Statistical perspectives on using hepatocellular carcinoma risk models to inform surveillance decisions

More than 50,000 people are diagnosed with hepatocellular carcinoma (HCC) every year in Europe. Many cases are known to specialist liver centres years before they present with HCC. Despite this, HCC is usually detected at a late stage, when prognosis is very poor. For more than two decades, clinical guidelines have recommended uniform surveillance for all patients with cirrhosis. However, studies continue to show that this broad-based approach is inefficient and poorly implemented in practice. A "personalised" approach, where the surveillance regimen is customised to the needs of the patient, is gaining growing support in the clinical community. The cornerstone of personalised surveillance is the HCC risk model - a mathematical equation predicting a patient's individualised probability of developing HCC within a specific time window. However, although numerous risk models have now been published, few are being used in routine care to inform HCC surveillance decisions. In this article, we discuss methodological issues stymieing the use of HCC risk models in routine practice - highlighting biases, evidence gaps and misconceptions that future research must address.