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The 2018 Banff Working Group classification of definitive polyomavirus nephropathy: A multicenter validation study in the modern era
Author(s) -
Nickeleit Volker,
Singh Harsharan K.,
Dadhania Darshana,
Cornea Virgilius,
ElHusseini Amr,
Castellanos Ana,
Davis Vicki G.,
Waid Thomas,
Seshan Surya V.
Publication year - 2021
Publication title -
american journal of transplantation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.89
H-Index - 188
eISSN - 1600-6143
pISSN - 1600-6135
DOI - 10.1111/ajt.16189
Subject(s) - medicine , creatinine , renal function , nephropathy , urology , cohort , surgery , gastroenterology , endocrinology , diabetes mellitus
Polyomavirus nephropathy (PVN) remained inadequately classified until 2018 when the Banff Working Group published a new 3‐tier morphologic classification scheme derived from in‐depth statistical analysis of a large multinational patient cohort. Here we report a multicenter “modern‐era” validation study that included 99 patients with definitive PVN transplanted post January 1, 2009 and followed the original 2018 study design. Results validate the PVN classification, that is, the 3 PVN disease classes predicted clinical presentation, allograft function, and outcome independent of therapeutic intervention. PVN class 1 compared to classes 2 and 3 was diagnosed earlier (16.9 weeks posttransplant [median], P = .004), and showed significantly better function at 24 months postindex biopsy (serum creatinine 1.75 mg/dl, geometric mean, vs class 2: P = .037, vs class 3: P = .013). Class 1 presented during long‐term follow‐up with a low graft failure rate: 5% class 1, vs 30% class 2, vs 50% class 3 ( P = .009). Persistent PVN was associated with an increased risk for graft failure (and functional decline in class 2 at 24 months postdiagnosis; serum creatinine with persistence: 2.48 mg/dL vs 1.65 with clearance, geometric means, P = .018). In conclusion, we validate the 2018 Banff Working Group PVN classification that provides significant clinical information and enhances comparative data analysis.