A scoring model predicts hepatitis B e antigen seroconversion in chronic hepatitis B patients treated with nucleos(t)ide analogs: real-world clinical practice.

AIM: This study developed and validated a non-invasive scoring model to predict 1-year hepatitis B e antigen (HBeAg) seroconversion in response to nucleos(t)ide analog (NA) treatment in NA-naïve patients with HBeAg-positive chronic hepatitis B (CHB). METHODS: Baseline data from 1014 patients visiting the outpatient and inpatient clinics of Beijing Ditan Hospital, Capital Medical University, China between October 2008 and April 2015 were included. These patients received NAs for HBeAg-positive CHB. The patients were assigned randomly to the derivation (n=710) and validation (n=304) cohorts in a 7:3 ratio. A prediction scoring model was established based on univariate and multivariate Cox proportional hazards regression analyses to identify independent prediction factors. In the derivation cohort, the odds ratio of the predictors were converted to integer risk scores by rounding the quotient from dividing the odds ratio, and the final score was the sum of these values. The predictive accuracy of the scoring model was further assessed using Harrell's concordance index (C-index). RESULTS: The 1-year cumulative HBeAg seroconversion rates were 11.83% and 8.55% in the derivation and validation cohorts, respectively. In the derivation cohort, baseline pretreatment alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (GGT), globulin (GLO), and quantitative HBeAg (qHBeAg) levels were independently associated with HBeAg seroconversion and were included in the scoring system. The model had good discrimination in the derivation and validation cohorts (C-index=0.750, 95% confidence interval 0.694-0.806 and C-index=0.776, 95% confidence interval 0.698-0.855, respectively). The prediction scores ranged from 0 to 4; scores of 0-1 and 2-4 identified patients with lower and higher levels of HBeAg seroconversion, respectively. Kaplan-Meier analysis was used to determine the 1-year cumulative HBeAg seroconversion rates in the two groups (scores of 0-1 and 2-4) of the primary cohort, and log-rank tests revealed a significant difference (4.87% vs. 20.9%, p<0.0001). CONCLUSIONS: The 1-year prediction scoring model based on baseline levels of ALT, GGT, GLO, and qHBeAg offered a reliable predictive value for the response to NA therapy in a Chinese cohort.

Development and validation of a prognostic model for acute-on-chronic hepatitis B liver failure.

AIM: The CANONIC study proposed the Chronic Liver Failure Consortium acute-on-chronic liver failure (CLIF-C ACLF) prognostic model at the European Association for the Study of the Liver-CLIF diagnosis. This study aimed to develop and validate a prognostic model for predicting the short-term mortality of hepatitis B virus (HBV) ACLF as defined by the Asia-Pacific Association for the Study of the Liver. PATIENTS AND METHODS: A retrospective cohort of 381 HBV ACLF patients and a prospective cohort of 192 patients were included in this study. Independent predictors of disease progression were determined using univariate and multivariate Cox proportional hazard regression analysis, and a regression model for predicting prognosis was established. Patient survival was estimated by Kaplan-Meier analysis and subsequently compared by log-rank tests. The area under the receiver operating characteristic curve was used to compare the performance of various current prognostic models. RESULTS: Our model was constructed with five independent risk factors: hepatic encephalopathy, international normalized ratio, neutrophil-lymphocyte ratio, age, and total bilirubin, termed as the HINAT ACLF model, which showed the strongest predictive values compared with CLIF-C ACLF, CLIF-C Organ Failure, Sequential Organ Failure Assessment, CLIF-Sequential Organ Failure Assessment, Model for End-stage Liver Disease, Model for End-stage Liver Disease-sodium, and Child-Turcotte-Pugh scores; this model reduced the corresponding prediction error rates at 28 and 90 days by 16.4-54.5% after ACLF diagnosis in both the derivation cohort and the validation cohorts. CONCLUSION: The HINAT ACLF model can accurately predict the short-term mortality of patients with HBV ACLF as defined by Asia-Pacific Association for the Study of the Liver.

Nomogram prediction of individual prognosis of patients with hepatocellular carcinoma.

BACKGROUND: The purpose of this study was to develop an effective nomogram capable of estimating the individual survival outcomes of patients with hepatocellular carcinoma (HCC), and compare the predictive accuracy and discriminative ability with other staging systems. METHODS: The nomogram was established based on a retrospective study of 661 patients newly diagnosed with HCC at the Beijing Ditan Hospital (Beijing, China), Capital Medical University, between October 2008 and July 2012. The predictive accuracy and discriminative ability of the previously developed nomogram were assessed by C-index and calibration curves, and were compared to seven current commonly used staging systems. The results were validated, using a bootstrap approach to correct for bias, in a prospective study of 220 patients consecutively enrolled between August 2012 and March 2013. RESULTS: Multivariate analysis of the primary cohort for survival analysis identified the independent factors to be aspartate aminotransferase, É£-glutamyl transpeptidase, white blood cell count, neutrophil-to-lymphocyte ratio, prothrombin activity, α-fetoprotein, tumor number and size, lymph node metastasis, and portal vein involvement, which were all included to build the nomogram. The calibration curve for predicting the probability of survival showed consistency between the nomogram and the actual observation. The C-index of the nomogram was 0.81 (95% confidence interval, 0.79-0.82), which was statistically better than that of the Tumor, Node, Metastasis staging (0.71), Barcelona Clinic Liver Cancer staging (0.77), Okuda (0.62), Japan Integrated Staging (0.73), Cancer of the Liver Italian Program score (0.76), Chinese University Prognostic Index (0.68), and the Groupe d' Etude et de Traitement du Carcinome Hepatocellulaire Prognostic classification (0.65) (p < 0.001 for all). The results were validated in the prospective validation cohort. CONCLUSIONS: The prognostic nomogram resulted in more accurate individualized risk estimates for overall survival in HCC patients.

Lamivudine improves short-term outcome in hepatitis B virus-related acute-on-chronic liver failure patients with a high model for end-stage liver disease score.

AIM: Hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF) has significant morbidity and mortality. There is no standard approach for the management of HBV-related ACLF with nucleos(t)ide analogs. Our objective was to compare the short-term mortality between entecavir (ETV) and lamivudine (LAM) in patients with HBV-related ACLF. METHODS: We recruited 311 inpatients with HBV-related ACLF from December 2002 to January 2015. The patients were treated with ETV (n=143) or LAM (n=168). The primary endpoint was mortality rate at week 8. Virological and biochemical responses were also studied. RESULTS: By week 8, 53 (37.06%) patients in the ETV group and 57 (33.93%) patients in the LAM group died, and the two groups had similar mortality (P=0.414). Multivariate analysis showed that age, total bilirubin, international normalized ratio, and model for end-stage liver disease (MELD) score were independent factors for mortality at week 8. The best cut-off value of the MELD score was 24.5 for 8-week mortality. Twenty-nine of the 170 (17.06%) patients with MELD score less than 24.5 died at week 8, and the ETV and LAM groups had similar mortality (P=0.743). Eighty-one of the 141 (57.45%) patients with MELD score of at least 24.5 died at week 8 and the LAM group had lower mortality than the ETV group (P=0.018 at week 4; P=0.039 at week 8). Both groups showed similar virological and biochemical responses at 4 weeks. CONCLUSION: LAM reduces the 8-week mortality rate significantly in patients with HBV-related ACLF who had MELD score of at least 24.5.

Score model for predicting acute-on-chronic liver failure risk in chronic hepatitis B.

AIM: To establish a clinical scoring model to predict risk of acute-on-chronic liver failure (ACLF) in chronic hepatitis B (CHB) patients. METHODS: This was a retrospective study of 1457 patients hospitalized for CHB between October 2008 and October 2013 at the Beijing Ditan Hospital, Capital Medical University, China. The patients were divided into two groups: severe acute exacerbation (SAE) group (n = 382) and non-SAE group (n = 1075). The SAE group was classified as the high-risk group based on the higher incidence of ACLF in this group than in the non-SAE group (13.6% vs 0.4%). Two-thirds of SAE patients were randomly assigned to risk-model derivation and the other one-third to model validation. Univariate risk factors associated with the outcome were entered into a multivariate logistic regression model for screening independent risk factors. Each variable was assigned an integer value based on the regression coefficients, and the final score was the sum of these values in the derivation set. Model discrimination and calibration were assessed using area under the receiver operating characteristic curve and the Hosmer-Lemeshow test. RESULTS: The risk prediction scoring model included the following four factors: age ≥ 40 years, total bilirubin ≥ 171 µmol/L, prothrombin activity 40%-60%, and hepatitis B virus DNA > 10(7) copies/mL. The sum risk score ranged from 0 to 7; 0-3 identified patients with lower risk of ACLF, whereas 4-7 identified patients with higher risk. The Kaplan-Meier analysis showed the cumulative risk for ACLF and ACLF-related death in the two risk groups (0-3 and 4-7 scores) of the primary cohort over 56 d, and log-rank test revealed a significant difference (2.0% vs 33.8% and 0.8% vs 9.4%, respectively; both P < 0.0001). In the derivation and validation data sets, the model had good discrimination (C index = 0.857, 95% confidence interval: 0.800-0.913 and C index = 0.889, 95% confidence interval: 0.820-0.957, respectively) and calibration demonstrated by the Hosmer-Lemeshow test (χ (2) = 4.516, P = 0.808 and χ (2) = 1.959, P = 0.923, respectively). CONCLUSION: Using the scoring model, clinicians can easily identify patients (total score ≥ 4) at high risk of ACLF and ACLF-related death early during SAE.

Pretreatment neutrophil-lymphocyte ratio: an independent predictor of survival in patients with hepatocellular carcinoma.

The neutrophil-to-lymphocyte ratio (NLR) has been shown to be associated with prognosis in various types of cancer. We evaluated pretreatment NLR as a predictor of poor prognosis in patients with hepatocellular carcinoma (HCC), and we compared the prognostic value of NLR with other prognostic scores.We retrospectively analyzed 825 patients diagnosed with HCC between October 2008 and May 2012. Baseline data, including the NLR and the Child-Pugh class or Model for End-Stage Liver Disease (MELD) score, were recorded before treatment. The relationships between overall survival (OS) and the study variables were assessed using univariate and multivariate analyses and receiver operating characteristic (ROC) curves. The prognostic value of NLR was assessed using a Kaplan-Meier survival analysis and compared with that of the Barcelona-Clinic Liver Cancer (BCLC) and Tumor, Node, Metastasis (TNM) staging.The NLR, γ-glutamyltranspeptidase, α-fetoprotein ≥ 400 ng/mL, tumor number ≥ 3, tumor size ≥ 5 cm, lymph node metastasis, portal vein involvement, and Child-Pugh class were significantly associated with OS. The NLR demonstrated the strongest prognostic value (area under ROC curve = 0.811). An NLR ≥ 2.7 was a significant predictor of poor OS (P < 0.0001), and the survival period of patients with an NLR ≥ 2.7 decreased with more advanced BCLC and TNM stage.Pretreatment NLR is a useful prognostic biomarker in HCC patients. The prognostic value of NLR ≥ 2.7 is superior to that of MELD stage or Child-Pugh class, and correlates with that of BCLC and TNM staging scores.