The mortality of hepatocellular carcinoma (HCC) is rising, and it is projected to become the 3rd leading cause of cancer death in the U.S. by 2030. Given the association between early tumor detection and improved survival, multiple national professional societies recommend screening using abdominal ultrasound with or without a serum biomarker, alpha fetoprotein (AFP), every 6 months in at-risk individuals, including all patients with cirrhosis. However, most HCC patients are diagnosed at a late stage due to limitations in our current early detection strategy. The strategy of ultrasound and AFP for all cirrhosis patients is inadequate for 3 reasons: 1) It ignores heterogeneity in HCC risk between cirrhosis patients; 2) It ignores the poor accuracy of current screening tests; and 3) It ignores poor reliability of screening test performance between patients. Our proposal’s goal is to develop and evaluate a precision medicine strategy for early HCC detection in patients with cirrhosis that matches the best screening test to individual risk and screening test performance. We will leverage prospective cohort studies among 2000 patients with cirrhosis to evaluate the performance of risk stratification and early detection models incorporating novel biomarkers. Specifically, we propose to: Aim 1: Develop and validate the performance of risk stratification models incorporating a blood-based molecular signature panel to risk stratify cirrhosis patients for developing HCC Aim 2: Characterize and compare the performance of two biomarker-based early HCC detection strategies, the Doylestown Plus and a longitudinal biomarker algorithm, in a diverse cohort of patients with cirrhosis Aim 3: Compare the cost effectiveness, using micro-simulation modeling, of a tailored early detection strategy based on individual HCC risk and expected screening test performance to the current standard strategy of ultrasound and AFP in all patients with cirrhosis Our proposal leverages two prospective cohort studies with 2000 cirrhosis patients, to evaluate novel biomarker-based models for HCC risk stratification and early detection. We use these data to compare the effectiveness of a tailored early detection strategy to the current strategy of ultrasound and AFP for all patients using micro-simulation modeling. Tailoring early HCC detection efforts to individual risk and screening test performance moves beyond the current “one-size-fits-all” strategy and aligns HCC screening with the principles of precision medicine. Our proposed HCC early detection strategy would maximize screening benefits and minimize screening harms for each patient, thereby optimizing HCC screening value in the United States.