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Noninvasive scoring system for significant inflammation related to chronic hepatitis B.

ABSTRACT: Although a liver stiffness measurement-based model can precisely predict significant intrahepatic inflammation, transient elastography is not commonly available in a primary care center. Additionally, high body mass index and bilirubinemia have notable effects on the accuracy of transient elastography. The present study aimed to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to chronic hepatitis B, without the aid of transient elastography. A total of 396 patients with chronic hepatitis B were enrolled in the present study. Liver biopsies were performed, liver histology was scored using the Scheuer scoring system, and serum markers and liver function were investigated. Inflammatory activity scoring models were constructed for both hepatitis B envelope antigen (+) and hepatitis B envelope antigen (-) patients. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were 86.00%, 84.80%, 62.32%, 95.39%, and 0.9219, respectively, in the hepatitis B envelope antigen (+) group and 91.89%, 89.86%, 70.83%, 97.64%, and 0.9691, respectively, in the hepatitis B envelope antigen (-) group. Significant inflammation related to chronic hepatitis B can be predicted with satisfactory accuracy by using our logistic regression-based scoring system.

SUBMITTER: Hong MZ

PROVIDER: S-EPMC5345042 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Noninvasive scoring system for significant inflammation related to chronic hepatitis B.

Hong Mei-Zhu MZ Ye Linglong L Jin Li-Xin LX Ren Yan-Dan YD Yu Xiao-Fang XF Liu Xiao-Bin XB Zhang Ru-Mian RM Fang Kuangnan K Pan Jin-Shui JS

Scientific reports 20170310

Although a liver stiffness measurement-based model can precisely predict significant intrahepatic inflammation, transient elastography is not commonly available in a primary care center. Additionally, high body mass index and bilirubinemia have notable effects on the accuracy of transient elastography. The present study aimed to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to chronic hepatitis B, without the aid of transient elastography. A ...[more]

PMID: 28281521

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Project description:The presence of significant liver inflammation is an important indication for antiviral treatment in patients with chronic hepatitis B (CHB) in the indeterminate phase. We aimed to establish a non-invasive nomogram to predict significant liver inflammation in these patients. A total of 195 CHB patients in the indeterminate phase were randomly split into training and validation sets. The least absolute shrinkage and selection operator and logistic regression were applied to identify risk factors and establish a predictive model. A calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve were applied to assess the performance of the nomogram. The median age was 42.0 y and 59.5% of the patients were male. Alkaline phosphatase, γ-glutamyl transpeptidase, and prothrombin time were independent predictors for significant liver inflammation and selected to establish the AGP-nomogram. The calibration plot demonstrated that the predicted results matched the actual values. The DCA showed a high net benefit when the threshold probability was 25-83% in the training set and 31-100% in the validation set. The areas under ROC curves of AGP-nomogram in predicting significant inflammation were significantly higher than ALT in the training set (0.744 vs. 0.642, P = 0.049) and validation set (0.766 vs. 0.660, P = 0.047). The ability of AGP-nomogram in predicting advanced inflammation was also superior to ALT. The AGP-nomogram can accurately identify significant inflammation in CHB patients in the indeterminate phase, and its application may reduce the need for liver biopsy and help identify candidates for antiviral treatment.Abbreviations: AASLD: American Association for the Study of Liver Diseases; ALB: albumin; ALP: alkaline phosphatase; ALT: alanine aminotransferase; APRI: aspartate aminotransferase-to-platelet ratio index; AST: aspartate aminotransferase; AUROC: area under the receiver operating characteristic curve; CHB: chronic hepatitis B; CI: confidence interval; DCA: decision curve analysis; FIB-4: fibrosis index based on the four factors; GLB: globulin; GGT: γ-glutamyl transpeptidase; HBcAb: hepatitis B core antibody; HBeAg: hepatitis B e antigen; HBsAg: hepatitis B surface antigen; HBV: hepatitis B virus; HCC: hepatocellular carcinoma; HIV: human immunodeficiency virus; INR: international-normalized ratio; IQR: interquartile range; LASSO: least absolute shrinkage and selection operator; LB: liver biopsy; LR: Likelihood ratio; NAFLD: non-alcoholic fatty liver disease; NPV: negative predictive value; PLT: platelets; PPV: positive predictive value; PT: prothrombin time; ROC: receiver operating characteristic; TB: total bilirubin; TE: transient elastography; ULN: upper limit of normal.

Project description:Evaluating liver fibrosis is crucial for disease severity assessment, treatment decisions, and hepatocarcinogenic risk prediction among patients with chronic hepatitis C. In this retrospective multicenter study, we aimed to construct a novel model formula to predict cirrhosis. A total of 749 patients were randomly allocated to training and validation sets at a ratio of 2:1. Liver stiffness measurement (LSM) was made via transient elastography using FibroScan. Patients with LSM ≥12.5 kPa were regarded as having cirrhosis. The best model formula for predicting cirrhosis was constructed based on factors significantly and independently associated with LSM (≥12.5 kPa) using multivariate regression analysis. Among the 749 patients, 198 (26.4%) had LSM ≥12.5 kPa. In the training set, multivariate analysis identified logarithm natural (ln) type IV collagen 7S, ln hyaluronic acid, and ln Wisteria floribunda agglutinin positive Mac-2-binding protein (WFA+-Mac-2 BP) as the factors that were significantly and independently associated with LSM ≥12.5 kPa. Thus, the formula was constructed as follows: score = -6.154 + 1.166 × ln type IV collagen 7S + 0.526 × ln hyaluronic acid + 1.069 × WFA+-Mac-2 BP. The novel formula yielded the highest area under the curve (0.882; optimal cutoff, -0.381), specificity (81.5%), positive predictive values (62.6%), and predictive accuracy (81.6%) for predicting LSM ≥12.5 kPa among fibrosis markers and indices. These results were almost similar to those in the validated set, indicating the reproducibility and validity of the novel formula. The novel formula scores were significantly, strongly, and positively correlated with LSM values in both the training and validation data sets (correlation coefficient, 0.721 and 0.762; p = 2.67 × 10-81 and 1.88 × 10-48, respectively). In conclusion, the novel formula was highly capable of diagnosing cirrhosis in patients with chronic hepatitis C and exhibited better diagnostic performance compared to conventional fibrosis markers and indices.

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Noninvasive scoring system for significant inflammation related to chronic hepatitis B.

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Noninvasive scoring system for significant inflammation related to chronic hepatitis B.

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