4.7 Article

Estrogen receptor classification for hepatocellular carcinoma:: Comparison with clinical staging systems

Journal

JOURNAL OF CLINICAL ONCOLOGY
Volume 21, Issue 3, Pages 441-446

Publisher

AMER SOC CLINICAL ONCOLOGY
DOI: 10.1200/JCO.2003.11.051

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Purpose: Several scoring systems to evaluate patients with hepatocellular carcinoma (HCC) exist. A good scoring system should provide information on prognosis and guide therapeutic decisions. The presence of variant liver estrogen receptor (ER) transcripts in the tumor has been shown to be the strongest negative predictor of survival in HCC. The aim of this study was to compare the predictive value of the commonly applied clinical scoring systems for survival of patients with HCC with that of the evaluation of ER in patients with HCC (molecular scoring system). Materials and Methods: HCC was staged according to the Okuda classification, Barcelona Clinic Liver Cancer classification, Italian classification system (CLIP), French classification, and ER status in 96 patients. Analysis of survival was performed according to the Kaplan-Maier test and was made for each classification system and ER. A comparison between classifications was made by univariate and multivariate analysis. Results: Among the clinical classification systems, only the CLIP was able to identify patient populations with good, intermediate, and poor prognosis. On multivariate analysis, ER classification was shown to be the best predictive classification for survival of patients with HCC (P < .0001). This difference was the result of a better allocation of patients with ominous prognosis (variant ER) having nevertheless good clinical score. Conclusion: The evaluation of the presence of wild-type or variant ER transcripts in the tumor is the best predictor of survival in patients with HCC. Its accuracy in discriminating patients with good or unfavorable prognosis is significantly greater than that of the commonly used scoring systems for the staging of HCC. (C) 2003 by American Society of Clinical Oncology.

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