Development and Validation of an α-Fetoprotein Tumor Burden Score Model to Predict Postrecurrence Survival among...

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

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: ATS 2 = (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.

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).

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