法国巴黎大学Alexandre Loupy小组在研究中取得进展。他们开发并验证了一种肾移植患者移植物丢失风险预测系统。 这一研究成果于2019年9月17日在线发表于《英国医学杂志》。

在这项研究中，衍生队列为2005-2014年间，法国的4个中心前瞻性招募的4000名连续肾移植受者；验证队列为2002-2014年间，来自欧洲3个中心的2129名肾移植受者和来自北美3个中心的1428名肾移植受者。

在7557例肾移植受者中，中位随访7.12年后，有1067例（14.1%）移植失败。在衍生队列中，八个功能、组织学和免疫学预后因素与同种异体移植物失败独立相关，遂将其合并为风险预测评分（iBox）。该评分可准确校正与判别。来自欧洲和美国的验证队列进一步证实了iBox的性能。

iBox系统在移植后评估的不同时间段展现了它的准确性，并在不同的临床方案中进行验证，包括使用免疫抑制方案的类型和对排斥治疗的反应，并显著优于先前的风险预测评分以及仅基于功能参数（包括估计的肾小球滤过率和蛋白尿）的风险评分。最后，三个随机对照试验证实了iBox风险评分预测长期同种异体移植物丢失的准确性。

最终，研究组建立了一个综合、准确、容易实现的风险预测评分系统，用于预测肾移植失败，并展现了全球各中心的普遍性和常见的临床情况。iBox风险预测评分可帮助指导监测患者，以及进一步完善临床试验的有效性和早期替代终点的设计与开发。

附：英文原文

Title: Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study

Author: Alexandre Loupy, Olivier Aubert, Babak J Orandi, Maarten Naesens, Yassine Bouatou, Marc Raynaud, Gillian Divard, Annette M Jackson, Denis Viglietti, Magali Giral, Nassim Kamar, Olivier Thaunat, Emmanuel Morelon, Michel Delahousse, Dirk Kuypers, Alexandre Hertig, Eric Rondeau, Elodie Bailly, Farsad Eskandary, Georg Bhmig, Gaurav Gupta, Denis Glotz, Christophe Legendre, Robert A Montgomery, Mark D Stegall, Jean-Philippe Empana, Xavier Jouven, Dorry L Segev, Carmen Lefaucheur

Issue&Volume: 2019/09/17

Abstract: 

Objective To develop and validate an integrative system to predict long term kidney allograft failure.

Design International cohort study.

Setting Three cohorts including kidney transplant recipients from 10 academic medical centres from Europe and the United States.

Participants Derivation cohort: 4000 consecutive kidney recipients prospectively recruited in four French centres between 2005 and 2014. Validation cohorts: 2129 kidney recipients from three centres in Europe and 1428 from three centres in North America, recruited between 2002 and 2014. Additional validation in three randomised controlled trials (NCT01079143, EudraCT 2007-003213-13, and NCT01873157).

Main outcome measure Allograft failure (return to dialysis or pre-emptive retransplantation). 32 candidate prognostic factors for kidney allograft survival were assessed.

Results Among the 7557 kidney transplant recipients included, 1067 (14.1%) allografts failed after a median post-transplant follow-up time of 7.12 (interquartile range 3.51-8.77) years. In the derivation cohort, eight functional, histological, and immunological prognostic factors were independently associated with allograft failure and were then combined into a risk prediction score (iBox). This score showed accurate calibration and discrimination (C index 0.81, 95% confidence interval 0.79 to 0.83). The performance of the iBox was also confirmed in the validation cohorts from Europe (C index 0.81, 0.78 to 0.84) and the US (0.80, 0.76 to 0.84). The iBox system showed accuracy when assessed at different times of evaluation post-transplant, was validated in different clinical scenarios including type of immunosuppressive regimen used and response to rejection therapy, and outperformed previous risk prediction scores as well as a risk score based solely on functional parameters including estimated glomerular filtration rate and proteinuria. Finally, the accuracy of the iBox risk score in predicting long term allograft loss was confirmed in the three randomised controlled trials.

Conclusion An integrative, accurate, and readily implementable risk prediction score for kidney allograft failure has been developed, which shows generalisability across centres worldwide and common clinical scenarios. The iBox risk prediction score may help to guide monitoring of patients and further improve the design and development of a valid and early surrogate endpoint for clinical trials.

DOI: 10.1136/bmj.l4923

Source: https://www.bmj.com/content/366/bmj.l4923