4.6 Article

Real-time monitoring of acute liver-allograft rejection using the Banff schema

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TRANSPLANTATION
卷 74, 期 9, 页码 1290-1296

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LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/00007890-200211150-00016

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  1. NIAID NIH HHS [AI38899] Funding Source: Medline
  2. NIDDK NIH HHS [DK49615] Funding Source: Medline

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Background. The Banff schema is the internationally accepted standard for grading acute liver-allograft rejection, but it has not been prospectively tested. Methods. Complete Banff grading was prospectively applied to 2,038 liver-allograft biopsies from 901 adult tacrolimus-treated primary hepatic allograft recipients between August 1995 and September 2001. Histopathologic data was melded with demographic, clinical, and laboratory data into a database on an ongoing basis using locally developed software. Results. Acute rejection developed in 575 of 901 (64%) patients and the worst grade was mild in 422 of 575 (73%). At least one episode of moderate or severe acute rejection developed in 153 of 901 (17%) patients and most episodes, irrespective of severity, occurred within the first year after transplantation. Patients with moderate or severe acute rejection showed higher alanine aminotransferase (P=0.007) and aspartate aminotransferase (P=0.07) levels and were more likely to develop perivenular fibrosis on follow-up biopsies (P=0.001) and graft failure from acute or chronic rejection (P=0.004) than those with mild rejection. Regardless of severity, 80% of patients with acute rejection did not develop significant fibrosis in follow-up biopsies, and graft failure from acute or chronic rejection occurred in only 11 of 901 (1%) allografts. Conclusions. Most acute-rejection episodes are mild and do not lead to clinically significant architectural sequelae. When tested prospectively under real-life and -time conditions, the Banff schema can be used to identify those few patients who are potentially at risk for more significant problems. Creation, capture, and integration of non-free text, or digital, pathology data can be used to prospectively conduct outcomes-based research in transplantation.

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