For HCV patients, new online calculator predicts HCC risk after treatment

Naveed Saleh, MD, MS, for MDLinx | October 03, 2018

Experts have designed and validated models to predict the risk of hepatocellular carcinoma (HCC) in patients infected with hepatitis C virus (HCV) following antiviral treatment, according to new research published in the Journal of Hepatology.

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Researchers have developed an online calculator that estimates an HCV-infected patient’s risk for hepatocellular carcinoma after antiviral treatment.

From these models, the researchers designed an online calculator, now available at www.hccrisk.com, that estimates a patient’s HCC risk after treatment.

“It is important that we can model the risk of hepatocellular carcinoma in these patients, so that we develop the optimum screening strategy that avoids unnecessary screening, while adequately screening those at increased risk,” wrote authors led by George N. Ioannou, MD, MS, Division of Gastroenterology, Department of Medicine, Veterans Affairs Puget Sound Healthcare System, University of Washington, Seattle, WA.

Most Americans with chronic HCV are now treated with direct-acting antivirals (DAAs) for 3 to 5 years. This treatment eradicates HCV in the majority of these patients, with sustained virologic response (SVR) rates exceeding 90%. After achieving SVR, the risk of HCC is significantly reduced.

“It follows that HCC risk needs to be estimated specifically for the period following antiviral treatment, incorporating whether SVR was achieved or not, and that previous models predicting HCC risk in untreated HCV-infected patients do not apply to patients who have undergone antiviral treatment,” the authors wrote.

Although current guidelines call for screening HCV-infected patients with cirrhosis, there is no such mandate for non-cirrhotic HCV-infected individuals, despite the HCC risk. This “one-size-fits-all” strategy is problematic in the age of DAA treatment and, according to the authors, requires improvement.

In this study, Dr. Ioannou and colleagues used the Veterans Affairs (VA) national database to identify 45,810 patients (mean age 55.8 years) who started HCV antiviral treatment from the start of 2009 to the end of 2015. Of these, 64% were treated with DAAs only and 36% were given interferon with or without DAAs. Patients were retrospectively followed for an average of 2.5 years to identify HCC incident cases diagnosed for the first time within 180 days of antiviral treatment initiation. Among all patients, 23% had a diagnosis of cirrhosis and 74% achieved SVR.

The team used Cox proportional hazards regression to formulate and validate models predicting HCC risk by means of baseline characteristics at the time of antiviral treatment. They used an iterative process to determine which predictors to use in the final models. Of note, four predictors ended up accounting for most of the models’ predictive value: age, platelet count, serum aspartate aminotransferase/alanine aminotransferase ratio, and albumin.

“Our models estimate HCC risk based on simple, readily available, objective, and reproducible predictors and thus can be utilized easily in clinical practice,” wrote the researchers.

The investigators found that their models outperformed all-or-none screening strategies. Moreover, SVR, along with several other patient characteristics, modified HCC risk substantially, thereby discounting the sole use of cirrhosis as the criterion upon which HCC surveillance is determined. They suggested that their models be used to estimate HCC risk first and then surveillance strategies be determined based on risk.

The researchers suggested that estimating HCC risk using their models could enhance HCC surveillance efforts, boost early detection of HCC, and decrease harm associated with needless surveillance.

They acknowledged that their study may be limited by the analysis of data from a VA-exclusive cohort with few women, and suggested that their results be externally validated in a non-VA population, preferably one undergoing HCC surveillance.

“These models, which are available as web-based tools (www.hccrisk.com), can help stratify patients according to HCC risk, and consequently help determine an appropriate screening strategy based on a patient’s calculated risk,” the authors concluded. “A screening strategy targeting those who exceed a certain predetermined HCC risk may be more efficacious and cost-effective than the current ‘screen-all’ or ‘screen-none’ strategies, which depend solely on cirrhosis status.”

This study was funded by the National Institutes of Health/National Cancer Institute and the US Department of Veteran Affairs Office of Clinical Science Research and Development.

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