TY - JOUR
T1 - A Probabilistic Approach to Histologic Diagnosis of Antibody-Mediated Rejection in Kidney Transplant Biopsies
AU - Halloran, P. F.
AU - Famulski, K. S.
AU - Chang, J.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Histologic diagnosis of antibody-mediated rejection (ABMR) in kidney transplant biopsies uses lesion score cut-offs such as 0 vs. > 0 rather than actual scores, and requires donor-specific antibody (DSA). However, cutoffs lose information, and DSA is not always reliable. Using microarray-derived molecular ABMR scores as a histology-independent estimate of ABMR in 703 biopsies, we reassessed criteria for ABMR to determine relative importance of various lesions; the utility of equations using actual scores rather than cutoffs, and the potential for diagnosing ABMR when DSA is unknown or negative. We confirmed that the important features for ABMR diagnosis were peritubular capillaritis (ptc), glomerulitis (g), glomerular double contours (cg), DSA, and C4d staining but questioned some features: arterial fibrosis, vasculitis, acute tubular injury, and sum of ptc+g scores. Regression equations using lesion scores predicted molecular ABMR more accurately than score cut-offs (area-under-curve 0.85-0.86 vs. 0.75). DSA positivity improved accuracy, but regression equations predicted ABMR with moderate accuracy when DSA was unknown. Some biopsies without detectable DSA had high probability of ABMR by regression, although most had HLA antibody. We conclude that regression equations using lesion scores plus DSA maximize diagnostic accuracy, and can estimate probable ABMR when DSA is unknown or undetectable. This article is protected by copyright. All rights reserved.
AB - Histologic diagnosis of antibody-mediated rejection (ABMR) in kidney transplant biopsies uses lesion score cut-offs such as 0 vs. > 0 rather than actual scores, and requires donor-specific antibody (DSA). However, cutoffs lose information, and DSA is not always reliable. Using microarray-derived molecular ABMR scores as a histology-independent estimate of ABMR in 703 biopsies, we reassessed criteria for ABMR to determine relative importance of various lesions; the utility of equations using actual scores rather than cutoffs, and the potential for diagnosing ABMR when DSA is unknown or negative. We confirmed that the important features for ABMR diagnosis were peritubular capillaritis (ptc), glomerulitis (g), glomerular double contours (cg), DSA, and C4d staining but questioned some features: arterial fibrosis, vasculitis, acute tubular injury, and sum of ptc+g scores. Regression equations using lesion scores predicted molecular ABMR more accurately than score cut-offs (area-under-curve 0.85-0.86 vs. 0.75). DSA positivity improved accuracy, but regression equations predicted ABMR with moderate accuracy when DSA was unknown. Some biopsies without detectable DSA had high probability of ABMR by regression, although most had HLA antibody. We conclude that regression equations using lesion scores plus DSA maximize diagnostic accuracy, and can estimate probable ABMR when DSA is unknown or undetectable. This article is protected by copyright. All rights reserved.
U2 - 10.1111/ajt.13934
DO - 10.1111/ajt.13934
M3 - Article
C2 - 27340822
SN - 1600-6135
VL - 17
SP - 129
EP - 139
JO - American Journal of Transplantation
JF - American Journal of Transplantation
IS - 1
ER -