A genomic-clinicopathologic nomogram for predicting overall survival of hepatocellular carcinoma.
BMC Cancer
; 20(1): 1176, 2020 Dec 01.
Article
em En
| MEDLINE
| ID: mdl-33261584
BACKGROUND: Hepatocellular carcinoma (HCC) is a common digestive tumor with great heterogeneity and different overall survival (OS) time, causing stern problems for selecting optimal treatment. Here we aim to establish a nomogram to predict the OS in HCC patients. METHODS: International Cancer Genome Consortium (ICGC) database was searched for the target information in our study. Lasso regression, univariate and multivariate cox analysis were applied during the analysis process. And a nomogram integrating model scoring and clinical characteristic was drawn. RESULTS: Six mRNAs were screened out by Lasso regression to make a model for predicting the OS of HCC patients. And this model was proved to be an independent prognostic model predicting OS in HCC patients. The area under the ROC curve (AUC) of this model was 0.803. TCGA database validated the significant value of this 6-mRNA model. Eventually a nomogram including 6-mRNA risk score, gender, age, tumor stage and prior malignancy was set up to predict the OS in HCC patients. CONCLUSIONS: We established an independent prognostic model of predicting OS for 1-3 years in HCC patients, which is available to all populations. And we developed a nomogram on the basis of this model, which could be of great help to precisely individual treatment measures.
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Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Carcinoma Hepatocelular
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Genômica
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Nomogramas
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Neoplasias Hepáticas
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Limite:
Aged
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Female
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Humans
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Male
Idioma:
En
Revista:
BMC Cancer
Assunto da revista:
NEOPLASIAS
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
China