BACKGROUND: 

The purpose of this study is to establish a prognostic model to predict postrecurrence survival (PRS) probability after initial resection of hepatocellular carcinoma (HCC).

STUDY DESIGN: 

Patients with recurrent HCC after curative resection were identified through a multicenter consortium (training cohort, TC); data were from a separate institution were used as validation cohort (VC). The α-fetoprotein (AFP) tumor burden score (ATS) was defined as the distance from the origin on a 3-dimensional Cartesian coordinate system that incorporated 3 variables: largest tumor diameter (x axis), number of tumors (y axis), and ln AFP (z axis). ATS was calculated using the Pythagorean theorem: ATS² = (largest tumor diameter)² + (number of tumors)² + (ln AFP)², where ATS_d and ATS_r represent ATS at the time of initial diagnosis and at the time of recurrence, respectively. The final model was ATS_m = ATS_d + 4 × ATS_r. Predictive performance and discrimination of the ATS model were evaluated and compared with traditional staging systems.

RESULTS: 

The ATS model demonstrated strong predictive performance of PRS in both the TC (area under the curve [AUC] 0.70) and VC (AUC 0.71). An ATS-based nomogram was able to stratify patients accurately into low- and high-risk categories relative to PRS (TC: ATS_m ≤ 27, 74.9 months vs. ATS_m ≥ 28, 23.3 months; VC: ATS_m ≤ 27, 59.4 months vs. ATS_m ≥ 28, 15.1 months; both p < 0.001). The ATS model predicted PRS among patients undergoing curative or noncurative treatment of HCC recurrence (both p < 0.05). Of note, the ATS model outperformed the Barcelona Clinic Liver Cancer (BCLC), China Liver Cancer (CNLC), and American Joint Committee on Cancer (AJCC) staging systems relative to 1-, 2-, 3-, 4- and 5-year PRS (AUC 0.70, vs. BCLC, AUC 0.50, vs. CNLC, AUC 0.54, vs. AJCC, AUC 0.51).

CONCLUSIONS: 

The ATS model had excellent prognostic discriminatory power to stratify patients relative to PRS.