Comparative analysis of the predictive value of the ASAP model and the GAAD model for liver cancer high risk cohorts

The ASAP Model and GAAD Model integrate gender, age, AFP, and PIVKA-II to predict hepatocellular carcinoma (HCC) risk. This study compared their diagnostic performance in a high-risk cohort. A total of 352 subjects were enrolled, including 115 HCC patients, 137 with chronic liver disease (CLD), and 100 healthy controls (HCs). Serum AFP and PIVKA-II levels were measured using Abbott and Roche assays, respectively. ASAP and GAAD scores were calculated. Using manufacturer-recommended cutoffs and predefined thresholds (ASAP ≥ 33.4%, ASAP ≥ 66.7%, GAAD ≥ 2.57), we evaluated the diagnostic performance of each model. Area under the receiver operating characteristic curves (AUCs) were compared using the DeLong test. In the HCC group, both the median values and positive rates for ASAP and GAAD scores were significantly higher than those observed in the CLD group and HCs (P < 0.01). ASAP ≥ 33.4% showed the highest sensitivity (0.974), although its specificity was lower (0.658). ASAP ≥ 66.7% exhibited the highest specificity (0.894) and accuracy (0.901). However, neither threshold could definitively exclude HCC in low-risk ranges. For Test Cohort 1 (including the HCC group and other non-HCC groups), the AUCs for ASAP and GAAD scores were 0.955 and 0.958, respectively (P = 0.610). For Test Cohort 2 (including HCC and CLD groups), the AUCs for ASAP and GAAD scores were 0.926 and 0.928 (P = 0.810). For Test Cohort 3 (including the CLD and HCs groups), the AUCs for ASAP and GAAD scores were 0.833 and 0.832 (P = 0.944). Both ASAP and GAAD demonstrated excellent diagnostic performance for HCC, significantly outperforming single tumor markers. No significant differences were observed between the two models across all risk cohorts, suggesting their comparable clinical utility.