Maximum cold ischemia duration for a kidney allograft: a prediction model for allograft failure at the time of organ allocationResearch in context
Summary: Background: Many determinants of kidney allograft failure are established at the time of allocation by organ distribution agencies. At this point, the main modifiable factor is the duration of cold ischemia (CIT). Currently, no practical tool exists to determine the maximum permissible col...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | EClinicalMedicine |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589537025002548 |
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| Summary: | Summary: Background: Many determinants of kidney allograft failure are established at the time of allocation by organ distribution agencies. At this point, the main modifiable factor is the duration of cold ischemia (CIT). Currently, no practical tool exists to determine the maximum permissible cold ischemia time for a specific recipient at allocation. Methods: We analyzed two prospective cohorts of kidney transplant recipients from European centers: a derivation cohort of 7040 patients from 10 centers (Barcelona; Leuven; Oslo; Paris Necker, Lyon, Nantes, Nancy, Montpellier, Nice, Paris Saint Louis) with data collected between 2005 and 2020, and a validation cohort of 6131 patients from 6 French centers (Paris Necker, Lyon, Nantes, Nancy, Montpellier, Nice) with data collected between 2008 and 2019. The main outcome was allograft failure (return to dialysis or pre-emptive retransplantation). We assessed 26 determinants of allograft failure available at the time of allograft allocation including cold ischemia time as a modifiable factor. Prediction models were developed using a classical survival analysis and a competing risk framework. Findings: Allograft failure occurred in 16% (1113) of the derivation cohort and 14% (832) of the validation cohort. Independent determinants of allograft failure were donor age (HR 2.2 [1.9–2.6] for donors above 65 years old), previous allografts (HR 1.5 [1.3–1.6]), dialysis history (HR 1.7 [1.3–2] for Hemodialysis), diabetes (HR 1.4 [1.2–1.6]), vascular disease (HR 1.3 [1.1–1.5]), HLA-DR incompatibility (HR 1.2 [1.1–1.3]), donor serum creatinine (HR 1 [1–1]), and cold ischemia time (HR 1 [1–1]). Donor age was the strongest contributor, while cold ischemia was the only modifiable factor. These factors were combined into two predictive models of kidney allograft failure (Cox regression and Fine Gray) showing accurate calibration, and discrimination with a C-Index of 0.66 (95% CI: 0.63–0.70 at year one) on the validation cohort for the Fine Gray model. The Fine–Gray model, which accounts for the competing risks between allograft failure and patient death, was used to develop a practical tool for predicting allograft failure based on cold ischemia. Interpretation: Prediction model at the time of allocation provides a simple and practical tool which may guide organ distribution agencies and medico-surgical teams by customizing cold ischemia time for a kidney allograft transplantation. Funding: Centaure Foundation (SIREN 499,947,398–http://www.fondation-centaure.org) none of the funding sources had any role in study. |
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| ISSN: | 2589-5370 |