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肝细胞癌风险或预后相关列线图的建立与临床应用:综述

Establishment and Clinical Application of the Nomogram Related to Risk or Prognosis of Hepatocellular Carcinoma: A Review.

作者信息

Wang Xiangze, Zhao Minghui, Zhang Chensheng, Chen Haobo, Liu Xingyu, An Yang, Zhang Lu, Guo Xiangqian

机构信息

Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, 475004, People's Republic of China.

School of Computer and Information Engineering, Henan University, Kaifeng, 475004, People's Republic of China.

出版信息

J Hepatocell Carcinoma. 2023 Aug 22;10:1389-1398. doi: 10.2147/JHC.S417123. eCollection 2023.

Abstract

Hepatocellular carcinoma (HCC) is the most prevalent primary liver malignancy, accounting for approximately 90% of all primary liver cancers, with high mortality and a poor prognosis. A large number of predictive models have been applied that integrate multiple clinical factors and biomarkers to predict the prognosis of HCC. Nomograms, as easy-to-use prognostic predictive models, are widely used to predict the probability of clinical outcomes. We searched PubMed with the keywords "hepatocellular carcinoma" and "nomogram", and 974 relative literatures were retrieved. According to the construction methodology and the real validity of the nomograms, in this study, 97 nomograms for HCC were selected in 77 publications. These 97 nomograms were established based on more than 100,000 patients, covering seven main prognostic outcomes. The research data of 56 articles are from hospital-based HCC patients, and 13 articles provided external validation results of the nomogram. In addition to AFP, tumor size, tumor number, stage, vascular invasion, age, and other common prognostic risk factors are included in the HCC-related nomogram, more and more biomarkers, including gene mRNA expression, gene polymorphisms, and gene signature, etc. were also included in the nomograms. The establishment, assessment and validation of these nomograms are also discussed in depth. This study would help clinicians construct and select appropriate nomograms to guide precise judgment and appropriate treatments.

摘要

肝细胞癌(HCC)是最常见的原发性肝脏恶性肿瘤,约占所有原发性肝癌的90%,死亡率高且预后较差。已经应用了大量整合多种临床因素和生物标志物的预测模型来预测HCC的预后。列线图作为易于使用的预后预测模型,被广泛用于预测临床结局的概率。我们在PubMed上以“肝细胞癌”和“列线图”为关键词进行搜索,检索到974篇相关文献。根据列线图的构建方法和实际有效性,本研究从77篇出版物中筛选出97个HCC列线图。这些97个列线图基于超过10万名患者建立,涵盖七个主要预后结局。56篇文章的研究数据来自医院的HCC患者,13篇文章提供了列线图的外部验证结果。除了甲胎蛋白、肿瘤大小、肿瘤数量、分期、血管侵犯、年龄等常见的预后危险因素被纳入HCC相关列线图外,越来越多的生物标志物,包括基因mRNA表达、基因多态性和基因特征等也被纳入列线图中。同时,还深入讨论了这些列线图的建立、评估和验证。本研究将有助于临床医生构建和选择合适的列线图,以指导精准判断和恰当治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1300/10460189/03130b671157/JHC-10-1389-g0001.jpg

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