Development of predictive model for liver cancer incidence of chronic hepatitis B patients

[이데일리 이순용 기자]Professor Ahn Sang-bong of the Department of Gastrointestinal Internal Medicine of Nowon Eulji University Hospital presented the results of a study that made a predictive model for liver cancer in patients with chronic hepatitis B.

Liver cancer is one of the cancers with high incidence and mortality in Korea, and chronic hepatitis B is the main cause. As chronic hepatitis B treatment advances, the incidence of liver cancer is decreasing, but it is still too early to be relieved. As such, the relationship between the two diseases is high, so if you are a chronic hepatitis B patient, you need to be aware of the risk of developing liver cancer in advance and try to prevent it.

Professor Ahn Sang-Bong said, “What is noteworthy in this study is that, unlike previous liver cancer prediction models, only patients who are actually undergoing hepatitis B treatment were targeted. Through this, it was found that 12 months after the start of hepatitis B treatment is the time point for the highest predicted liver cancer. This study confirms that active follow-up is necessary for patients with a high incidence rate through a model for predicting the incidence of liver cancer in the actual clinical field. As a result, it will play a big role in early detection of liver cancer.”

In general, patients with chronic hepatitis B are treated with antiviral therapy. This is to slow the progression of hepatitis. Prof. Ahn confirmed that hematological findings stabilized at 12 months after the start of antiviral therapy. In other words, it was proved that the presence or absence of cirrhosis, platelet count after 12 months of treatment, and AFP level had the most significant influence on predicting liver cancer incidence.

Based on this, data on patients with hepatitis B from Stanford University in the United States were simultaneously used as well as data on patients who used antiviral drugs as an initial treatment for chronic hepatitis B in Korea. As a result, we created a model with the highest prediction rates in both countries.

This paper was recently published in Liver International.

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