유전자료를 이용한 악성 간암환자 나무구조 생존예측 모형연구
Tree Structured Prognostic Survival Model for Hepatocellular Carcinoma using Gene Expression Data
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참고문헌
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초록
A tree-structured method for analyzing censored survival data is attractive for several reasons. The association between survival time and covariates is easy to interpret even if the covariates are numerous and there are interactions among them. Moreover a tree-structured method using gene expression data gives additional insight into the role of the covariates. Recent SNP data analysis makes it possible to find out large numbers of gene related with human cancers and to support accurate diagnosis of human cancers according to their several pathological judgements. The purpose of this study was designed to evaluate the prognosis of HCC in relation to treatment methods and their affecting gene and clinical factors by tree structured model. We could identify a feature set of 44 genes to distinguish the status of HCC and non-tumor liver tissues. Our proposed survival tree model shows the genes related with clinical, pathological data and risk factors of HCC. These findings could be available to predict prognosis of HCC and give valuable information to justify the treatment strategy for clinician.
Abstract
A tree-structured method for analyzing censored survival data is attractive for several reasons. The association between survival time and covariates is easy to interpret even if the covariates are numerous and there are interactions among them. Moreover a tree-structured method using gene expression data gives additional insight into the role of the covariates. Recent SNP data analysis makes it possible to find out large numbers of gene related with human cancers and to support accurate diagnosis of human cancers according to their several pathological judgements. The purpose of this study was designed to evaluate the prognosis of HCC in relation to treatment methods and their affecting gene and clinical factors by tree structured model. We could identify a feature set of 44 genes to distinguish the status of HCC and non-tumor liver tissues. Our proposed survival tree model shows the genes related with clinical, pathological data and risk factors of HCC. These findings could be available to predict prognosis of HCC and give valuable information to justify the treatment strategy for clinician.
참고문헌 (6)
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- Tae Rim Lee, "A Study on the Tree Structured Model for early diagnosis of B-type Hepatitis", The Journal of Data Science and Classification, 1(2) (1997)
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- Qin, L.F., "Expression of p27Kip1 and p21WAF1", CIP1 in primary hepatocellularcarcinoma: Clinicopathologic cerrelation ans survival analysis, 2001, pp.32, 778~785
- T.R.Lee, "TheraputicEfficacy of Transcatheter Aterial Chemoembolization as copared with Hepatic Resection in Hepatocellular Carcinoma patients with compensated liverfunction in a Hepatitis B Virus-Endemic area", Journal of Clinical Oncology, 20(22) (2002)
- T.R.Lee, "Independent Prognostic Factors of 861 cases of oral squamous cell carcinoma in Korean adults", Oral Oncology, 42, pp.208~217 (2006)