Tumor Burden Score and Serum Alpha-fetoprotein Subclassify Intermediate-Stage Hepatocellular Carcinoma

PIVKA‐II combined with tumor burden score to predict long‐term outcomes of AFP‐negative hepatocellular carcinoma patients after liver resection

“…32 Therefore, some studies investigated the synergetic impact of morphological characteristics and biological characteristics (tumor markers, e.g., AFP) on long-term outcomes of HCC patients after hepatectomy and demonstrated the good performance of the combination of TBS and AFP in stratifying the OS of HCC patients after liver resection. 12,18,19,33,34 relationship between the synergetic impact of combining TBS and PIVKA-II and survival outcomes of AFPnegative HCC patients within BCLC 0/A/B after liver resection. We established a simple prognostic scoring model (TPS model) based on TBS and preoperative PIVKA-II levels and demonstrated that the TPS model had excellent performance in stratifying OS and early recurrence in AFP-negative HCC patients after liver resection.…”

“…[15][16][17] Thus, whether combine AFP and TBS could predict survival outcomes of HCC patients after liver resection is an interesting topic, and several studies have demonstrated the synergistic effect of both in predicting the postoperative prognosis of HCC patients. 12,[18][19][20] However, it is worth noting that AFP (at a threshold level of 20 ng/mL) has a limited ability to detect HCC (sensitivity of 40%-60% with specificity of 80-90%), which means that a proportion of HCC patients have negative AFP levels (< 20 ng/mL) at diagnosis, especially for small HCC patients. 21 Protein induced by vitamin K deficiency II (PIVKA-II) was identified for the first time in 1968 and was demonstrated to be a potential biomarker supplementing AFP for the diagnosis of HCC in many studies.…”

“…Serum α‐fetoprotein (AFP) is a typical tumor biomarker of HCC and plays a crucial function in monitoring, diagnosing, and determining the prognosis of HCC patients 15–17 . Thus, whether combine AFP and TBS could predict survival outcomes of HCC patients after liver resection is an interesting topic, and several studies have demonstrated the synergistic effect of both in predicting the postoperative prognosis of HCC patients 12,18–20 …”

Machine‐Based Learning Hierarchical Cluster Analysis: Sex‐Based Differences in Prognosis Following Resection of Hepatocellular Carcinoma

“…Preoperative variables of interest included sex, age, BMI, liver disease etiology (i.e., hepatitis B virus [HBV], hepatitis C virus [HCV], non‐alcoholic steatohepatitis [NASH] and other), presence of cirrhosis, platelet count (PLT), liver function (i.e., albumin‐bilirubin [ALBI] grade) [13], inflammation based‐scores (prognostic nutritional index [PNI]), immune status indices (i.e., SII: Platelet count x neutrophil count: lymphocyte count, NLR, PLR), and tumor‐related indicators (largest tumor size, number, AFP). Tumor burden score (TBS) was calculated by applying the Pythagorean theorem so that TBS 2 = (maximum tumor diameter) 2 + (number of tumors) 2 , where tumor diameter and number of tumors were extracted based on preoperative imaging data to allow for a cluster analysis based on preoperative factors [14]. Barcelona Clinic Liver Cancer (BCLC) staging was defined as very early, early, intermediate and advanced, based on the latest BCLC classification [15].…”

“…Tumor burden score (TBS) was calculated by applying the Pythagorean theorem so that TBS 2 = (maximum tumor diameter) 2 ? (number of tumors) 2 , where tumor diameter and number of tumors were extracted based on preoperative imaging data to allow for a cluster analysis based on preoperative factors [14]. Barcelona Clinic Liver Cancer (BCLC) staging was defined as very early, early, intermediate and advanced, based on the latest BCLC classification [15].…”