{"title":"基于数据挖掘方法的肝细胞癌碳离子放疗后预后风险分类新方法。","authors":"Kazuhiko Hayashi, Osamu Suzuki, Koji Ichise, Hirofumi Uchida, Makoto Anzai, Azusa Hasegawa, Shinichi Shimizu, Teruki Teshima, Jiro Fujimoto, Kazuhiko Ogawa","doi":"10.1111/cas.70079","DOIUrl":null,"url":null,"abstract":"<p><p>No classification methods to predict prognosis after carbon-ion radiotherapy for hepatocellular carcinoma have yet been reported. This study aimed to develop risk classification for cancer-specific survival (CSS) after carbon-ion radiotherapy for hepatocellular carcinoma using decision tree analysis as a data-mining method. In this single-center, retrospective study, we analyzed 90 consecutive patients with hepatocellular carcinoma treated with carbon-ion radiotherapy between 2018 and 2022. Liver tumors were irradiated at 60 Gy (relative biological effectiveness [RBE]) in four fractions. If the tumor was close to the gastrointestinal tract, it was irradiated at 60 Gy [RBE] in 12 fractions. Univariate and multivariate analyses of progression-free survival (PFS) and CSS were performed to assess patients' background and treatment-related factors. Decision tree analysis (DTA) was performed to assess prognostic factors for CSS that were significantly different in the multivariate analysis. The median follow-up period was 32.8 months for all patients and 35.6 months for survivors. Multivariate analysis identified dose fractionation and pretreatment alpha-fetoprotein values as significant prognostic factors for PFS and CSS. Moreover, clinical stage and pretreatment protein induced by vitamin K absence or antagonist ΙΙ values were significant prognostic factors for CSS. DTA revealed that the patients could be divided into three groups according to prognosis: low-risk, high-risk, and intermediate-risk. Consequently, the 3-year CSS rates for the low-, intermediate-, and high-risk groups were 100%, 73.3%, and 44.4%, respectively. DTA represents a new method for risk classification for CSS after carbon-ion radiotherapy for hepatocellular carcinoma based on tumor markers and clinical stage.</p>","PeriodicalId":48943,"journal":{"name":"Cancer Science","volume":" ","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Method for Prognostic Risk Classification After Carbon-Ion Radiotherapy for Hepatocellular Carcinoma Using Data-Mining Methods.\",\"authors\":\"Kazuhiko Hayashi, Osamu Suzuki, Koji Ichise, Hirofumi Uchida, Makoto Anzai, Azusa Hasegawa, Shinichi Shimizu, Teruki Teshima, Jiro Fujimoto, Kazuhiko Ogawa\",\"doi\":\"10.1111/cas.70079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>No classification methods to predict prognosis after carbon-ion radiotherapy for hepatocellular carcinoma have yet been reported. This study aimed to develop risk classification for cancer-specific survival (CSS) after carbon-ion radiotherapy for hepatocellular carcinoma using decision tree analysis as a data-mining method. In this single-center, retrospective study, we analyzed 90 consecutive patients with hepatocellular carcinoma treated with carbon-ion radiotherapy between 2018 and 2022. Liver tumors were irradiated at 60 Gy (relative biological effectiveness [RBE]) in four fractions. If the tumor was close to the gastrointestinal tract, it was irradiated at 60 Gy [RBE] in 12 fractions. Univariate and multivariate analyses of progression-free survival (PFS) and CSS were performed to assess patients' background and treatment-related factors. Decision tree analysis (DTA) was performed to assess prognostic factors for CSS that were significantly different in the multivariate analysis. The median follow-up period was 32.8 months for all patients and 35.6 months for survivors. Multivariate analysis identified dose fractionation and pretreatment alpha-fetoprotein values as significant prognostic factors for PFS and CSS. Moreover, clinical stage and pretreatment protein induced by vitamin K absence or antagonist ΙΙ values were significant prognostic factors for CSS. DTA revealed that the patients could be divided into three groups according to prognosis: low-risk, high-risk, and intermediate-risk. Consequently, the 3-year CSS rates for the low-, intermediate-, and high-risk groups were 100%, 73.3%, and 44.4%, respectively. DTA represents a new method for risk classification for CSS after carbon-ion radiotherapy for hepatocellular carcinoma based on tumor markers and clinical stage.</p>\",\"PeriodicalId\":48943,\"journal\":{\"name\":\"Cancer Science\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Science\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/cas.70079\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/cas.70079","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
A Novel Method for Prognostic Risk Classification After Carbon-Ion Radiotherapy for Hepatocellular Carcinoma Using Data-Mining Methods.
No classification methods to predict prognosis after carbon-ion radiotherapy for hepatocellular carcinoma have yet been reported. This study aimed to develop risk classification for cancer-specific survival (CSS) after carbon-ion radiotherapy for hepatocellular carcinoma using decision tree analysis as a data-mining method. In this single-center, retrospective study, we analyzed 90 consecutive patients with hepatocellular carcinoma treated with carbon-ion radiotherapy between 2018 and 2022. Liver tumors were irradiated at 60 Gy (relative biological effectiveness [RBE]) in four fractions. If the tumor was close to the gastrointestinal tract, it was irradiated at 60 Gy [RBE] in 12 fractions. Univariate and multivariate analyses of progression-free survival (PFS) and CSS were performed to assess patients' background and treatment-related factors. Decision tree analysis (DTA) was performed to assess prognostic factors for CSS that were significantly different in the multivariate analysis. The median follow-up period was 32.8 months for all patients and 35.6 months for survivors. Multivariate analysis identified dose fractionation and pretreatment alpha-fetoprotein values as significant prognostic factors for PFS and CSS. Moreover, clinical stage and pretreatment protein induced by vitamin K absence or antagonist ΙΙ values were significant prognostic factors for CSS. DTA revealed that the patients could be divided into three groups according to prognosis: low-risk, high-risk, and intermediate-risk. Consequently, the 3-year CSS rates for the low-, intermediate-, and high-risk groups were 100%, 73.3%, and 44.4%, respectively. DTA represents a new method for risk classification for CSS after carbon-ion radiotherapy for hepatocellular carcinoma based on tumor markers and clinical stage.
期刊介绍:
Cancer Science (formerly Japanese Journal of Cancer Research) is a monthly publication of the Japanese Cancer Association. First published in 1907, the Journal continues to publish original articles, editorials, and letters to the editor, describing original research in the fields of basic, translational and clinical cancer research. The Journal also accepts reports and case reports.
Cancer Science aims to present highly significant and timely findings that have a significant clinical impact on oncologists or that may alter the disease concept of a tumor. The Journal will not publish case reports that describe a rare tumor or condition without new findings to be added to previous reports; combination of different tumors without new suggestive findings for oncological research; remarkable effect of already known treatments without suggestive data to explain the exceptional result. Review articles may also be published.