Dynamics of liver stiffness-based risk prediction model during antiviral therapy in patients with chronic hepatitis B

External Validation of the FSAC Model Using On-Therapy Changes in Noninvasive Fibrosis Markers in Patients with Chronic Hepatitis B: A Multicenter Study

Simple Summary

We externally validated the recently suggested FSAC prediction model for hepatocellular carcinoma (HCC) in treatment-naïve Asian chronic hepatitis B patients starting potent antiviral therapy (AVT). The model reflects age, sex, presence of cirrhosis, and on-therapy changes in non-invasive fibrosis markers (NFMs) after 12 months of antiviral therapy, such as APRI and FIB-4. Our results highlighted better predictive performance for the FSAC model for HCC (Harrell’s c-index: 0.770) than the PAGE-B, modified PAGE-B, modified REACH-B, LSM-HCC, and CAMD models, which only use baseline parameters. A simplified version of FSAC score (i.e., FSAC (2)), including only NFMs at 12 months, also showed a high c-index value (0.763). Our retrospective study suggests that the accurate measurement of intra-hepatic fibrotic burden during adequate AVT is necessary for predicting HCC development.

Abstract

Antiviral therapy (AVT) induces the regression of non-invasive fibrosis markers (NFMs) and reduces hepatocellular carcinoma (HCC) risk among chronic hepatitis B (CHB) patients. We externally validated the predictive performance of the FSAC prediction model for HCC using on-therapy NFM responses. Our multicenter study consecutively recruited treatment-naïve CHB patients (n = 3026; median age, 50.0 years; male predominant (61.3%); cirrhosis in 1391 (46.0%) patients) receiving potent AVTs for >18 months between 2007 and 2018. During follow-up (median 64.0 months), HCC developed in 303 (10.0%) patients. Patients with low FIB-4 or APRI levels at 12 months showed significantly lower HCC risk than those with high NFM levels at 12 months (all p < 0.05). Cumulative 3-, 5-, and 8-year HCC probabilities were 0.0%, 0.3% and 1.2% in the low-risk group (FSAC ≤ 2); 2.1%, 5.2%, and 11.1% in the intermediate-risk group (FSAC 3−8); and 5.2%, 15.5%, and 29.8% in the high-risk group (FSAC ≥ 9) (both p < 0.001 between each adjacent pair). Harrell’s c-index value for FSAC score (0.770) was higher than those for PAGE-B (0.725), modified PAGE-B (0.738), modified REACH-B (0.737), LSM-HCC (0.734), and CAMD (0.742). Our study showed that the FSAC model, which incorporates on-therapy changes in NFMs, had better predictive performance than other models using only baseline parameters.

External validation of CAGE-B and SAGE-B scores for Asian chronic hepatitis B patients with well-controlled viremia by antivirals

CAGE-B and SAGE-B scores, consisting of age and fibrotic burden as cirrhosis and/or liver stiffness, were recently proposed to predict hepatocellular carcinoma (HCC) risk among Caucasian chronic hepatitis B (CHB) patients undergoing long-term antiviral therapy. We externally validated their predictive performances among an independent cohort from Asia, compared to other conventional prediction models. We consecutively recruited CHB patients with well-controlled viremia (serum HBV DNA < 2000 IU/mL) receiving antiviral therapy. Patients with decompensated cirrhosis or HCC at baseline were excluded. Among 1763 patients, CAGE-B score provided the highest Heagerty's integrated area under the curve (iAUC) (0.820), followed by SAGE-B (0.804), mREACH-B (0.800), CAMD (0.786), mPAGE-B (0.748) and PAGE-B (0.721) scores. CAGE-B score showed a significantly better performance than SAGE-B, CAMD, PAGE-B and mPAGE-B scores, but was similar to mREACH-B. SAGE-B score also showed significantly better performance than mPAGE-B and PAGE-B, but was similar to CAMD and mREACH-B. According to CAGE-B score 0-5, 6-10 and ≥11, the annual HCC incidences were 0.18, 1.34 and 6.03 per 100 person-years, respectively (all p < 0.001 between each pair). Likewise, by SAGE-B score 0-5, 6-10 and ≥11, those were 0.31, 1.49 and 8.96 per 100 person-years, respectively (all p < 0.001 between each pair). Hence, CAGE-B and SAGE-B scores showed acceptable predictive performances for Asian CHB patients undergoing antiviral therapy, with the higher performance by CAGE-B score. They show a trend towards better prognostic capability to predict HCC risk than previous models.

The Prognostic Role of On-Treatment Liver Stiffness for Hepatocellular Carcinoma Development in Patients with Chronic Hepatitis B

Background

Dynamic changes in fibrosis markers occur under long-term antiviral treatment (AVT) for chronic hepatitis B. We evaluated prognostic values of on-treatment liver stiffness (LS) compared to ultrasonography findings and determined its optimal cutoff.

Methods

The cumulative probability of hepatocellular carcinoma (HCC) was assessed among 880 patients receiving entecavir or tenofovir for ≥2 years. LS was measured using transient elastography.

Results

After ≥2 years’ AVT, the proportion of patients with cirrhosis on ultrasonography decreased from 54.7% to 44.9% and the mean LS decreased from 13.6 to 8.2 kPa (both p<0.001). However, unlike cirrhosis on ultrasonography before AVT (p<0.001), that after ≥2 years’ AVT did not discriminate HCC risk (p=0.792). Using the Contal and O’Quigley’s method, pre-AVT and on-treatment LS of 12.0 and 6.4 kPa, respectively, were chosen as optimal cutoffs to successfully discriminate HCC risk (both p<0.001). However, through stratification using both pre-AVT and on-treatment LS, the prognosis was finally determined according to on-treatment LS of 6.4 kPa, regardless of pre-AVT LS of 12.0 kPa. Using on-treatment LS of 12 kPa suggested by Caucasians with CHB receiving long-term AVT, patients with higher LS were more likely to develop HCC than those with lower LS (p=0.017); however, there was no significant difference between those with on-treatment LS of 6.4–11.9 and ≥ 12.0 kPa (p=0.920).

Conclusion

For HCC risk stratification in patients receiving long-term AVT, on-treatment LS cutoff should be lowered to 6.4 kPa, which is more predictive than 12 kPa or cirrhosis on ultrasonography. Further studies are required for validation.