Dataset Information

Suboptimal Performance of Hepatocellular Carcinoma Prediction Models in Patients with Hepatitis B Virus-Related Cirrhosis.

ABSTRACT: This study aimed to evaluate the predictive performance of pre-existing well-validated hepatocellular carcinoma (HCC) prediction models, established in patients with HBV-related cirrhosis who started potent antiviral therapy (AVT). We retrospectively reviewed the cases of 1339 treatment-naïve patients with HBV-related cirrhosis who started AVT (median period, 56.8 months). The scores of the pre-existing HCC risk prediction models were calculated at the time of AVT initiation. HCC developed in 211 patients (15.1%), and the cumulative probability of HCC development at 5 years was 14.6%. Multivariate Cox regression analysis revealed that older age (adjusted hazard ratio [aHR], 1.023), lower platelet count (aHR, 0.997), lower serum albumin level (aHR, 0.578), and greater LS value (aHR, 1.012) were associated with HCC development. Harrell's c-indices of the PAGE-B, modified PAGE-B, modified REACH-B, CAMD, aMAP, HCC-RESCUE, AASL-HCC, Toronto HCC Risk Index, PLAN-B, APA-B, CAGE-B, and SAGE-B models were suboptimal in patients with HBV-related cirrhosis, ranging from 0.565 to 0.667. Nevertheless, almost all patients were well stratified into low-, intermediate-, or high-risk groups according to each model (all log-rank p < 0.05), except for HCC-RESCUE (p = 0.080). Since all low-risk patients had cirrhosis at baseline, they had unneglectable cumulative incidence of HCC development (5-year incidence, 4.9-7.5%). Pre-existing risk prediction models for patients with chronic hepatitis B showed suboptimal predictive performances for the assessment of HCC development in patients with HBV-related cirrhosis.

SUBMITTER: Lee JS

PROVIDER: S-EPMC9818663 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Suboptimal Performance of Hepatocellular Carcinoma Prediction Models in Patients with Hepatitis B Virus-Related Cirrhosis.

Lee Jae Seung JS Lim Tae Seop TS Lee Hye Won HW Kim Seung Up SU Park Jun Yong JY Kim Do Young DY Ahn Sang Hoon SH Lee Hyun Woong HW Lee Jung Il JI Kim Ja Kyung JK Min In Kyung IK Kim Beom Kyung BK

Diagnostics (Basel, Switzerland) 20221220 1

This study aimed to evaluate the predictive performance of pre-existing well-validated hepatocellular carcinoma (HCC) prediction models, established in patients with HBV-related cirrhosis who started potent antiviral therapy (AVT). We retrospectively reviewed the cases of 1339 treatment-naïve patients with HBV-related cirrhosis who started AVT (median period, 56.8 months). The scores of the pre-existing HCC risk prediction models were calculated at the time of AVT initiation. HCC developed in 21 ...[more]

PMID: 36611295

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Project description:Background & aimsGuidelines recommend hepatocellular carcinoma (HCC) surveillance in patients with chronic HBV infection. Several HCC risk prediction models are available to guide surveillance decisions, but their comparative performance remains unclear.MethodsUsing a retrospective cohort of patients with HBV treated with nucleos(t)ide analogues at 130 Veterans Administration facilities between 9/1/2008 and 12/31/2018, we calculated risk scores from 10 HCC risk prediction models (REACH-B, PAGE-B, m-PAGE-B, CU-HCC, HCC-RESCUE, CAMD, APA-B, REAL-B, AASL-HCC, RWS-HCC). We estimated the models' discrimination and calibration. We calculated HCC incidence in risk categories defined by the reported cut-offs for all models.ResultsOf 3,101 patients with HBV (32.2% with cirrhosis), 47.0% were treated with entecavir, 40.6% tenofovir, and 12.4% received both. During a median follow-up of 4.5 years, 113 patients developed HCC at an incidence of 0.75/100 person-years. AUC values for 3-year HCC risk were the highest for RWS-HCC, APA-B, REAL-B, and AASL-HCC (all >0.80). Of these, 3 (APA-B, RWS-HCC, REAL-B) incorporated alpha-fetoprotein. AUC values for the other models ranged from 0.73 for PAGE-B to 0.79 for CAMD and HCC-RESCUE. Of the 7 models with AUC >0.75, only APA-B was poorly calibrated. In total, 10-20% of the cohort was deemed low-risk based on the published cut-offs. None of the patients in the low-risk groups defined by PAGE-B, m-PAGE-B, AASL-HCC, and REAL-B developed HCC during the study timeframe.ConclusionIn this national cohort of US-based patients with HBV on antiviral treatment, most models performed well in predicting HCC risk. A low-risk group, in which no cases of HCC occurred within a 3-year timeframe, was identified by several models (PAGE-B, m-PAGE-B, CAMD, AASL-HCC, REAL-B). Further studies are warranted to examine whether these patients could be excluded from HCC surveillance.Lay summaryRisk prediction models for hepatocellular carcinoma (HCC) in patients infected with hepatitis B virus (HBV) could guide HCC surveillance decisions. In this large cohort of US-based patients receiving treatment for HBV, most published models discriminated between those who did or did not develop HCC, although the RWS-HCC, REAL-B, and AASL-HCC performed the best. If confirmed in future studies, these models could help identify a low-risk subset of patients on antiviral treatment who could be excluded from HCC surveillance.

Project description:ObjectThe prediction of hepatocellular carcinoma (HCC) prognosis faced great challenge due to tumor heterogeneity. The purpose of this study was to explore the correlation between the immune infiltrate and prognosis. Moreover, we aimed to establish a risk prediction model for survival in HCC patients based on clinicopathological and immune indicators.MethodsIn this study, 316 patients with HCC who underwent radical resection in West China Hospital from 2009 to 2014 were included. Clinicopathological data and pathological specimens were collected. H&E staining and immunohistochemical staining were performed on the pathological tissue sections. The evaluation of tumor-infiltrating lymphocyte (TIL) density was based on H&E slices, and the assessment of the expressions of CD8, CD68, Lymphocyte activation gene-3 (LAG-3), T cell immunoglobulin domain and mucin domain-3 (TIM-3), Programmed Cell Death Protein 1 (PD-1), Programmed Cell Death Ligand 1 (PD-L1), OX40, CD66b, and Tryptase. was performed on the immunohistochemical slices. A risk prediction model for survival in HCC patients was established by integrating immune-related biomarkers and clinicopathological indicators.ResultsThe Barcelona Clinic Liver Cancer (BCLC) stage; the microvascular invasion status; the density of TILs; the expressing levels of CD66b, OX40, and PD-L1 in the immune cell; CD68; and CD8 were the predictors of patients' overall survival (OS). The BCLC stage; the density of TILs; and the expressions of OX40, CD68, and CD8 were associated with disease-free survival (DFS). The expressions of CD66b, CD68, OX40, and CD8 had a cumulative effect on prognosis. The area under the curve of the prediction model for OS based on clinicopathological features was improved from 0.62 to 0.74 by adding to CD8, OX40, CD68, CD66b, and TILs, whereas it was improved from 0.59 to 0.73 for the DFS prediction model.ConclusionOur results, if confirmed, indicated that immune-related biomarkers should be taken into account or stratified in survival analysis for HCC.

Dataset Information

Suboptimal Performance of Hepatocellular Carcinoma Prediction Models in Patients with Hepatitis B Virus-Related Cirrhosis.

Publications

Suboptimal Performance of Hepatocellular Carcinoma Prediction Models in Patients with Hepatitis B Virus-Related Cirrhosis.

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