ArticleRadiation and environmental biophysics2020
ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence.
Article in Radiation and environmental biophysics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Fit for purpose: German contributions to the new ICRP recommendations.Radiation and environmental biophysics · 2026Review
- Minimum latency effects for cancer associated with exposures to radiation or other carcinogens.British journal of cancer · 2024Article
- Time-integrated radiation risk metrics and interpopulation variability of survival.Zeitschrift fur medizinische Physik · 2024Article
- Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms.Radiation and environmental biophysics · 2023Article
- A bespoke health risk assessment methodology for the radiation protection of astronauts.Radiation and environmental biophysics · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
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Abstract
ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.
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