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

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.

Noninvasively predict the micro-vascular invasion and histopathological grade of hepatocellular carcinoma with CT-derived radiomics

“…The above results were consistent with many previous researches [43][44][45]. Besides, our results also demonstrated that age and gender were also associated with the histopathologic grade and MVI of HCC, which corresponded to some previous findings that the age and gender also served as independent risk factors and then were incorporated into the nomogram-based predictors [46][47][48]. Importantly, this study suggested that the integration of clinical indicators and radiomics resulted in fascinating diagnostic power for assessing the tumor grade and MVI (AUC > 0.900).…”

A multi‐omics‐based investigation of the immunological and prognostic impact of necroptosis‐related genes in patients with hepatocellular carcinoma

“…We collected literature on hepatocellular carcinoma, 18 , 19 , 20 extracted the genes they used to construct predictive models and performed survival curve and ROC curve analysis to compare the predictive power of our constructed models.…”

OHCCPredictor: an online risk stratification model for predicting survival duration of older patients with hepatocellular carcinoma

“…Nomogram is considered a widely used predictive model for evaluating the prognosis of cancer patients [12][13][14]. In this study, we aim to identify the prognostic factors of elderly patients with HCC and construct a new prognostic model for predicting their OS, which would facilitate the provision of therapy suggestions and assist clinical decision-making.…”