External Validation of an Easy-to-Use, Adjustable Score for Short- to Long-term Prediction of Kidney Graft Failure

Many tools have been developed to estimate the risk of graft loss for kidney transplant patients, but only a few have been thoroughly validated.

We previously developed the adjustable graft failure score (AdGFS), an easy-to-use tool combining 2-7 variables routinely collected at 1 y posttransplant in all of the transplantation centers. During model development, we selected the variables using random survival forest, a machine learning method, to come up with a simple decision tree based on: donor age; pretransplant non-donor-specific anti-HLA antibodies (presence/absence); kinetic profile of serum creatinine using its values at months 1, 3, 6, and 12 posttransplant; serum creatinine and proteinuria (g/L or g/24 h) at 1 y posttransplantation; occurrence of de novo donor-specific anti-HLA antibodies (yes/no); occurrence of a first episode of acute rejection. The aim of the present study was to validate AdGFS on 2 large, independent, longitudinal cohorts of kidney transplant patients from Leuven, Belgium (n = 930 patients) and Lyon, France (n = 307 patients).

The 4 risk groups obtained actually showed very large and significant differences in graft survival at 10 y posttransplantation: 89%, 81%, 59%, and 23% in the low, intermediate, high, and very high-risk groups, respectively. At 2, 5, and 10 y posttransplantation, the area under the curve (95% confidence interval) of the receiver operating characteristic curve of AdGFS was 0.86 (0.76-0.96), 0.76 (0.70-0.82), and 0.73 (0.69-0.77), respectively.

This external validation study confirmed that AdGFS is clinically applicable for the long-term risk graduation of graft loss at the first transplantation anniversary. It suggests that it may be used to tailor the overall management of the patient to the individual risk and as a surrogate outcome in clinical trials.