The transplant field currently lacks of robust risk stratification models leading to major problems for clinical care, clinical trials, and medical progress. The goal of this study was to generate an integrative and validated scoring system that predicts kidney allograft loss.

This international study involved 7 European centers and 2 North American centers including a total of 4.344 kidney transplant recipients transplanted between 2002 to 2014. We integrated the full spectrum of allograft parameters including baseline donor and recipient characteristics, transplant characteristics, post transplant injuries (AKI, BK, recurrence, rejection), treatment and prospective anti-HLA DSA measurements. In addition, all patients had systematic allograft assessment at 1-year post transplant including histopathology, allograft function and proteinuria.

Primary analyses were derived from the prospective Paris Group Cohorts enrolling 1016 patients. The prognostic ability of 80 parameters was evaluated using Cox regression analyses together with random Forest analysis. Final model included: allograft scarring (IFTA), allograft injury (microcirculation inflammation and C4d), allograft function (eGFR and proteinuria/creatininuria measured at 1-yr post transplant), anti-HLA DSA status and level (MFI) that were independently associated with 7-yrs post transplant allograft survival. The model exhibited excellent calibration and discrimination (C-statistic=0.83; 95%CI=0.78-0.87) and a nomogram for individual graft survival prediction was generated. The performance of the score was confirmed in the external validation cohort from Europe (n=2192, C-statistic=0.80; 95%CI=0.76-0.83) and North America (n=1136, C-statistic=0.85; 95%CI=0.81-0.89). The capacity of the score to accurately predict graft failure remained high in 1118 patients evaluated beyond 1-yr post transplant (C-statistic=0.83).

The iBox prognostic score and integrative nomogram precisely and accurately predict the individual long-term graft survival. The score demonstrates high performance, exportability across centers worldwide and adaptability beyond the first year post transplant evaluation.

CITATION INFORMATION: Loupy A, Aubert O, Orandi B, Jackson A, Naesens M, Kamar N, Thaunat O, Morelon E, Delahousse M, Viglietti D, Glotz D, Legendre C, Jouven X, Montgomery R, Stegall M, Segev D, Lefaucheur C. A Multidimensional Prognostic Score and Nomogram to Predict Kidney Transplant Survival: The Integrative Box (iBox) System. Am J Transplant. 2017;17 (suppl 3).

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