Simple Test Predicts Risk of Severe Liver Disease

Severe liver diseases such as cirrhosis and liver cancer are becoming increasingly common and often carry a poor prognosis when detected late. Current screening tools are limited in their ability to identify people at risk early, leaving many patients undiagnosed until the disease has progressed. Researchers have now demonstrated that a simple blood analysis can predict the risk of developing severe liver disease up to 10 years in advance, offering a pathway for earlier detection.

A team of researchers at Karolinska Institutet (Stockholm, Sweden), along with Finnish collaborators, has developed a model called CORE to estimate risk using advanced statistical methods. The model is based on five factors: age, sex, and levels of three common liver enzymes (AST, ALT, and GGT), which are routinely measured during standard health checks. To facilitate use in primary care, a web-based calculator has already been launched, enabling doctors and nurses to apply the tool easily.

The study analyzed data from more than 480,000 people in Stockholm who underwent health checks between 1985 and 1996. Participants were followed for up to 30 years, during which about 1.5 percent developed severe liver disease, including cirrhosis, liver cancer, or the need for a liver transplant. The findings, published in The BMJ, shows that the CORE model can accurately identify individuals most likely to develop severe liver disease.

The results demonstrated that the CORE model correctly differentiated between those who developed disease and those who did not in 88 percent of cases, outperforming the widely used FIB-4 method. Importantly, it proved accurate not only in Swedish participants but also when tested on populations in Finland and the UK. Researchers note, however, that further validation is needed in groups at especially high risk, such as individuals with obesity or type 2 diabetes.

The study highlights the potential for CORE to be integrated into primary care settings where most patients first seek medical attention. Early identification could enable timely interventions, including drug treatments that are becoming available for people at high risk of cirrhosis or liver cancer. Future steps include embedding the model into medical record systems and further evaluating its performance in diverse patient groups.

“These are diseases that are growing increasingly common and that have a poor prognosis if detected late,” said Rickard Strandberg, one of the developers of the new test. “Our method can predict the risk of severe liver disease within 10 years and is based on three simple routine blood tests.”

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