Donor-derived Cell-free DNA Combined With Histology Improves Prediction of Estimated Glomerular Filtration Rate Over Time in Kidney Transplant Recipients Compared With Histology Alone

Background. Higher Banff inflammation and chronicity scores on kidney transplant biopsies are associated with poorer graft survival, although histology alone has limitations in predicting outcomes. We investigated if integrating donor-derived cell-free DNA (dd-cfDNA, Allosure; CareDx, Inc.) with Banff biopsy scores into a predictive model for estimated glomerular filtration rate over time can improve prognostic assessment versus histology alone. Methods. We identified 180 kidney transplant patients with dd-cfDNA assessed within 1 mo of biopsy. Using linear mixed–effects models, a prediction model of Banff histology scores and dd-cfDNA on estimated glomerular filtration rate over time was derived. Nested models were compared using the likelihood-ratio test, Akaike Information Criterion, and Bayesian Information Criterion to assess if inclusion of dd-cfDNA into a model consisting of Banff biopsy scores would improve model fit. Results. Univariate models identified significant covariate-by-time interactions for cg = 3 versus