Taiwan offers new model to predict hepatitis C cancer risk...

Posted on Focus Taiwan News Channel on 2/19/12. At the Conference for Asian Pacific Association for the Study of the Liver,  Taiwanese researchers presented a successful new predictive model to calculate the likelihood of patients developing liver cancer.  They claim a 80% accuracy rate and hope that the model bolsters their hypothesis that treating HCV and HBV early can help prevent liver cancer.

Taiwan offers new model to predict hepatitis C cancer risk
2012/02/19 20:14:20


Taipei, Feb. 19 (CNA) A Taiwan-led research team has successfully devised a new prediction model to calculate the likelihood of hepatitis C patients developing liver cancer, the team leader said Sunday.

The model incorporates indicators such as age, the liver function indexes ALT and AST, hepatitis C virus RNA in serum, cirrhosis and the genotype of the virus, said Chen Chien-jen at a session of the Conference of the Asian Pacific Association for the Study of the Liver held in Taipei.

Chen, vice president of Taipei-based Academia Sinica, said the serum data was particularly important in predicting the chances of developing liver cancer.

The model, which can predict a result with 80 percent accuracy, assigns a score on 0-25 scale to analyze each case. The higher the score, the higher the risk of getting liver cancer, Chen said.

Hepatitis B and C viruses are the main causes of liver cancer in Taiwan, Chen said, with 20-25 percent of liver cancer cases triggered by the hepatitis C virus and 70-75 percent by the hepatitis B virus.

Close to 3 million people in Taiwan's 23-million population carry the hepatitis B virus, while some 600,000 carry the hepatitis C virus, according to the Department of Health.

With the model, "we hope to identify those facing higher risk of getting liver cancer and treat them as early as possible," Chen said.

Chen's team also launched a model in 2010 to calculate the chances of the hepatitis B virus developing into liver cancer.

In the future, the prediction models will be available on the Internet and in apps on smartphones to allow individuals to determine their own risk factor, Chen said.