Laboratory-based algorithm predicts liver cancer in Hep C and cirrhosis

Monday, April 28, 2014

Laboratory-based algorithm predicts liver cancer in Hep C and cirrhosis

Laboratory-based algorithm predicts liver cancer in Hep C and cirrhosis

May's issue of Gastroenterology reports on a new laboratory-based algorithm to predict development of hepatocellular carcinoma in patients with Hepatitis C and cirrhosis.

Serum levels of α-fetoprotein (AFP) are influenced not only by the presence of hepatocellular carcinoma (HCC), but also by the underlying severity and activity of liver disease, which is reflected by liver function tests.

Dr Hashem El-Serag and colleagues from Texas, USA constructed an AFP-based algorithm that included these factors to identify patients at risk for HCC, and tested its predictive ability in a large set of patients with cirrhosis.

The team used used the national Department of Veterans Affairs Hepatitis C Virus Clinical Case Registry to identify patients with cirrhosis, results from at least 1 AFP test, and 6 months of follow-up.

The researchers' algorithm included data on age, levels of aspartate aminotransferase, alanine aminotransferase (ALT), alkaline phosphatase, total bilirubin, albumin, creatinine, and hemoglobin, prothrombin time, and numbers of platelets and white cells.

The team examined the operating characteristics (calibration, discrimination, predictive values) of several different algorithms for identification of patients who would develop HCC within 6 months of the AFP test.

The probabilities of HCC, based only on 120 ng/mL AFP, were 11%

Gastroenterology

The research team assessed our final model in the development and validation subsets.

The team identified 11,721 patients with hepatitis C virus−related cirrhosis in whom 35,494 AFP tests were performed, and 987 patients developed HCC.

A predictive model that included data on levels of AFP, ALT, and platelets, along with age at time of AFP test, best discriminated between patients who did and did not develop HCC.
Using this AFP-adjusted model, the predictive accuracy increased at different AFP cutoffs compared with AFP alone.

At any given AFP value, low numbers of platelets and ALT and older age were associated with increased risk of HCC, and high levels of ALT and normal/high numbers of platelets were associated with low risk for HCC.

For example, the probabilities of HCC, based only on 20 ng/mL and 120 ng/mL AFP, were 4% and 11%, respectively.

However, the team noted that patients with the same AFP values who were 70 years old, with ALT levels of 40 IU/mL and platelet counts of 100,000, had probabilities of developing HCC of 8% and 29%, respectively.

Dr El-Serag's team concludes, "We developed and validated an algorithm based on levels of AFP, platelets, and ALT, along with age, which increased the predictive value for identifying patients with hepatitis C virus−associated cirrhosis likely to develop HCC within 6 months."

"If validated in other patient groups, this model would have immediate clinical applicability."