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肾移植同种异体移植物的最大冷缺血持续时间:器官分配时移植物失败的预测模型。

Maximum cold ischemia duration for a kidney allograft: a prediction model for allograft failure at the time of organ allocation.

作者信息

Gosset Clement, Barbosa Susana, Destere Alexandre, Cuozzo Sebastien, Albano Laetitia, Morelon Emmanuel, Charmetant Xavier, Le Quintrec Moglie, Serre Jean-Emmanuel, Ladrière Marc, Girerd Sophie, Masset Christophe, Anglicheau Dany, Lefaucheur Carmen, Divard Gillian, Gruden Enrico, Durand Matthieu, Kuypers Dirk, Coemans Maarten, Glaichenaus Nicolas, Bestard Oriol, Åsberg Anders, Giral Magali, Naesens Maarten, Sicard Antoine

机构信息

Laboratory of Molecular Physio Medicine (LP2M), UMR 7370, CNRS, University Côte d'Azur, Nice, France.

Department of Nephrology-Dialysis-Transplantation, University Hospital Centre of Nice, Nice, France.

出版信息

EClinicalMedicine. 2025 Jul 5;85:103322. doi: 10.1016/j.eclinm.2025.103322. eCollection 2025 Jul.

Abstract

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.

摘要

背景

肾移植失败的许多决定因素在器官分配机构进行分配时就已确定。此时,主要的可改变因素是冷缺血时间(CIT)。目前,尚无实用工具可在分配时确定特定受者的最大允许冷缺血时间。

方法

我们分析了来自欧洲中心的两个肾移植受者前瞻性队列:一个推导队列,包含来自10个中心(巴塞罗那;鲁汶;奥斯陆;巴黎内克尔、里昂、南特、南锡、蒙彼利埃、尼斯、巴黎圣路易)的7040例患者,数据收集时间为2005年至2020年;一个验证队列,包含来自6个法国中心(巴黎内克尔、里昂、南特、南锡、蒙彼利埃、尼斯)的6131例患者,数据收集时间为2008年至2019年。主要结局是移植肾失功(恢复透析或抢先再次移植)。我们评估了移植肾分配时可用的26个移植肾失功决定因素,包括作为可改变因素的冷缺血时间。使用经典生存分析和竞争风险框架开发预测模型。

结果

推导队列中16%(1113例)发生移植肾失功,验证队列中14%(832例)发生移植肾失功。移植肾失功的独立决定因素包括供者年龄(65岁以上供者的风险比[HR]为2.2[1.9 - 2.6])、既往移植(HR为1.5[1.3 - 1.6])、透析史(血液透析的HR为1.7[1.3 - 2])、糖尿病(HR为1.4[1.2 - 1.6])、血管疾病(HR为1.3[1.1 - 1.5])、HLA - DR不相容性(HR为1.2[1.1 - 1.3])、供者血清肌酐(HR为1[1 - 1])以及冷缺血时间(HR为1[1 - 1])。供者年龄是最强的影响因素,而冷缺血是唯一的可改变因素。这些因素被纳入两个肾移植失败预测模型(Cox回归模型和Fine Gray模型),显示出良好的校准度,在验证队列中,Fine Gray模型的C指数为0.66(第1年的95%置信区间:0.63 - 0.70),具有鉴别能力。考虑到移植肾失功与患者死亡之间竞争风险的Fine - Gray模型,被用于开发一种基于冷缺血预测移植肾失功的实用工具。

解读

分配时的预测模型提供了一种简单实用的工具,可通过为肾移植定制冷缺血时间来指导器官分配机构和医疗手术团队。

资助

半人马座基金会(SIREN 499,947,398 - http://www.fondation - centaure.org),所有资助来源在研究中均未发挥任何作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd2f/12273218/385209acb694/gr1.jpg

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