Abstract: TH-PO0946
AlloView in Kidney Transplant Rejection
Session Information
- Transplantation: Clinical - Glomerular Diseases, Infections, and Rejection
November 06, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Transplantation
- 2102 Transplantation: Clinical
Authors
- Swamy, Varsha, The University of Chicago, Chicago, Illinois, United States
- Kelley, Courtney, The University of Chicago, Chicago, Illinois, United States
- Vachachira, Anissa, The University of Chicago, Chicago, Illinois, United States
- Shi, Jing, CareDx Inc, Brisbane, California, United States
- Patel, Shree, CareDx Inc, Brisbane, California, United States
- Lawrecki, Tatyana M, CareDx Inc, Brisbane, California, United States
- Concepcion, Beatrice P., The University of Chicago, Chicago, Illinois, United States
- Kyeso, Yousuf, The University of Chicago, Chicago, Illinois, United States
Background
AlloView, a model integrating donor-derived cell free DNA (dd-cfDNA) with standard of care (SOC) parameters (eGFR, graft instability, proteinuria, anti-HLA donor specific antibody, previous episode of rejection) has been shown to help in predicting rejection when compared to SOC alone. A previous study compared AlloView results to biopsy-proven rejection and showed that median AlloView scores were higher in both acute cellular rejection (ACR) and antibody mediated rejection (AMR). We sought to add to the available data from our transplant center to improve interpretation of AlloView results.
Methods
We included biopsy samples from kidney transplant recipients from 2017-2024 with a dd-cfDNA ≤30 days prior to biopsy and all SOC variables. All biopsies were for-cause. A Kruskal-Wallis analysis was done to evaluate AlloView across ACR, AMR, borderline rejection, and no rejection (NR) phenotypes. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the ability to determine AMR versus NR and rejection versus NR using AlloView.
Results
We included 78 biopsy samples from 71 transplant recipients. Forty-seven biopsies were classified as NR, 4 borderline, 19 AMR, and 8 ACR. There was a significant difference in median AlloView score of AMR (76%, IQR 17-82%) compared to NR (16%, IQR 11-27%), (P = 0.0062). There was no significant difference in AlloView score of ACR compared to NR or borderline compared to NR. The AUC of AlloView to discriminate rejection from NR is 0.61 (95%CI: 0.46, 0.76). The AUC to discriminate AMR from NR is 0.74 (95%CI: 0.58, 0.9).
Conclusion
This data suggests that AlloView may be helpful in predicting AMR. AlloView did not predict ACR, but this may due to the small sample size and majority of low grade (IA) ACR in this cohort. Studies with larger sample sizes may continue to improve the interpretation and clinical utility of Alloview.
Figure 1: Boxplot of Biopsy Phenotypes
Figure 2: ROC curves of Alloview discriminating rejection or AMR from no rejection