Literature DB >> 29165812

A novel and validated prognostic nomogram based on liver fibrosis and tumor burden for patients with hepatocellular carcinoma after curative resection.

Jin-Long Huang1, Yi-Peng Fu1, Chu-Yu Jing1, Yong Yi1, Jian Sun1, Wei Gan1, Zhu-Feng Lu1, Jian Zhou1, Jia Fan1, Shuang-Jian Qiu1,2.   

Abstract

BACKGROUND AND OBJECTIVES: Most conventional staging systems were formulated concerning the tumor burden rather than the severity of liver fibrosis, which plays a central role in tumor promotion. The aim of this study was to formulate a prognostic nomogram comprehensively considering these two aspects for HCC after hepatectomy.
METHODS: The prognostic significances of the four indicators namely laminin, hyaluronic acid, human procollagen type-III, and collagen type-IV that reflect liver fibrosis were explored in two independent cohorts. A nomogram was established based on the results of multivariate analysis. The predictive accuracy of the nomogram was measured by concordance index (C-index) and calibration. The decision curve analysis (DCA) was used to evaluate the clinical benefit of the nomogram.
RESULTS: Preoperative serum laminin level is an independent prognostic factor for overall survival in HCC patients after resection. The C-indices of the nomogram in the training and validation cohorts were 0.779 and 0.719, respectively. The calibration showed optimal agreement between the prediction by nomogram and actual observation. Moreover, the C-indices and DCA revealed that the nomogram provided better clinical benefit compared with the BCLC stage, CLIP score, and AJCC 7th edition.
CONCLUSIONS: The prognostic nomogram constructed on laminin represents a superior predictive model.
© 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  hepatocellular carcinoma; laminin; liver fibrosis; nomogram; prognostic factors

Mesh:

Substances:

Year:  2017        PMID: 29165812     DOI: 10.1002/jso.24895

Source DB:  PubMed          Journal:  J Surg Oncol        ISSN: 0022-4790            Impact factor:   3.454


  8 in total

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Journal:  J Hepatocell Carcinoma       Date:  2020-10-27

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Journal:  Zhejiang Da Xue Xue Bao Yi Xue Ban       Date:  2020-05-25

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Journal:  Ann Transl Med       Date:  2020-11

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7.  A scoring model combining serum alpha-fetoprotein and tumor size and number predicts prognosis in hepatitis B virus-related hepatocellular carcinoma patients after curative hepatectomy.

Authors:  Bai Wei; Jing-San Chen; Sheng-Li Yang; George G Chen; Hao He
Journal:  Transl Cancer Res       Date:  2019-08       Impact factor: 1.241

8.  A novel machine learning algorithm to predict disease free survival after resection of hepatocellular carcinoma.

Authors:  Markus Bo Schoenberg; Julian Nikolaus Bucher; Dominik Koch; Nikolaus Börner; Sebastian Hesse; Enrico Narciso De Toni; Max Seidensticker; Martin Kurt Angele; Christoph Klein; Alexandr V Bazhin; Jens Werner; Markus Otto Guba
Journal:  Ann Transl Med       Date:  2020-04
  8 in total

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