The prevalence of significant fibrosis in chronic hepatitis B patients with ALT <80 IU/L.
- Author:
Woo Jin LEE
1
;
Seung Ha PARK
;
Dong Joon KIM
;
Sung Hoa LEE
;
Chan Woo LEE
;
Kyu Tae PARK
;
Jae Youn CHEONG
;
Sung Won CHO
;
Seong Gyu HWANG
;
Youn Jae LEE
;
Mong CHO
;
Jin Mo YANG
;
Young Bae KIM
Author Information
1. Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Korea. djkim@hallym.ac.kr
- Publication Type:Original Article
- Keywords:
Hepatitis B, chronic;
Fibrosis;
Prediction;
Model
- MeSH:
Alanine Transaminase;
Aspartate Aminotransferases;
Biopsy;
Fibrosis;
Hepatitis B, Chronic;
Hepatitis, Chronic;
Humans;
Liver;
Logistic Models;
Prevalence;
ROC Curve;
Tertiary Care Centers;
Viruses
- From:Korean Journal of Medicine
2010;78(1):68-74
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
BACKGROUND/AIMS: The aims of this study were to investigate the prevalence of significant fibrosis in patients with chronic hepatitis B (CHB) virus infections and alanine aminotransferase (ALT) <80 IU/L, and to develop a noninvasive predictive model for significant fibrosis. METHODS: The 136 patients with CHB who underwent liver biopsy were recruited from six tertiary hospitals. The diagnostic value of predictors was judged using multivariate logistic modeling and the area under the receiver operating characteristic (AUROC) curve. RESULTS: Significant fibrosis was diagnosed in 97 patients (71.3%, 95% CI, 63.7~78.9%). In the training set (n = 85), the most important clinical data for predicting significant fibrosis were age and aspartate aminotransferase (AST). The AUROC of this model was 0.86 (95% CI, 0.78~0.94). The validation set (n=51), obtained from another institute, yielded similar results [AUROC: 0.90 (95% CI, 0.78~0.99)]. CONCLUSIONS: A high prevalence of significant fibrosis in CHB patients with ALT <80 IU/L was observed. A simple model that includes age and AST provides an easily applicable tool for physicians to guide the decision-making process regarding the need to perform a liver biopsy in individual patients. However, additional studies are needed to explore the model's performance in larger, independent patient populations.
