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  • 标题:A Data Mining-based Prognostic Algorithm for NAFLD-related Hepatoma Patients: A Nationwide Study by the Japan Study Group of NAFLD
  • 本地全文:下载
  • 作者:Takumi Kawaguchi ; Katsutoshi Tokushige ; Hideyuki Hyogo
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2018
  • 卷号:8
  • 期号:1
  • 页码:10434
  • DOI:10.1038/s41598-018-28650-0
  • 语种:English
  • 出版社:Springer Nature
  • 摘要:The prognosis of patients with nonalcoholic fatty liver disease-related hepatocellular carcinoma (NAFLD-HCC) is intricately associated with various factors. We aimed to investigate the prognostic algorithm of NAFLD-HCC patients using a data-mining analysis. A total of 247 NAFLD-HCC patients diagnosed from 2000 to 2014 were registered from 17 medical institutions in Japan. Of these, 136 patients remained alive (Alive group) and 111 patients had died at the censor time point (Deceased group). The random forest analysis demonstrated that treatment for HCC and the serum albumin level were the first and second distinguishing factors between the Alive and Deceased groups. A decision-tree algorithm revealed that the best profile comprised treatment with hepatectomy or radiofrequency ablation and a serum albumin level ≥3.7 g/dL (Group 1). The second-best profile comprised treatment with hepatectomy or radiofrequency ablation and serum albumin levels <3.7 g/dL (Group 2). The 5-year overall survival rate was significantly higher in the Group 1 than in the Group 2. Thus, we demonstrated that curative treatment for HCC and serum albumin level >3.7 g/dL was the best prognostic profile for NAFLD-HCC patients. This novel prognostic algorithm for patients with NAFLD-HCC could be used for clinical management.
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