Dataset Information

Development and validation of a prognostic model for patients with hepatocellular carcinoma undergoing radiofrequency ablation.

ABSTRACT: BACKGROUND:There are large variations in prognosis among hepatocellular carcinoma (HCC) patients undergoing radiofrequency ablation (RFA). However, current staging or scoring systems hardly discriminate the outcome of HCC patients treated with RFA. METHODS:A total of 757 treatment-naïve HCC patients undergoing RFA (derivation cohort) were analyzed to establish a nomogram for disease-free survival (DFS) based on Cox proportional hazard regression model. Accuracy of the nomogram was assessed and compared with conventional staging or scoring systems. Furthermore, external validation was performed in an independent cohort including 208 patients (validation cohort). RESULTS:Tumor size, tumor number, alpha-fetoprotein, prothrombin induced by vitamin K absence-II, lymphocyte count, albumin, and presence of ascites were adopted to construct the prognostic nomogram from the derivation cohort. Calibration curves to predict probability of DFS at 3 and 5 years after RFA showed good agreements between the nomogram and actual observations. The concordance index of the present nomogram was 0.759 (95% confidence interval 0.728-0.790), which was superior to those of conventional staging or scoring systems (range 0.505-0.683, all P < .001). These results were also reproduced in the validation cohort. CONCLUSION:Our simple-to-use nomogram optimized for treatment-naïve HCC patients undergoing RFA provided better prognostic performance than conventional staging or scoring systems.

SUBMITTER: Kim CG

PROVIDER: S-EPMC6718586 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and validation of a prognostic model for patients with hepatocellular carcinoma undergoing radiofrequency ablation.

Kim Chang Gon CG Lee Hyun Woong HW Choi Hye Jin HJ Lee Jung Il JI Lee Hye Won HW Kim Seung Up SU Park Jun Yong JY Kim Do Young DY Ahn Sang Hoon SH Han Kwang-Hyub KH Kim Han Sang HS Kim Kyung Hwan KH Choi Seong Jin SJ Kim Yongun Y Lee Kwan Sik KS Kim Gyoung Min GM Kim Man Deuk MD Won Jong Yoon JY Lee Do Yun DY Kim Beom Kyung BK

Cancer medicine 20190710 11

<h4>Background</h4>There are large variations in prognosis among hepatocellular carcinoma (HCC) patients undergoing radiofrequency ablation (RFA). However, current staging or scoring systems hardly discriminate the outcome of HCC patients treated with RFA.<h4>Methods</h4>A total of 757 treatment-naïve HCC patients undergoing RFA (derivation cohort) were analyzed to establish a nomogram for disease-free survival (DFS) based on Cox proportional hazard regression model. Accuracy of the nomogram was ...[more]

PMID: 31290618

Similar Datasets

Project description:BACKGROUND:CpG island methylator phenotype (CIMP), a common biological phenomenon characterized by a subset of concurrently methylated genes, can have an influence on the progression of multiple cancers. However, the potential mechanism of CIMP in hepatocarcinogenesis and its clinical relevance remains only partially understood. METHODS:We used a methylation array from the cancer genome atlas (TCGA) to stratify HCC patients into different CIMP subtypes, and evaluated their correlation with clinical characteristics. In addition, mutation, CNV, and transcriptome profiles were also utilized to evaluate the distinctive genomic patterns correlated with CIMP. Finally, a CIMP-associated prognostic model (CPM) was trained and validated using four independent datasets. FINDINGS:A subgroup of patients was identified as having CIMP-H, which was associated with worse OS and DFS. Gene enrichment analysis indicated that the terms "liver cancer with EPCAM up", "tumor invasiveness up", "methyltransferase complex", and "translational initiation" were enriched in CIMP-H subgroup. Notably, somatic mutation analysis indicated that CIMP-H patients presented with a higher mutation burden of BRD4, DDIAS and NOX1. Moreover, four CPM associated genes could significantly categorize patients into low- and high-risk groups in the training dataset and another 3 independent validation datasets. Finally, a nomogram incorporating a classifier based on four mRNAs, pathological M stage and CIMP status was established, which showed a favorable discriminating ability and might contribute to clinical decision-making for HCC. INTERPRETATION:Our work highlights the potential clinical application value of CPM in predicting the overall survival of HCC patients and the mechanisms underlying the role of CIMP in hepatocarcinogenesis. FUND: This work was supported by the State Key Project on Infectious Diseases of China (2018ZX10723204-003), the National Nature Science Foundation of China (Nos. 81874065, 81500565, 81874149, 81572427, and 81401997), the Hepato-Biliary-Pancreatic Malignant Tumor Investigation Fund of Chen Xiao-ping Foundation for the Development of Science and Technology of Hubei Province (CXPJJH11800001-2018356).

Dataset Information

Development and validation of a prognostic model for patients with hepatocellular carcinoma undergoing radiofrequency ablation.

Publications

Development and validation of a prognostic model for patients with hepatocellular carcinoma undergoing radiofrequency ablation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets