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BMC Cancer

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01-12-2020 | Hepatocellular Carcinoma | Research article

A genomic-clinicopathologic nomogram for predicting overall survival of hepatocellular carcinoma

Authors: Kena Zhou, Qiang Zhou, Congbo Cai

Published in: BMC Cancer | Issue 1/2020

Abstract

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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Title: A genomic-clinicopathologic nomogram for predicting overall survival of hepatocellular carcinoma
Authors: Kena Zhou
Qiang Zhou
Congbo Cai
Publication date: 01-12-2020
Publisher: BioMed Central
Keywords: Hepatocellular Carcinoma
Hepatocellular Carcinoma
Published in: BMC Cancer / Issue 1/2020
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-020-07688-2

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Abstract

Background

Methods

Results

Conclusions

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