The detection of hepatocellular carcinoma using a prospectively developed and validated model based on serological biomarkers.

BACKGROUND: Hepatocellular carcinoma is a common complication of chronic liver disease (CLD), and is conventionally diagnosed by radiological means. We aimed to build a statistical model that could determine the risk of hepatocellular carcinoma in individual patients with CLD using objective measures, particularly serological tumor markers.
METHODS: A total of 670 patients with either CLD alone or hepatocellular carcinoma were recruited from a single UK center into a case-control study. Sera were collected prospectively and specifically for this study. A logistic regression analysis was used to determine independent factors associated with hepatocellular carcinoma and a model built and assessed in terms of sensitivity, specificity, and proportion of correct diagnoses.
RESULTS: The final model involving gender, age, AFP-L3, α fetoprotein (AFP), and des-carboxy-prothrombin ("GALAD") was developed in a "discovery" data set and validated in independent data sets both from the same institution and from an external institution. When optimized for sensitivity and specificity, the model gave values of more than 0.88 irrespective of the disease stage.
CONCLUSIONS: The presence of hepatocellular carcinoma can be detected in patients with CLD on the basis of a model involving objective clinical and serological factors. It is now necessary to test the model's performance in a prospective manner and in a routine clinical practice setting, to determine if it may replace or, more likely, enhance current radiological approaches. IMPACT: Our data provide evidence that an entirely objective serum biomarker-based model may facilitate the detection and diagnosis of hepatocellular carcinoma and form the basis for a prospective study comparing this approach with the standard radiological approaches.