Author information
1
Division of Gastroenterology, Department of Medicine Veterans Affairs Puget Sound Healthcare System and University of Washington, Seattle WA, United States; Health Services Research and Development, Veterans Affairs Puget Sound Healthcare System, Seattle WA, United States. Electronic address: georgei@medicine.washington.edu.
2
Health Services Research and Development, Veterans Affairs Puget Sound Healthcare System, Seattle WA, United States.
3
Health Services Research and Development, Veterans Affairs Puget Sound Healthcare System, Seattle WA, United States; Division of General Internal Medicine, Department of Medicine Veterans Affairs Puget Sound Healthcare System and University of Washington, Seattle WA, United States.
4
Division of General Internal Medicine, Department of Medicine Veterans Affairs Puget Sound Healthcare System and University of Washington, Seattle WA, United States.
5
Department of Biostatistics, University of Washington, Seattle, WA, United States.
Abstract
BACKGROUND AND AIMS:
Most patients with hepatitis C virus (HCV) infection will undergo antiviral treatment with direct-acting antivirals (DAA) and achieve sustained virologic response (SVR). We aimed to develop models estimating HCC risk after antiviral treatment.
METHODS:
We identified 45,810 patients who initiated antiviral treatment in the Veterans Affairs (VA) national healthcare system from 1/1/2009 to 12/31/2015, including 29,309 (64%) DAA-only regimens and 16,501(36%) interferon ± DAA regimens. We retrospectively followed patients until 6/15/2017 to identify incident cases of HCC. We used Cox proportional hazards regression to develop and internally validate models predicting HCC risk using baseline characteristics at the time of antiviral treatment.
RESULTS:
We identified 1412 incident cases of HCC diagnosed at least 180 days after initiation of antiviral treatment during a mean follow-up of 2.5 years (range 1-7.5 years). Models predicting HCC risk after antiviral treatment were developed and validated separately for four sub-groups of patients: cirrhosis/SVR, cirrhosis/no SVR, no cirrhosis/SVR, no cirrhosis/no SVR. Four predictors (age, platelet count, serum AST/√ALT ratio and albumin) accounted for most of the prediction with smaller contributions from sex, race-ethnicity, HCV genotype, body mass index, hemoglobin and serum alpha fetoprotein. Fitted models were well-calibrated with very good measures of discrimination. Decision curves demonstrated higher net benefit of using model-based HCC risk estimates to determine whether to recommend screening or not compared to the screen-all or screen-none strategies.
CONCLUSIONS:
We developed and internally validated models that estimate HCC risk following antiviral treatment. These models are available as web-based tools that can be used to inform risk-based HCC surveillance strategies in individual patients.