A new integrative box risk prediction (iBox) score performs well in predicting long-term kidney allograft failure across countries and clinical settings, reports a study in the British Medical Journal.
The score was developed using data from a prospectively enrolled derivation cohort of 4000 consecutive adult kidney transplant recipients (from living or deceased donors) at three French hospitals between 2005 and 2014. Allograft loss, defined as definitive return to dialysis or preemptive transplantation, was assessed using follow-up data to 2018. Independent predictors on multivariable analysis—including demographic factors, measures of allograft function and histology, and the recipient’s immunologic profile—were incorporated into the iBox score. The score was validated in cohorts of 2129 recipients from European centers and 1428 from North American centers, with additional validation using data from three randomized trials.
The combined cohorts comprised 1775 transplant recipients; at a median follow-up of 7.12 years, the allograft failure rate was 14.1%. The iBox score had accurate calibration and discrimination, with a C index of 0.81 in both the derivation and validation cohorts. Its discriminative capability was confirmed using 3-, 5-, and 7-year follow-up data. The iBox score also performed well in data from randomized trials evaluating therapeutic interventions.
The new risk prediction score was validated in clinical scenarios involving immunosuppressive regimens and response to rejection therapy. In a systematic review, the iBox score provided additional value over previously reported risk scores, as well as scores based on measures of allograft function.
The iBox score meets the need for an integrated tool for predicting the long-term risk of allograft failure after kidney transplantation. Combining demographic, functional, histologic, and immunologic variables, it can be readily implemented for risk prediction in clinical practice. An online interface for calculating allograft survival estimates for individual patients is available at www.paristransplantgroup.org [Loupy A, et al. Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study. BMJ 2019; 366:l4923].