BACKGROUND: No staging systems of hepatocellular carcinoma (HCC) are tailored for assessing recurrence risk. We sought to establish a recurrence risk scoring system to predict recurrence of HCC patients receiving surgical curative treatment (liver resection or transplantation). METHODS: We retrospectively studied 286 HCC patients with preserved liver function receiving liver resection (n=184) or transplantation (n=102). Independent risk factors were identified to construct the recurrence risk scoring model. The recurrence free survival and discriminatory ability of the model were analyzed. RESULTS: Total tumor volume, HBsAg status, plasma fibrinogen level were included as independent prognostic factors for recurrence-free survival and used for constructing a 3-factor recurrence risk scoring model. The scoring model was as follows: 0.758 x HBsAg status (negative: 0; positive: 1) + 0.387 x plasma fibrinogen level (≤ 3.24 g/L: 0; >3.24 g/L: 1) + 0.633 x total tumor volume (≤ 107.5 cm3: 0; > 107.5 cm3: 1). The cut-off value was set to 1.02, and we defined the patients with the score ≤ 1.02 as a low risk group and those with the score > 1.02 as a high risk group. The 3-year recurrence-free survival rate was significantly higher in the low risk group compared with that in the high risk group (67.9% vs 41.3%, P < 0.001). In the subgroup analysis, liver transplantation patients had a better 3-year recurrence-free survival rate than the liver resection patients in the low risk group (80.0% vs 64.0%, P < 0.01). Additionally for patients underwent liver transplantation, we compared the recurrence risk model with the Milan criteria in the prediction of recurrence, and the 3-year recurrence survival rates were similar (80.0% vs 79.3%, P = 0.906). CONCLUSION: Our recurrence risk scoring model is effective in categorizing recurrence risks and in predicting recurrence-free survival of HCC before potential surgical curative treatment.
BACKGROUND: No staging systems of hepatocellular carcinoma (HCC) are tailored for assessing recurrence risk. We sought to establish a recurrence risk scoring system to predict recurrence of HCC patients receiving surgical curative treatment (liver resection or transplantation). METHODS: We retrospectively studied 286 HCC patients with preserved liver function receiving liver resection (n=184) or transplantation (n=102). Independent risk factors were identified to construct the recurrence risk scoring model. The recurrence free survival and discriminatory ability of the model were analyzed. RESULTS: Total tumor volume, HBsAg status, plasma fibrinogen level were included as independent prognostic factors for recurrence-free survival and used for constructing a 3-factor recurrence risk scoring model. The scoring model was as follows: 0.758 x HBsAg status (negative: 0; positive: 1) + 0.387 x plasma fibrinogen level (≤ 3.24 g/L: 0; >3.24 g/L: 1) + 0.633 x total tumor volume (≤ 107.5 cm3: 0; > 107.5 cm3: 1). The cut-off value was set to 1.02, and we defined the patients with the score ≤ 1.02 as a low risk group and those with the score > 1.02 as a high risk group. The 3-year recurrence-free survival rate was significantly higher in the low risk group compared with that in the high risk group (67.9% vs 41.3%, P < 0.001). In the subgroup analysis, liver transplantation patients had a better 3-year recurrence-free survival rate than the liver resection patients in the low risk group (80.0% vs 64.0%, P < 0.01). Additionally for patients underwent liver transplantation, we compared the recurrence risk model with the Milan criteria in the prediction of recurrence, and the 3-year recurrence survival rates were similar (80.0% vs 79.3%, P = 0.906). CONCLUSION: Our recurrence risk scoring model is effective in categorizing recurrence risks and in predicting recurrence-free survival of HCC before potential surgical curative treatment.
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
Authors: Jeroen Dekervel; Dusan Popovic; Hannah van Malenstein; Petra Windmolders; Line Heylen; Louis Libbrecht; Ashenafi Bulle; Bart De Moor; Eric Van Cutsem; Frederik Nevens; Chris Verslype; Jos van Pelt Journal: Transl Oncol Date: 2016-04 Impact factor: 4.243