The number of patients with liver cancer in the US has tripled over the past two decades, with most patients being diagnosed at late stages when curative treatments are no longer possible. As a result, liver cancer is the fastest growing cause of cancer-related death in the U.S. Liver cancer is particularly problematic for Texas, which has one of the highest incidence and mortality rates for liver cancer in the country. Based on findings from an expert panel, CPRIT has identified improving our approach to risk assessment and early detection of liver cancer as two high priority targets to reducing liver cancer mortality. Our proposal directly address both of these priorities. Our current stra...

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The number of patients with liver cancer in the US has tripled over the past two decades, with most patients being diagnosed at late stages when curative treatments are no longer possible. As a result, liver cancer is the fastest growing cause of cancer-related death in the U.S. Liver cancer is particularly problematic for Texas, which has one of the highest incidence and mortality rates for liver cancer in the country. Based on findings from an expert panel, CPRIT has identified improving our approach to risk assessment and early detection of liver cancer as two high priority targets to reducing liver cancer mortality. Our proposal directly address both of these priorities. Our current strategy is to perform an abdominal ultrasound and a blood test, alpha fetoprotein, in all patients with cirrhosis, the primary at-risk cohort in Texas and the U.S. However, this strategy is inadequate because it ignores 1) heterogeneity in HCC risk between patients, 2) poor accuracy of current screening tests, and 3) inconsistent performance of screening tests. To overcome these limitations, we propose to rigorously evaluate novel and promising risk stratification and early detection biomarkers in a phase III biomarker study, leveraging a prospective cohort of >3000 patients with cirrhosis from 4 sites in the Texas HCC Consortium (THCCC). Using a microsimulation model, we will demonstrate if a tailored early detection strategy incorporating our proposed risk stratification and early detection strategies will increase screening benefits (via early HCC detection) and minimize harms (via false positive results) for each individual patient, thereby optimizing overall value. These data would have the potential to immediately transform our approach to HCC risk assessment and early detection, thereby taking the first big step to reducing liver cancer mortality in Texas and the US.

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