Improving Hepatocellular Carcinoma Surveillance Outcomes in Patients with Cirrhosis after Hepatitis C Cure: A Modelling Study

Abstract

Background & aims: Hepatocellular carcinoma (HCC) presents a significant global health challenge, particularly among individuals with liver cirrhosis, with hepatitis C (HCV) a major cause. In people with HCV-related cirrhosis, an increased risk of HCC remains after cure. HCC surveillance with six monthly ultrasounds has been shown to improve survival. However, adherence to biannual screening is currently suboptimal. This study aimed to evaluate the effect of increased HCC surveillance uptake and improved ultrasound sensitivity on mortality among people with HCV-related cirrhosis post HCV cure.

Methods: This study utilized mathematical modelling to assess HCC progression, surveillance, diagnosis, and treatment among individuals with cirrhosis who had successfully been treated for HCV. The deterministic compartmental model incorporated Barcelona Clinic Liver Cancer (BCLC) stages to simulate disease progression and diagnosis probabilities in 100 people with cirrhosis who had successfully been treated for hepatitis C over 10 years. Four interventions were modelled to assess their potential for improving life expectancy: realistic improvements to surveillance adherence, optimistic improvements to surveillance adherence, diagnosis sensitivity enhancements, and improved treatment efficacy Results: Realistic adherence improvements resulted in 9.8 (95% CI 7.9, 11.6) life years gained per cohort of 100 over a 10-year intervention period; 17.2 (13.9, 20.3) life years were achieved in optimistic adherence improvements. Diagnosis sensitivity improvements led to a 7.0 (3.6, 13.8) year gain in life years, and treatment improvements improved life years by 9.0 (7.5, 10.3) years.

Conclusions: Regular HCC ultrasound surveillance remains crucial to reduce mortality among people with cured hepatitis C and cirrhosis. Our study highlights that even minor enhancements to adherence to ultrasound surveillance can significantly boost life expectancy across populations more effectively than strategies that increase surveillance sensitivity or treatment efficacy.

Keywords: Hepatitis C; alpha-fetoproteins; disease progression; early detection of cancer; epidemiologic surveillance; epidemiological models; hepatocellular carcinoma; life expectancy; liver cirrhosis.

Figure 1

A visual representation of the model. The base model simulates the progression of hepatocellular carcinoma in someone who is undiagnosed (with all people starting in the cirrhosis compartment). The treatment layer describes how once someone develops hepatocellular carcinoma, the model simulates patient diagnosis/treatment. Variables names are defined in Table 2 and Table 3.

Figure 2

Variables names are defined in Table 2 and Table 3. (A) A 95% confidence interval of the mean years spent in each BCLC stage. The dots correspond to the point estimates used in the model. (B) Bootstrap estimates for ultrasound sensitivity, with the cross representing the point estimate. The grey area is empty since the calibration assumes BCLC stage 0 ultrasound sensitivity must be lower than BCLC stage A ultrasound sensitivity. (C) The partial correlation coefficient between the bootstrap estimates for the model parameters and the status quo outcomes. The bootstrap parameter estimates were logit transformed. (D) The effect of a ±25% univariate change in model parameters that could be affected by the intervention and measured relative to baseline in a ten-year simulation of 100 people with cirrhosis.

Figure 3

Over a 10-year simulated intervention with 100 people, this figure shows how four scenarios affect the mean additional years of life attributable to each diagnosed case.