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

Abstract

ObjectiveTo develop and validate an integrative system to predict long term kidney allograft failure.DesignInternational cohort study.SettingThree cohorts including kidney transplant recipients from 10 academic medical centres from Europe and the United States.ParticipantsDerivation 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 measureAllograft failure (return to dialysis or pre-emptive retransplantation). 32 candidate prognostic factors for kidney allograft survival were assessed.ResultsAmong 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.ConclusionAn 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.Trial registrationClinicaltrials.gov NCT03474003.

Banff 2019 Meeting Report: Molecular diagnostics in solid organ transplantation–Consensus for the Banff Human Organ Transplant (B-HOT) gene panel and open source multicenter validation

“…The MDWG is aligning joint efforts using available NanoString systems at participating centers for studying a broad spectrum of archived and well‐annotated transplant biopsies. To centralize the resulting multicenter molecular data from archived transplant biopsies together with the related clinical and outcome data, algorithms, and tools for analysis (including explorative analytics, machine learning‐based diagnostic approaches/classifiers, and risk prediction tools) with remote access by users across the world, a data integration platform (DIP) will be built 67 (Figure 3). Participating centers will be able to upload routinely collected transplant‐related patient data in an anonymized and uniform fashion.…”

“…As the Banff consensus rules for histology underwent refinement over the last 28 years as new knowledge emerged, any molecular “consensus” will also need to undergo constant refinement and, no doubt further, technological innovation. Only through integration with clinical decision‐making and end points in clinical trials can the true clinical utility of molecular diagnostics be demonstrated 67 …”

The Banff 2019 Kidney Meeting Report (I): Updates on and clarification of criteria for T cell– and antibody-mediated rejection

“…Continuing a theme from the Banff 2015 meeting, 1 results of studies using artificial intelligence (AI) and integrative epidemiological approaches were presented. Their applicability in prediction, prognostication, and clinical trials could change standards of care for transplant recipients 2 . The conference was preceded by a premeeting on “Regenerative Medicine and Digital Pathology” and a joint session between the ASHI and Banff key opinion leaders, which presented insights into future tissue and organ engineering and new technologies in solid organ transplantation.…”

Use of biomarkers to improve immunosuppressive drug development and outcomes in renal organ transplantation: A meeting report

“…The integrative box (iBox) Scoring System is one potential surrogate endpoint biomarker to predict the likelihood of graft survival 3, 5, and 7 years after risk assessment . The iBox prediction system was developed by the Paris Transplant Group, using data prospectively collected from 4000 consecutive kidney transplant recipients across four centers in France.…”