ArticleRadiation and environmental biophysics2012
Breast cancer risk in atomic bomb survivors from multi-model inference with incidence data 1958-1998.
Article in Radiation and environmental biophysics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 23 citations in OpenAlex.
- A cell-based model approach to radiation-induced breast cancer development.Frontiers in public health · 2026Article
- A mathematical model assuming frequency-dependent cost for analyzing the influence of cell competition on radiation effects.PloS one · 2025Article
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- Comparison and multi-model inference of excess risks models for radiation-related solid cancer.Radiation and environmental biophysics · 2023Article
- Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms.Radiation and environmental biophysics · 2023Article
- Mammary Chain Irradiation in Left-Sided Breast Cancer: Can We Reduce the Risk of Secondary Cancer and Ischaemic Heart Disease with Modern Intensity-Modulated Radiotherapy Techniques?Breast care (Basel, Switzerland) · 2021Article
- ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence.Radiation and environmental biophysics · 2020Article
- Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003.Radiation and environmental biophysics · 2018Article
- Correlations between Risk Factors for Breast Cancer and Genetic Instability in Cancer Patients-A Clinical Perspective Study.Frontiers in genetics · 2017Article
- Mechanistic study on lung cancer mortality after radon exposure in the Wismut cohort supports important role of clonal expansion in lung carcinogenesis.Radiation and environmental biophysics · 2016Article
- Article
- A method for determining weights for excess relative risk and excess absolute risk when applied in the calculation of lifetime risk of cancer from radiation exposure.Radiation and environmental biophysics · 2013Article
- Independent analysis of the radiation risk for leukaemia in children and adults with mortality data (1950-2003) of Japanese A-bomb survivors.Radiation and environmental biophysics · 2013Article
- Dose-responses from multi-model inference for the non-cancer disease mortality of atomic bomb survivors.Radiation and environmental biophysics · 2012Article
- Response to "model averaging in the analysis of leukaemia mortality among Japanese A-bomb survivors" by Richardson and Cole.Radiation and environmental biophysics · 2012Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer risk from radiation exposure has been analyzed in the cohort of Japanese a-bomb survivors using empirical models and mechanistic two-step clonal expansion (TSCE) models with incidence data from 1958 to 1998. TSCE models rely on a phenomenological representation of cell transition processes on the path to cancer. They describe the data as good as empirical models and this fact has been exploited for risk assessment. Adequate models of both types have been selected with a statistical protocol based on parsimonious parameter deployment and their risk estimates have been combined using multi-model inference techniques. TSCE models relate the radiation risk to cell processes which are controlled by age-increasing rates of initiating mutations and by changes in hormone levels due to menopause. For exposure at young age, they predict an enhanced excess relative risk (ERR) whereas the preferred empirical model shows no dependence on age at exposure. At attained age 70, the multi-model median of the ERR at 1 Gy decreases moderately from 1.2 Gy(-1) (90% CI 0.72; 2.1) for exposure at age 25 to a 30% lower value for exposure at age 55. For cohort strata with few cases, where model predictions diverge, uncertainty intervals from multi-model inference are enhanced by up to a factor of 1.6 compared to the preferred empirical model. Multi-model inference provides a joint risk estimate from several plausible models rather than relying on a single model of choice. It produces more reliable point estimates and improves the characterization of uncertainties. The method is recommended for risk assessment in practical radiation protection.
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