TY - JOUR
T1 - International validation of a natural-killer-cell–based model to predict recurrence-free survival in hepatocellular carcinoma
AU - Akabane, Miho
AU - Kawashima, Jun
AU - Woldesenbet, Selamawit
AU - Cauchy, François
AU - Aucejo, Federico
AU - Popescu, Irinel
AU - Kitago, Minoru
AU - Martel, Guillaume
AU - Ratti, Francesca
AU - Aldrighetti, Luca
AU - Poultsides, George A.
AU - Imaoka, Yuki
AU - Ruzzenente, Andrea
AU - Endo, Itaru
AU - Gleisner, Ana
AU - Marques, Hugo P.
AU - Lam, Vincent
AU - Hugh, Tom
AU - Bhimani, Nazim
AU - Shen, Feng
AU - Pawlik, Timothy M.
PY - 2025/10
Y1 - 2025/10
N2 - Background: Models estimating recurrence-free survival (RFS) after hepatectomy for hepatocellular carcinoma (HCC) rely on clinical variables and often overlook tumor immunobiology. The Liver Immune Status Index (LISI), derived from BMI, albumin, and Fibrosis-4 (FIB-4), reflects liver-resident natural killer (NK) cell activity. We validated the HISCO-HCC score, combining LISI, tumor burden score (TBS), and alpha-fetoprotein (AFP), using an international cohort. Methods: Patients undergoing curative-intent hepatectomy for HCC (2000–2023) were identified from an international database (median follow-up: 38.9 [14.9–67.5] months). RFS was the primary endpoint. LISI's predictive performance was compared with other liver-related indices. The original HISCO-HCC (oHISCO-HCC) was recalibrated via multivariable Cox regression in a training cohort (80 %) stratified by region, yielding a modified score (mHISCO-HCC). Validation was conducted in the testing cohort (20 %). Results: Among 1213 patients, LISI had the highest AUCs among liver-related indices for 1-/2-year RFS (0.60/0.60) and 1-/5-year OS (0.64/0.60). The formula: mHISCO-HCC = 0.49 × TBS + 0.41 × log(AFP) + 0.13 × LISI. In testing, mHISCO-HCC outperformed oHISCO-HCC and mHALT-HCC for 12-/36-/60-month RFS (AUCs: 0.73/0.71/0.66) with the lowest AIC. It also had the highest OS AUCs and stratified RFS and OS (p < 0.001). Conclusions: The mHISCO-HCC score, integrating tumor morphology, biology, and NK cell-based immunity, improves prediction of recurrence and survival. It may aid postoperative stratification.
AB - Background: Models estimating recurrence-free survival (RFS) after hepatectomy for hepatocellular carcinoma (HCC) rely on clinical variables and often overlook tumor immunobiology. The Liver Immune Status Index (LISI), derived from BMI, albumin, and Fibrosis-4 (FIB-4), reflects liver-resident natural killer (NK) cell activity. We validated the HISCO-HCC score, combining LISI, tumor burden score (TBS), and alpha-fetoprotein (AFP), using an international cohort. Methods: Patients undergoing curative-intent hepatectomy for HCC (2000–2023) were identified from an international database (median follow-up: 38.9 [14.9–67.5] months). RFS was the primary endpoint. LISI's predictive performance was compared with other liver-related indices. The original HISCO-HCC (oHISCO-HCC) was recalibrated via multivariable Cox regression in a training cohort (80 %) stratified by region, yielding a modified score (mHISCO-HCC). Validation was conducted in the testing cohort (20 %). Results: Among 1213 patients, LISI had the highest AUCs among liver-related indices for 1-/2-year RFS (0.60/0.60) and 1-/5-year OS (0.64/0.60). The formula: mHISCO-HCC = 0.49 × TBS + 0.41 × log(AFP) + 0.13 × LISI. In testing, mHISCO-HCC outperformed oHISCO-HCC and mHALT-HCC for 12-/36-/60-month RFS (AUCs: 0.73/0.71/0.66) with the lowest AIC. It also had the highest OS AUCs and stratified RFS and OS (p < 0.001). Conclusions: The mHISCO-HCC score, integrating tumor morphology, biology, and NK cell-based immunity, improves prediction of recurrence and survival. It may aid postoperative stratification.
UR - http://www.scopus.com/inward/record.url?scp=105010969602&partnerID=8YFLogxK
U2 - 10.1016/j.hpb.2025.06.011
DO - 10.1016/j.hpb.2025.06.011
M3 - Article
C2 - 40683791
AN - SCOPUS:105010969602
SN - 1365-182X
VL - 27
SP - 1259
EP - 1269
JO - HPB
JF - HPB
IS - 10
ER -