Prediction Model with <i>HLA-A*33:03</i> Reveals Number of Days to Develop Liver Cancer from Blood Test
The development of liver cancer in patients with hepatitis B is a major problem, and several models have been reported to predict the development of liver cancer. However, no predictive model involving human genetic factors has been reported to date. For the items incorporated in the prediction mode...
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MDPI AG
2023-03-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/24/5/4761 |
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| author | Nao Nishida Jun Ohashi Goki Suda Takehiro Chiyoda Nobuharu Tamaki Takahiro Tomiyama Sachiko Ogasawara Masaya Sugiyama Yosuke Kawai Seik-Soon Khor Masao Nagasaki Akihiro Fujimoto Takayo Tsuchiura Miyuki Ishikawa Koichi Matsuda Hirohisa Yano Tomoharu Yoshizumi Namiki Izumi Kiyoshi Hasegawa Naoya Sakamoto Masashi Mizokami Katsushi Tokunaga |
| author_facet | Nao Nishida Jun Ohashi Goki Suda Takehiro Chiyoda Nobuharu Tamaki Takahiro Tomiyama Sachiko Ogasawara Masaya Sugiyama Yosuke Kawai Seik-Soon Khor Masao Nagasaki Akihiro Fujimoto Takayo Tsuchiura Miyuki Ishikawa Koichi Matsuda Hirohisa Yano Tomoharu Yoshizumi Namiki Izumi Kiyoshi Hasegawa Naoya Sakamoto Masashi Mizokami Katsushi Tokunaga |
| author_sort | Nao Nishida |
| collection | DOAJ |
| description | The development of liver cancer in patients with hepatitis B is a major problem, and several models have been reported to predict the development of liver cancer. However, no predictive model involving human genetic factors has been reported to date. For the items incorporated in the prediction model reported so far, we selected items that were significant in predicting liver carcinogenesis in Japanese patients with hepatitis B and constructed a prediction model of liver carcinogenesis by the Cox proportional hazard model with the addition of <i>Human Leukocyte Antigen</i> (<i>HLA</i>) genotypes. The model, which included four items—sex, age at the time of examination, alpha-fetoprotein level (log<sub>10</sub>AFP) and presence or absence of <i>HLA-A*33:03</i>—revealed an area under the receiver operating characteristic curve (AUROC) of 0.862 for HCC prediction within 1 year and an AUROC of 0.863 within 3 years. A 1000 repeated validation test resulted in a C-index of 0.75 or higher, or sensitivity of 0.70 or higher, indicating that this predictive model can distinguish those at high risk of developing liver cancer within a few years with high accuracy. The prediction model constructed in this study, which can distinguish between chronic hepatitis B patients who develop hepatocellular carcinoma (HCC) early and those who develop HCC late or not, is clinically meaningful. |
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| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-11T07:22:21Z |
| publishDate | 2023-03-01 |
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| spelling | doaj.art-2ef071f4f95b4c1aaaf7374f5a3d1ba72023-11-17T07:53:02ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-03-01245476110.3390/ijms24054761Prediction Model with <i>HLA-A*33:03</i> Reveals Number of Days to Develop Liver Cancer from Blood TestNao Nishida0Jun Ohashi1Goki Suda2Takehiro Chiyoda3Nobuharu Tamaki4Takahiro Tomiyama5Sachiko Ogasawara6Masaya Sugiyama7Yosuke Kawai8Seik-Soon Khor9Masao Nagasaki10Akihiro Fujimoto11Takayo Tsuchiura12Miyuki Ishikawa13Koichi Matsuda14Hirohisa Yano15Tomoharu Yoshizumi16Namiki Izumi17Kiyoshi Hasegawa18Naoya Sakamoto19Masashi Mizokami20Katsushi Tokunaga21Genome Medical Science Project, National Center for Global Health and Medicine, Ichikawa 272-8516, JapanDepartment of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, JapanDepartment of Gastroenterology and Hepatology, Graduate School of Medicine, Hokkaido University, North 15, West 7, Kita-ku, Sapporo 060-8638, JapanHepato-Biliary-Pancreatic Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, JapanDepartment of Gastroenterology and Hepatology, Musashino Red Cross Hospital, Musashino 180-8610, JapanDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, JapanDepartment of Pathology, Kurume University School of Medicine, Kurume 830-0011, JapanDepartment of Viral Pathogenesis and Controls, National Center for Global Health and Medicine, Ichikawa 272-8516, JapanGenome Medical Science Project-Toyama, National Center for Global Health and Medicine, Tokyo 162-8655, JapanGenome Medical Science Project-Toyama, National Center for Global Health and Medicine, Tokyo 162-8655, JapanHuman Biosciences Unit for the Top Global Course Center for the Promotion of Interdisciplinary Education and Research, Kyoto University, Kyoto 606-8507, JapanDepartment of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0003, JapanGenome Medical Science Project, National Center for Global Health and Medicine, Ichikawa 272-8516, JapanGenome Medical Science Project, National Center for Global Health and Medicine, Ichikawa 272-8516, JapanLaboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, JapanDepartment of Pathology, Kurume University School of Medicine, Kurume 830-0011, JapanDepartment of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, JapanDepartment of Gastroenterology and Hepatology, Musashino Red Cross Hospital, Musashino 180-8610, JapanHepato-Biliary-Pancreatic Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, JapanDepartment of Gastroenterology and Hepatology, Graduate School of Medicine, Hokkaido University, North 15, West 7, Kita-ku, Sapporo 060-8638, JapanGenome Medical Science Project, National Center for Global Health and Medicine, Ichikawa 272-8516, JapanGenome Medical Science Project-Toyama, National Center for Global Health and Medicine, Tokyo 162-8655, JapanThe development of liver cancer in patients with hepatitis B is a major problem, and several models have been reported to predict the development of liver cancer. However, no predictive model involving human genetic factors has been reported to date. For the items incorporated in the prediction model reported so far, we selected items that were significant in predicting liver carcinogenesis in Japanese patients with hepatitis B and constructed a prediction model of liver carcinogenesis by the Cox proportional hazard model with the addition of <i>Human Leukocyte Antigen</i> (<i>HLA</i>) genotypes. The model, which included four items—sex, age at the time of examination, alpha-fetoprotein level (log<sub>10</sub>AFP) and presence or absence of <i>HLA-A*33:03</i>—revealed an area under the receiver operating characteristic curve (AUROC) of 0.862 for HCC prediction within 1 year and an AUROC of 0.863 within 3 years. A 1000 repeated validation test resulted in a C-index of 0.75 or higher, or sensitivity of 0.70 or higher, indicating that this predictive model can distinguish those at high risk of developing liver cancer within a few years with high accuracy. The prediction model constructed in this study, which can distinguish between chronic hepatitis B patients who develop hepatocellular carcinoma (HCC) early and those who develop HCC late or not, is clinically meaningful.https://www.mdpi.com/1422-0067/24/5/4761hepatitis B virushepatocellular carcinomahuman leukocyte antigenpredictioncox proportional-hazards regression model |
| spellingShingle | Nao Nishida Jun Ohashi Goki Suda Takehiro Chiyoda Nobuharu Tamaki Takahiro Tomiyama Sachiko Ogasawara Masaya Sugiyama Yosuke Kawai Seik-Soon Khor Masao Nagasaki Akihiro Fujimoto Takayo Tsuchiura Miyuki Ishikawa Koichi Matsuda Hirohisa Yano Tomoharu Yoshizumi Namiki Izumi Kiyoshi Hasegawa Naoya Sakamoto Masashi Mizokami Katsushi Tokunaga Prediction Model with <i>HLA-A*33:03</i> Reveals Number of Days to Develop Liver Cancer from Blood Test International Journal of Molecular Sciences hepatitis B virus hepatocellular carcinoma human leukocyte antigen prediction cox proportional-hazards regression model |
| title | Prediction Model with <i>HLA-A*33:03</i> Reveals Number of Days to Develop Liver Cancer from Blood Test |
| title_full | Prediction Model with <i>HLA-A*33:03</i> Reveals Number of Days to Develop Liver Cancer from Blood Test |
| title_fullStr | Prediction Model with <i>HLA-A*33:03</i> Reveals Number of Days to Develop Liver Cancer from Blood Test |
| title_full_unstemmed | Prediction Model with <i>HLA-A*33:03</i> Reveals Number of Days to Develop Liver Cancer from Blood Test |
| title_short | Prediction Model with <i>HLA-A*33:03</i> Reveals Number of Days to Develop Liver Cancer from Blood Test |
| title_sort | prediction model with i hla a 33 03 i reveals number of days to develop liver cancer from blood test |
| topic | hepatitis B virus hepatocellular carcinoma human leukocyte antigen prediction cox proportional-hazards regression model |
| url | https://www.mdpi.com/1422-0067/24/5/4761 |
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