Published in:
01-05-2018 | Original Article
Utility of Tumor Burden Score to Stratify Prognosis of Patients with Hepatocellular Cancer: Results of 4759 Cases from ITA.LI.CA Study Group
Published in: Journal of Gastrointestinal Surgery | Issue 5/2018
Login to get accessAbstract
Background
Dichotomous models like Milan Criteria represent the routinely used tools for predicting the outcome of patients with hepatocellular carcinoma (HCC). However, a paradigm shift from a dichotomous to continuous prognostic stratification should represent a good strategy for improving the prediction process. Recently, the tumor burden score (TBS) has been proposed for selecting patients with colorectal liver metastases. To date, TBS has not been validated in a large HCC population. The main objective of this study was to evaluate the prognostic power of TBS in an HCC population treated with different curative and palliative modalities.
Methods
Prospectively collected data from consecutive HCC patients managed in 24 institutions participating in the ITA.LI.CA group between Jan 2002 and Mar 2015 were analyzed (n = 4759). A sub-analysis focused on 3909 patients with the radiological evidence of vascular invasion or metastatic disease was also performed.
Results
TBS demonstrated the best discriminative ability when compared to MC and other tumor-specific scores. At multivariable Cox regression analysis, TBS was an independent risk factor of overall survival, with a 6% increased risk for patient death for each point increase in TBS. At survival analysis, when TBS ≥ 8 was connected with MELD ≥ 15 and alpha-fetoprotein ≥ 1000 ng/mL, patients presenting all these three risk factors presented the worst results (p value < 0.0001).
Conclusions
Survival prediction of HCC patients was very well done using TBS model, even stratifying the population in relation to the presence of metastases and/or vascular invasion. TBS model was the best in terms of discriminatory ability and goodness of fit when compared with other continuous or binary variables. Its incorporation in a model composed by tumor- and liver function-related variables further increases its survival prediction.