Quirino Lai1, Daniele Nicolini, Milton Inostroza Nunez, Samuele Iesari, Pierre Goffette, Andrea Agostini, Andrea Giovagnoni, Marco Vivarelli, Jan Lerut. 1. *Starzl Unit of Abdominal Transplantation, University Hospitals Saint Luc, Université catholique Louvain, Brussels, Belgium†Department of General Surgery and Organ Transplantation, L'Aquila University, L'Aquila‡Unit of Hepatobiliary surgery and Transplantation, Azienda Ospedaliero-Universitaria "Ospedali Riuniti," Torrette Ancona, Italy§Department of Radiology, Azienda Ospedaliero-Universitaria "Ospedali Riuniti," Torrette Ancona, Italy.
Abstract
OBJECTIVE: A novel and easy prognostic score based on the combination of pre-operatively available variables in patients with hepatocellular cancer (HCC) waiting for liver transplantation (LT) has been developed from a long waiting time (WT) training set and then validated in a short-WT set. SUMMARY OF BACKGROUND DATA: The role of radiological response to loco-regional therapies, alpha-fetoprotein modification, inflammatory markers, and length of WT has been recently shown to be important selection criteria for the risk of intention-to-treat (ITT)-death and recurrence. METHODS: The training set consisted of 179 HCC patients listed for LT during the period January 2000 to December 2012 from the UCL Brussels Transplant Centre; the validation set consisted of 110 patients listed during the period January 2005 to December 2014 from the Ancona Liver Centre. RESULTS: The proposed Time-Radiological-response-Alpha-fetoprotein-INflammation (TRAIN) score was the best predictor of microvascular invasion. A TRAIN score ≥1.0 excellently stratified both the investigated populations in terms of ITT and recurrence survivals. When compared with Milan criteria, the proposed score allowed obtaining an increase of potentially transplantable patients (+8.9% in training set and 24.6% in validation set) without additive recurrence risks. CONCLUSIONS: The proposed TRAIN score is an easy selection tool based on variables available before LT. This score enables the selection process to be refined in the 2 different scenarios of long and short WT. In case of longer WT, the score is better at predicting risk of death during the WT; in case of short WT, the score is better at identifying risk of post-LT recurrence.
OBJECTIVE: A novel and easy prognostic score based on the combination of pre-operatively available variables in patients with hepatocellular cancer (HCC) waiting for liver transplantation (LT) has been developed from a long waiting time (WT) training set and then validated in a short-WT set. SUMMARY OF BACKGROUND DATA: The role of radiological response to loco-regional therapies, alpha-fetoprotein modification, inflammatory markers, and length of WT has been recently shown to be important selection criteria for the risk of intention-to-treat (ITT)-death and recurrence. METHODS: The training set consisted of 179 HCC patients listed for LT during the period January 2000 to December 2012 from the UCL Brussels Transplant Centre; the validation set consisted of 110 patients listed during the period January 2005 to December 2014 from the Ancona Liver Centre. RESULTS: The proposed Time-Radiological-response-Alpha-fetoprotein-INflammation (TRAIN) score was the best predictor of microvascular invasion. A TRAIN score ≥1.0 excellently stratified both the investigated populations in terms of ITT and recurrence survivals. When compared with Milan criteria, the proposed score allowed obtaining an increase of potentially transplantable patients (+8.9% in training set and 24.6% in validation set) without additive recurrence risks. CONCLUSIONS: The proposed TRAIN score is an easy selection tool based on variables available before LT. This score enables the selection process to be refined in the 2 different scenarios of long and short WT. In case of longer WT, the score is better at predicting risk of death during the WT; in case of short WT, the score is better at identifying risk of post-LT recurrence.
Authors: Markus B Schoenberg; Julian N Bucher; Adrian Vater; Alexandr V Bazhin; Jingcheng Hao; Markus O Guba; Martin K Angele; Jens Werner; Markus Rentsch Journal: Dtsch Arztebl Int Date: 2017-08-07 Impact factor: 5.594