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Sci Rep. 2018 Jul 11;8(1):10434. doi: 10.1038/s41598-018-28650-0.

A Data Mining-based Prognostic Algorithm for NAFLD-related Hepatoma Patients: A Nationwide Study by the Japan Study Group of NAFLD.

Author information

1
Department of Medicine, Kurume University School of Medicine, Kurume, Japan. takumi@med.kurume-u.ac.jp.
2
Department of Internal Medicine and Gastroenterology, Tokyo Women's Medical University, Tokyo, Japan.
3
Department of Gastroenterology and Hepatology, JA Hiroshima General Hospital, Hatsukaichi, Japan.
4
Department of Gastroenterology and Metabolism, Applied Life Science, Institute of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
5
Department of Hepatology, Sapporo Kosei General Hospital, Sapporo, Japan.
6
Department of Gastroenterology and Hepatology, Kochi Medical School, Nankoku, Japan.
7
Department of General Internal Medicine2, General Medical Center, Kawasaki Medical School, Okayama, Japan.
8
Division of Gastroenterology and Hematology/Oncology, Department of Medicine, Asahikawa Medical University, Asahikawa, Japan.
9
Department of Gastroenterology and Hepatology, Yokohama City University School of Medicine, Yokohama, Japan.
10
Department of Gastroenterology, Faculty of Medicine, Oita University, Yufu, Japan.
11
Internal Medicine, Saga University faculty of Medicine, Saga, Japan.
12
Center for Digestive and Liver Diseases, Nara City Hospital, Nara, Japan.
13
Department of Gastroenterology and Hepatology, Kyoto Prefectural University of Medicine, Kyoto, Japan.
14
Department of Gastroenterology, National Center for Global Health and Medicine, Tokyo, Japan.
15
Department of Gastroenterology and Hepatology, Osaka University, Graduate School of Medicine, Suita, Japan.
16
Department of Hepatology, Osaka City University, Graduate School of Medicine, Osaka, Japan.
17
Department of Gastroenterology and Hepatology, Osaka City Juso Hospital, Osaka, Japan.
18
Center for Comprehensive Community Medicine Faculty of Medicine, Saga University, Saga, Japan.
19
Division of Hepatology and Pancreatology, Department of Internal Medicine, Aichi Medical University, Nagakute, Japan.
20
Liver Center, Saga University Hospital, Saga, Japan.
21
Department of Gastroenterology, Nayoro City General Hospital, Nayoro, Japan.
22
Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, NSW, Australia.
23
Department of Medicine, Kurume University School of Medicine, Kurume, Japan.

Abstract

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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