TY - JOUR
T1 - A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C
AU - Wai, Chun Tao
AU - Greenson, Joel K.
AU - Fontana, Robert J.
AU - Kalbfleisch, John D.
AU - Marrero, Jorge A.
AU - Conjeevaram, Hari S.
AU - Lok, Anna S F
N1 - Funding Information:
Abbreviations: CHC, chronic hepatitis C; AST, aspartate aminotransferase; ALT, alanine aminotransferase; HCV, hepatitis C virus; IDU, injection drug use; ALP, alkaline phosphatase; ULN, upper limit of normal; ROC, receiver operating characteristics; AUC, area under receiver operating curves; CI, confidence interval; APRI, aspartate aminotransferase to platelet count ratio index. From the 1Division of Gastroenterology, 2Department of Pathology, 3Department of Biostatistics, University of Michigan Medical School, Ann Arbor, MI. Received March 11, 2003, accepted May 20, 2003. Supported by the Singapore HMDP Fellowship (C.T.W.) and by National Institutes of Health contract N01-DK-9-2323, and grants U01-DK-57577, U01-DK-62498, and R43-AI-51919 (A.S.-F.L.). Address reprint requests to: Anna S.-F. Lok, M.D., Division of Gastroenterology, University of Michigan Medical Center, 3912 Taubman Center, Box 0362, Ann Arbor, MI 48109-0362. E-mail: aslok@umich.edu; fax: 734-936-7392. Copyright © 2003 by the American Association for the Study of Liver Diseases. 0270-9139/03/3802-0030$30.00/0 doi:10.1053/jhep.2003.50346
PY - 2003/8/1
Y1 - 2003/8/1
N2 - Information on the stage of liver fibrosis is essential in managing chronic hepatitis C (CHC) patients. However, most models for predicting liver fibrosis are complicated and separate formulas are needed to predict significant fibrosis and cirrhosis. The aim of our study was to construct one simple model consisting of routine laboratory data to predict both significant fibrosis and cirrhosis among patients with CHC. Consecutive treatment-naive CHC patients who underwent liver biopsy over a 25-month period were divided into 2 sequential cohorts: training set (n = 192) and validation set (n = 78). The best model for predicting both significant fibrosis (Ishak score ≥ 3) and cirrhosis in the training set included platelets, aspartate aminotransferase (AST), and alkaline phosphatase with an area under ROC curves (AUC) of 0.82 and 0.92, respectively. A novel index, AST to platelet ratio index (APRI), was developed to amplify the opposing effects of liver fibrosis on AST and platelet count. The AUC of APRI for predicting significant fibrosis and cirrhosis were 0.80 and 0.89, respectively, in the training set. Using optimized cut-off values, significant fibrosis could be predicted accurately in 51% and cirrhosis in 81% of patients. The AUC of APRI for predicting significant fibrosis and cirrhosis in the validation set were 0.88 and 0.94, respectively. In conclusion, our study showed that a simple index using readily available laboratory results can identify CHC patients with significant fibrosis and cirrhosis with a high degree of accuracy. Application of this index may decrease the need for staging liver biopsy specimens among CHC patients.
AB - Information on the stage of liver fibrosis is essential in managing chronic hepatitis C (CHC) patients. However, most models for predicting liver fibrosis are complicated and separate formulas are needed to predict significant fibrosis and cirrhosis. The aim of our study was to construct one simple model consisting of routine laboratory data to predict both significant fibrosis and cirrhosis among patients with CHC. Consecutive treatment-naive CHC patients who underwent liver biopsy over a 25-month period were divided into 2 sequential cohorts: training set (n = 192) and validation set (n = 78). The best model for predicting both significant fibrosis (Ishak score ≥ 3) and cirrhosis in the training set included platelets, aspartate aminotransferase (AST), and alkaline phosphatase with an area under ROC curves (AUC) of 0.82 and 0.92, respectively. A novel index, AST to platelet ratio index (APRI), was developed to amplify the opposing effects of liver fibrosis on AST and platelet count. The AUC of APRI for predicting significant fibrosis and cirrhosis were 0.80 and 0.89, respectively, in the training set. Using optimized cut-off values, significant fibrosis could be predicted accurately in 51% and cirrhosis in 81% of patients. The AUC of APRI for predicting significant fibrosis and cirrhosis in the validation set were 0.88 and 0.94, respectively. In conclusion, our study showed that a simple index using readily available laboratory results can identify CHC patients with significant fibrosis and cirrhosis with a high degree of accuracy. Application of this index may decrease the need for staging liver biopsy specimens among CHC patients.
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U2 - 10.1053/jhep.2003.50346
DO - 10.1053/jhep.2003.50346
M3 - Article
C2 - 12883497
AN - SCOPUS:0042265556
SN - 0270-9139
VL - 38
SP - 518
EP - 526
JO - Hepatology
JF - Hepatology
IS - 2
ER -