Background. We aimed to identify a reliable composite scoring system (clinical / biological) to evalute organ quality and predict outcomes post-kidney transplantation (KT).

Methods. 233 deceased donor KT recipients (KTRs) were evaluated. Gene expression (GE) profiling of pre-implantation kidney biopsies was performed. Clinical and transcriptome data was integrated in composite score models. Kidney Donor Risk Index (KDRI) was tested for performance in the study cohort. Short-(DGF) and long-term outcomes (Progressors (P) or non-Progressors (NP) to CAD at 24-mo) were evaluated. Using two patient subsets, GE biomarkers predictive of post-KT outcomes were first identified and confirmed by a non-parametric Spearman correlation test. Combing these predictive biomarkers with patients' clinical variables, generalized multivariate regression models were developed on training patient data. The performance of the final multivariate prediction models was validated on independent patient subsets by evaluating overall prediction concordance with a rank-based correlation test and the C statistics.

Results.The performance of the KDRI score predicting (a) short- and (b) long- term outcomes was evaluated as: (a) For 233 DD KTRs with both KDRI and DGF (100 yes; 133 no), KDRI was not a significant predictor of DGF (p = 0.19). The threshold of KDRI that optimizes sensitivity and specificity was 1.104 yielding a sensitivity, specificity, and accuracy of 62.6%, 55.2%, and 58.4% respectively and (b) For 214 subjects with both KDRI and outcome (100 P; 114 NP), the threshold of KDRI that optimizes sensitivity and specificity was 1.01 yielding a sensitivity of 80% and a specificity of 50.9% for an accuracy of 64.5%. Using our available data set, several predictive models for predicting outcomes for KT were obtained and independently validated by integrating molecular and clinical information. In these models both donor age and several molecular markers were found to be important for the prediction of KT outcomes.

Conclusions. These results show the feasibility of establishing accurate composite scores for predicting post-KT outcomes including markers of intrinsic donor biology.

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