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 ATSd and ATSr represent ATS at the time of initial diagnosis and at the time of recurrence, respectively. The final model was ATSm = ATSd + 4 × ATSr. 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: ATSm ≤ 27, 74.9 months vs. ATSm ≥ 28, 23.3 months; VC: ATSm ≤ 27, 59.4 months vs. ATSm ≥ 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.
Development and Validation of an α-Fetoprotein Tumor Burden Score Model to Predict Postrecurrence Survival among Patients with Hepatocellular Carcinoma / Ding, H. -F.; Yang, T.; Lv, Y.; Zhang, X. -F.; Pawlik, T. M.; Ratti, F.; Marques, H. P.; Silva, S.; Soubrane, O.; Lam, V.; Poultsides, G. A.; Popescu, I.; Grigorie, R.; Alexandrescu, S.; Martel, G.; Guglielmi, A.; Hugh, T.; Aldrighetti, L.; Endo, I.. - In: JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS. - ISSN 1072-7515. - 236:5(2023), pp. 982-992. [10.1097/XCS.0000000000000638]
Development and Validation of an α-Fetoprotein Tumor Burden Score Model to Predict Postrecurrence Survival among Patients with Hepatocellular Carcinoma
Ratti F.;Silva S.;Aldrighetti L.;
2023-01-01
Abstract
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 ATSd and ATSr represent ATS at the time of initial diagnosis and at the time of recurrence, respectively. The final model was ATSm = ATSd + 4 × ATSr. 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: ATSm ≤ 27, 74.9 months vs. ATSm ≥ 28, 23.3 months; VC: ATSm ≤ 27, 59.4 months vs. ATSm ≥ 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
