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Sixty‐five gene‐based risk score classifier predicts overall survival in hepatocellular carcinoma
Author(s) -
Kim Soo Mi,
Leem SunHee,
Chu InSun,
Park YunYong,
Kim Sang Cheol,
Kim SangBae,
Park Eun Sung,
Lim Jae Yun,
Heo Jeonghoon,
Kim Yoon Jun,
Kim DaeGhon,
Kaseb Ahmed,
Park Young Nyun,
Wang Xin Wei,
Thorgeirsson Snorri S.,
Lee JuSeog
Publication year - 2012
Publication title -
hepatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.488
H-Index - 361
eISSN - 1527-3350
pISSN - 0270-9139
DOI - 10.1002/hep.24813
Subject(s) - medicine , framingham risk score , hepatocellular carcinoma , cohort , hazard ratio , proportional hazards model , oncology , confidence interval , hepatology , disease
Clinical application of the prognostic gene expression signature has been delayed due to the large number of genes and complexity of prediction algorithms. In the current study we aimed to develop an easy‐to‐use risk score with a limited number of genes that can robustly predict prognosis of patients with hepatocellular carcinoma (HCC). The risk score was developed using Cox coefficient values of 65 genes in the training set (n = 139) and its robustness was validated in test sets (n = 292). The risk score was a highly significant predictor of overall survival (OS) in the first test cohort ( P = 5.6 × 10 −5 , n = 100) and the second test cohort ( P = 5.0 × 10 −5 , n = 192). In multivariate analysis, the risk score was a significant risk factor among clinical variables examined together (hazard ratio [HR], 1.36; 95% confidence interval [CI], 1.13‐1.64; P = 0.001 for OS). Conclusion: The risk score classifier we have developed can identify two clinically distinct HCC subtypes at early and late stages of the disease in a simple and highly reproducible manner across multiple datasets. (H EPATOLOGY 2011)