Abstract

Objective: To validate the performance of a multi-omics combined test for early screening of high-risk liver cancer populations. Methods: 173 high-risk patients with liver cancer were prospectively screened in a real-world setting, and 164 cases were finally enrolled. B-ultrasound, alpha-fetoprotein (AFP), and HCC screens were conducted in all patients. A multi-omics early screening test was performed for liver cancer in combination with multi-gene methylation, TP53/TERT/CTNNB1 mutations, AFP, and abnormal prothrombin (PIVKA-II). Differences in rates were compared using the chi-square test, adjusted chi-square test, or Fisher's exact probability method for count data. A non-parametric rank test (Mann-Whitney) was used to compare the differences between the two groups of data. Results: The HCCscreen detection had a sensitivity of 100% for liver cancer screening, 93.8% for liver cancer and precancerous diseases, 34.1% for positive predictive value, 99.2% for negative predictive value, and 0.89 for an area under the curve (AUC). Parallel detection of AFP, AFP+B-ultrasound, and methylation+mutation had a sensitivity/specificity and AUC of 31.3%/88.5% (AUC=0.78), 56.3%/88.2% (AUC=0.86), and 81.3%/82.4 % (AUC=0.84). At the same time, the disease severity range was significantly correlated with the methylation+mutation score, HCCscreen score, or positive detection rate (PDR). There was no significant correlation between AFP serum levels and methylation+mutation or HCCscreen scores, while there was a significant linear correlation between methylation+mutation scores and HCCscreen scores (r = 0.73, P < 0.001). Conclusion: In real-world settings, HCCscreen shows high sensitivity for screening opportunistic, high-risk liver cancer populations. Furthermore, it may efficaciously detect liver cancer and precancerous diseases, with superior performance to AFP and AFP+ultrasound. Hence, HCCscreen has the potential to become an effective screening tool that is superior to existing screening methods for high-risk liver cancer populations.

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