Key Points: Prediction models are becoming increasingly relevant in precision medicine. These models should be highly performant and not negatively affected by competing risk events. We thus aimed to carefully assess the effect of competing risks in allograft failure prediction. Background: Prognostic models are becoming increasingly relevant in clinical trials as potential surrogate end points and for patient management as clinical decision support tools. However, the effect of competing risks on model performance remains poorly investigated. We aimed to carefully assess the performance of competing risk and noncompeting risk models in the context of kidney transplantation, where allograft failure and death with a functioning graft are two competing outcomes. Methods: We included 11,046 kidney transplant recipients enrolled in ten countries. We developed prediction models for long-term kidney graft failure prediction, without accounting ( i.e ., censoring) and accounting for the competing risk of death with a functioning graft, using Cox, Fine–Gray, and cause-specific Cox regression models. To this aim, we followed a detailed and transparent analytical framework for competing and noncompeting risk modeling and carefully assessed the models' development, stability, discrimination, calibration, overall fit, clinical utility, and generalizability in external validation cohorts and subpopulations. More than 15 metrics were used to provide an exhaustive assessment of model performance. Results: Among 11,046 recipients in the derivation and validation cohorts, 1497 (14%) lost their graft and 1003 (9%) died with a functioning graft after a median follow-up postrisk evaluation of 4.7 years (interquartile range, 2.7–7.0). The cumulative incidence of graft loss was similarly estimated by Kaplan–Meier and Aalen–Johansen methods (17% versus 16% in the derivation cohort). Cox and competing risk models showed similar and stable risk estimates for predicting long-term graft failure (average mean absolute prediction error of 0.0140, 0.0138, and 0.0135 for Cox, Fine–Gray, and cause-specific Cox models, respectively). Discrimination and overall fit were comparable in the validation cohorts, with concordance index ranging from 0.76 to 0.87. Across various subpopulations and clinical scenarios, the models performed well and similarly, although in some high-risk groups (such as donors older than 65 years), the findings suggest a trend toward moderately improved calibration when using a competing risk approach. Conclusions: Competing and noncompeting risk models performed similarly in predicting long-term kidney graft failure.

Current knowledge on histopathological changes occurring after COVID‐19 in transplanted kidneys is limited. Herein, we present renal allograft pathology findings in patients recovered from COVID‐19.Six patients underwent indication biopsy, and one required allograft nephrectomy after acute COVID‐19. Demographic data, clinical characteristics, and laboratory findings were recorded. The histopathological analysis included light microscopy, immunostaining, and electron microscopy.Five patients were hospitalized for acute COVID‐19, and all were diagnosed with imaging‐confirmed pneumonia, one requiring mechanical ventilation, and two requiring dialysis. Two patients had mild form. Histopathologic examination of renal allograft specimens revealed collapsing, perihilar, tip‐lesion and secondary FSGS in one patient each. One patient had borderline acute cellular rejection, and two had chronic antibody‐mediated rejection. Histopathologic changes of glomerular tufts were accompanied by acute tubular injury in four patients. None of our patients had signs of viral inclusions in kidney cells.One patient died and one remained dialysis‐dependent after the good initial response to treatment. Patients with collapsing and perihilar FSGS had further progression of their chronic allograft nephropathy still without need for dialysis.In conclusion, diverse kidney pathology may be found in SARS‐CoV‐2–infected renal transplant patients. It seems that viral infection may affect the immune system with triggering of glomerular diseases, while the acute tubular injury is of multifactorial etiology. Direct viral effect is less likely.