Validation of the hepatocellular carcinoma early detection screening algorithm Doylestown and aMAP in a cohort of Chinese with cirrhosis

Previous studies have developed some blood-based biomarker algorithms such as the Doylestown algorithm and aMAP score to improve the detection of Hepatocellular carcinoma (HCC). However, no one has studied the application of the Doylestown algorithm in the Chinese. Meanwhile, which of these two screening models is more suitable for people with liver cirrhosis remains to be investigated.In this study, HCC surveillance was performed by radiographic imaging and testing for tumor markers every 6 months from August 21, 2018, to January 12, 2021. We conducted a retrospective study of 742 liver cirrhosis patients, and among them, 20 developed HCC during follow-up. Samples from these patients at three follow-up time points were tested to evaluate alpha-fetoprotein (AFP), the Doylestown algorithm, and aMAP score.Overall, 521 liver cirrhosis patients underwent semiannual longitudinal follow-up three times. Five patients were diagnosed with HCC within 0-6 months of the third follow-up. We found that for these liver cirrhosis patients, the Doylestown algorithm had the highest accuracy for HCC detection, with areas under the receiver operating characteristic curve (AUCs) of 0.763, 0.801, and 0.867 for follow-ups 1-3, respectively. Compared with AFP at 20 ng/ml, the Doylestown algorithm increased biomarker performance by 7.4%, 21%, and 13% for follow-ups 1-3, respectively.Our findings show that the Doylestown algorithm performance appeared to be optimal for HCC early screening in the Chinese cirrhotic population when compared with the aMAP score and AFP at 20 ng/ml.