{"title":"随机阈值模型:考虑个人癌症易感性的低剂量辐射诱发风险评估方法。","authors":"Takashi Yanagawa, Hisanori Fukunaga","doi":"10.1177/15593258241298553","DOIUrl":null,"url":null,"abstract":"<p><p><b>Objectives:</b> The linear no-threshold (LNT) model, which has been used for radiation protection purposes, was developed based on the assumption that exposure to even a small amount of radiation may cause cancer. However, although it is known in carcinogenesis that there is variation in radiation sensitivity among individuals, the LNT model does not adequately consider radiosensitive subgroups. In this paper, we represent susceptibility to contract cancer by radiation exposure by means of the threshold of a dose-response function, introduce an assumption that the thresholds are random to represent the variation of the radiosensitivity among individuals in a susceptible subgroup. We propose a novel method, the random threshold (RT) model, for determining the safe dose limit for the subgroup to protect cancer-susceptible individuals from radiation exposure. <b>Conclusion:</b> The proposed method is illustrated by targeting <i>ATM</i> gene (a cancer-susceptible gene) mutation carriers as a radiosensitive subgroup. For cancer risk associated with low-dose radiation exposure, the contribution of radiosensitivity cannot be ignored, thus the RT model would be more suitable for risk protection for radiosensitive subgroups instead of the LNT model. We also notice that it could be widely applicable for risk protection of not only low-dose radiation but also environmental pollutants.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11533321/pdf/","citationCount":"0","resultStr":"{\"title\":\"Random Threshold Model: A Low-Dose Radiation-Induced Risk Assessment Approach Considering Individual Susceptibility to Cancer.\",\"authors\":\"Takashi Yanagawa, Hisanori Fukunaga\",\"doi\":\"10.1177/15593258241298553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Objectives:</b> The linear no-threshold (LNT) model, which has been used for radiation protection purposes, was developed based on the assumption that exposure to even a small amount of radiation may cause cancer. However, although it is known in carcinogenesis that there is variation in radiation sensitivity among individuals, the LNT model does not adequately consider radiosensitive subgroups. In this paper, we represent susceptibility to contract cancer by radiation exposure by means of the threshold of a dose-response function, introduce an assumption that the thresholds are random to represent the variation of the radiosensitivity among individuals in a susceptible subgroup. We propose a novel method, the random threshold (RT) model, for determining the safe dose limit for the subgroup to protect cancer-susceptible individuals from radiation exposure. <b>Conclusion:</b> The proposed method is illustrated by targeting <i>ATM</i> gene (a cancer-susceptible gene) mutation carriers as a radiosensitive subgroup. For cancer risk associated with low-dose radiation exposure, the contribution of radiosensitivity cannot be ignored, thus the RT model would be more suitable for risk protection for radiosensitive subgroups instead of the LNT model. We also notice that it could be widely applicable for risk protection of not only low-dose radiation but also environmental pollutants.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11533321/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/15593258241298553\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/15593258241298553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Random Threshold Model: A Low-Dose Radiation-Induced Risk Assessment Approach Considering Individual Susceptibility to Cancer.
Objectives: The linear no-threshold (LNT) model, which has been used for radiation protection purposes, was developed based on the assumption that exposure to even a small amount of radiation may cause cancer. However, although it is known in carcinogenesis that there is variation in radiation sensitivity among individuals, the LNT model does not adequately consider radiosensitive subgroups. In this paper, we represent susceptibility to contract cancer by radiation exposure by means of the threshold of a dose-response function, introduce an assumption that the thresholds are random to represent the variation of the radiosensitivity among individuals in a susceptible subgroup. We propose a novel method, the random threshold (RT) model, for determining the safe dose limit for the subgroup to protect cancer-susceptible individuals from radiation exposure. Conclusion: The proposed method is illustrated by targeting ATM gene (a cancer-susceptible gene) mutation carriers as a radiosensitive subgroup. For cancer risk associated with low-dose radiation exposure, the contribution of radiosensitivity cannot be ignored, thus the RT model would be more suitable for risk protection for radiosensitive subgroups instead of the LNT model. We also notice that it could be widely applicable for risk protection of not only low-dose radiation but also environmental pollutants.