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.

Poor responses to mRNA COVID-19 vaccine have been reported after 2 vaccine injections in kidney transplant recipients (KTRs) treated with belatacept. We analyzed the humoral response in belatacept-treated KTRs without a history of SARS-CoV-2 infection who received three injections of BNT162b2-mRNA COVID-19 vaccine. We also investigated vaccine immunogenicity in belatacept-treated KTRs with prior COVID-19 and characterized symptomatic COVID-19 infections after the vaccine in belatacept-treated KTRs.Among the 62 belatacept-treated KTRs (36 [58%] males), the median age ( 63.5 years IQR [51-72]), without COVID-19 history, only four patients (6.4%) developed anti-SARS-CoV-2 IgG with low antibody titers (median 209, IQR [20-409] AU/ml). 71% were treated with mycophenolic acid and 100% with steroids in association with belatacept. In contrast, in all the 5 KTRs with prior COVID-19 history, mRNA vaccine induced a strong antibody response with high antibody titers (median 10 769 AU/ml, IQR [6410-20 069]) after two injections. Seroprevalence after three-vaccine doses in 35 non-belatacept-treated KTRs was 37.1%. Twelve KTRs developed symptomatic COVID-19 after vaccination, including severe forms (50% of mortality). Breakthrough COVID-19 occurred in 5% of fully vaccinated patients. Administration of a third dose of BNT162b2 mRNA COVID-19 vaccine did not improve immunogenicity in KTRs treated with belatacept without prior COVID-19. Other strategies aiming to improve patient protection are needed. K E Y W O R D S belatacept, COVID-19 mRNA vaccine, kidney transplant recipients, three doses 1 | INTRODUC TI ON In contrast to immunocompetent individuals, poor immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccines have been observed in kidney transplant recipients (KTRs) after two vaccine injections. Several studies demonstrated seroconversion rates between 30% and 54% in patients treated with calcineurin inhibitors (CNI)-based immunosuppressive therapy. 1-5

BackgroundOver the past decades, an international group of experts iteratively developed a consensus classification of kidney transplant rejection phenotypes, known as the Banff classification. Data-driven clustering of kidney transplant histologic data could simplify the complex and discretionary rules of the Banff classification, while improving the association with graft failure.MethodsThe data consisted of a training set of 3510 kidney-transplant biopsies from an observational cohort of 936 recipients. Independent validation of the results was performed on an external set of 3835 biopsies from 1989 patients. On the basis of acute histologic lesion scores and the presence of donor-specific HLA antibodies, stable clustering was achieved on the basis of a consensus of 400 different clustering partitions. Additional information on kidney-transplant failure was introduced with a weighted Euclidean distance.ResultsBased on the proportion of ambiguous clustering, six clinically meaningful cluster phenotypes were identified. There was significant overlap with the existing Banff classification (adjusted rand index, 0.48). However, the data-driven approach eliminated intermediate and mixed phenotypes and created acute rejection clusters that are each significantly associated with graft failure. Finally, a novel visualization tool presents disease phenotypes and severity in a continuous manner, as a complement to the discrete clusters.ConclusionsA semisupervised clustering approach for the identification of clinically meaningful novel phenotypes of kidney transplant rejection has been developed and validated. The approach has the potential to offer a more quantitative evaluation of rejection subtypes and severity, especially in situations in which the current histologic categorization is ambiguous.