Dynamic risk assessment for hepatocellular carcinoma in patients with chronic hepatitis C.

Autor: Lu, Mei, Salgia, Reena, Li, Jia, Trudeau, Sheri, Rupp, Loralee B., Wu, Trueman, Daida, Yihe G., Schmidt, Mark A., Gordon, Stuart C.
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Zdroj: Journal of Viral Hepatitis; Sep2023, Vol. 30 Issue 9, p746-755, 10p
Abstrakt: Chronic hepatitis C (HCV) is a primary cause of hepatocellular carcinoma (HCC). Although antiviral treatment reduces risk of HCC, few studies quantify the impact of treatment on long‐term risk in the era of direct‐acting antivirals (DAA). Using data from the Chronic Hepatitis Cohort Study, we evaluated the impact of treatment type (DAA, interferon‐based [IFN], or none) and outcome (sustained virological response [SVR] or treatment failure [TF]) on risk of HCC. We then developed and validated a predictive risk model. 17186 HCV patients were followed until HCC, death or last follow‐up. We used extended landmark modelling, with time‐varying covariates and propensity score justification and generalized estimating equations with a link function for discrete time‐to‐event data. Death was considered a competing risk. We observed 586 HCC cases across 104,000 interval‐years of follow‐up. SVR from DAA or IFN‐based treatment reduced risk of HCC (aHR 0.13, 95% CI 0.08–0.20; and aHR 0.45, 95% CI 0.31–0.65); DAA SVR reduced risk more than IFN SVR (aHR 0.29, 95% CI 0.17–0.48). Independent of treatment, cirrhosis was the strongest risk factor for HCC (aHR 3.94, 95% CI 3.17–4.89 vs. no cirrhosis). Other risk factors included male sex, White race and genotype 3. Our six‐variable predictive model had 'excellent' accuracy (AUROC 0.94) in independent validation. Our novel landmark interval‐based model identified HCC risk factors across antiviral treatment status and interactions with cirrhosis. This model demonstrated excellent predictive accuracy in a large, racially diverse cohort of patients and could be adapted for 'real world' HCC monitoring. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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