cohort. Calibration curves showed that the prediction probabilities of 5-year graft survival were in concordance with actual observations. Additionally, KTRs could be successfully stratified into three risk groups by nomograms. Conclusions These predictive nomograms combining demographic and 0-6- or 0-12- month markers derived from post-transplant laboratory data could serve as useful tools for early identification of 5-year graft survival probability in individual KTRs.

The roles of PD-182 KTRs were enrolled in this study. 45 KTRs were included in the chronic allograft dysfunction (CAD) group, and 37 KTRs were included in the stable recipients group. Among the CAD group, 12 cases of antibody-mediated rejection (ABMR) and 4 cases of T cell-mediated rejection (TCMR) were diagnosed by biopsy. The percentage of CXCR5The expression of CXCR5 on CD3Our results suggested that PD-1