Correction to: A noninvasive model to predict liver histology for antiviral therapy decision in chronic hepatitis B with alanine aminotransferase < 2 upper limit of normal

Abstract Background At present, most assessments of liver fibrosis staging mainly focus on non-invasive diagnostic methods. This study aims to construct a noninvasive model to predict liver histology for antiviral therapy in chronic hepatitis B (CHB) with alanine aminotransferase (ALT) < 2 times upper limit of normal (ULN). Methods We retrospectively analyzed 577 patients with CHB who received liver biopsy and whose ALT was less than 2 ULN. Then they were randomly divided into a training group and a validation group. Through logistic regression analysis, a novel predictive model was constructed in the training group to predict significant changes in liver histology [necro-inflammatory activity grade (G) ≥ 2 or fibrosis stage (S) ≥ 2] and then validated in the validation group. Results If liver biopsy showed moderate or severe inflammation or significant fibrosis, antiviral treatment was recommended. Aspartate aminotransferase (AST), anti-hepatitis B virus core antibody (anti-HBC) and glutamine transpeptidase (GGT) were identified as independent predictors for antiviral therapy, with area under the ROC curve (AUROC) of 0.649, 0.647 and 0.616, respectively. Our novel model index, which combined AST, anti- HBC and GGT with AUROC of 0.700 and 0.742 in training set and validation set. Conclusions This study established a noninvasive model to predict liver histology for antiviral treatment decision in patients with CHB with ALT < 2 ULN, which can reduce the clinical needs of liver biopsy.

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Clinical Non-invasive Model to Predict Liver Inflammation in Chronic Hepatitis B With Alanine Aminotransferase ≤ 2 Upper Limit of Normal

Frontiers in Medicine ◽

10.3389/fmed.2021.661725 ◽

2021 ◽

Vol 8 ◽

Author(s):

Shanshan Chen ◽

Haijun Huang

Keyword(s):

Chronic Hepatitis ◽

Hepatitis B ◽

Liver Biopsy ◽

Antiviral Therapy ◽

Chronic Hepatitis B ◽

Alanine Aminotransferase ◽

Liver Inflammation ◽

Non Invasive ◽

Upper Limit ◽

Validation Set

Background and Aim: Liver biopsy remains the gold standard for evaluating liver histology. However, it has certain limitations, and many patients refuse it. Non-invasive methods of liver evaluation are thus attracting considerable interest. In this study, we sought predictors of liver inflammation in chronic hepatitis B (CHB) patients with alanine aminotransferase (ALT) levels ≤ 2-fold the upper limit of normal (ULN); these may guide decisions on whether to commence antiviral therapy.Methods: We retrospectively analyzed 720 patients with CHB who underwent liver biopsy and whose ALT levels were ≤2 ULN. The patients were randomly divided into a training and validation set. We used univariate and multivariate regression analyses of data from the training set to construct a model that predicted significant (grade ≥2) liver inflammation, and validated the model employing the validation set.Results: Aspartate aminotransferase (AST) level, prothrombin time (PT), glutamyl transpeptidase (GGT) level, and anti-hepatitis B virus core antibody (anti-HBC) level were independent predictors of significant liver inflammation in CHB patients with ALT levels ≤ 2 ULN. A model featuring these four parameters afforded areas under the ROC curve of 0.767 and 0.714 for the training and validation sets. The model was more predictive than were the individual factors.Conclusion: AST, GGT, anti-HBC, and PT reflect significant liver inflammation among CHB patients with ALT levels ≤ 2 ULN. Their combination indicates whether antiviral therapy is required.

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A Noninvasive Model to Predict Liver Histology for Antiviral Therapy Decision in Chronic Hepatitis B with Alanine Aminotransferase＜2 Upper Limit of Normal

10.21203/rs.3.rs-73605/v1 ◽

2020 ◽

Author(s):

Shanshan Chen ◽

Haijun Huang

Keyword(s):

Chronic Hepatitis ◽

Hepatitis B ◽

Liver Biopsy ◽

Antiviral Therapy ◽

Alanine Aminotransferase ◽

Antiviral Treatment ◽

Training Group ◽

Liver Histology ◽

Validation Group ◽

Upper Limit

Abstract Background and Aim: Although liver biopsy is currently the gold standard to evaluate liver histology, it has many limitations, such as sampling error, cost and risk of complications. This study aims to construct a noninvasive model to predict liver histology for antiviral therapy in chronic hepatitis B (CHB) with alanine aminotransferase (ALT)＜2 times upper limit of normal(ULN).Methods: We retrospectively analyzed 577 patients with CHB who received liver biopsy and whose ALT was less than 2 ULN. Then they were randomly divided into a training group and a validation group. Through logistic regression analysis, a novel predictive model was constructed in the training group to predict significant changes in liver histology [necro-inflammatory activity grade (G) ≥2 or fibrosis stage (S) ≥2] and then validated in the validation group.Results: If liver biopsy showed moderate or severe inflammation or significant fibrosis, antiviral treatment was recommended. Aspartate aminotransferase (AST), anti-hepatitis B virus core antibody (anti-HBC) and glutamine transpeptidase (GGT) were identified as independent predictors for antiviral therapy, with area under the ROC curve (AUROC) of 0.649, 0.647 and 0.616, respectively. Our novel model index, which combined AST, anti- HBC and GGT with AUROC of 0.700 and 0.742 in estimation set and validation set.Conclusions: This study established a noninvasive model to predict liver histology for antiviral treatment decision in patients with CHB with ALT < 2 ULN, which can reduce the clinical needs of liver biopsy.

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