Cancer is a stochastic effect of radiation, meaning that it only has a probability of occurrence, as opposed to deterministic effects which always happen over a certain dose threshold. The consensus of the nuclear industry, nuclear regulators, and governments, is that the incidence of cancers due to ionizing radiation can be modeled as increasing linearly with effective radiation dose at a rate of 5.5% per sievert. Individual studies, alternate models, and earlier versions of the industry consensus have produced other risk estimates scattered around this consensus model. There is general agreement that the risk is much higher for infants and fetuses than adults, higher for the middle-aged than for seniors, and higher for women than for men, though there is no quantitative consensus about this. This model is widely accepted for external radiation, but its application to internal contamination is disputed. For example, the model fails to account for the low rates of cancer in early workers at Los Alamos National Laboratory who were exposed to plutonium dust, and the high rates of thyroid cancer in children following the Chernobyl accident, both of which were internal exposure events. Chris Busby of the self styled "European Committee on Radiation Risk", calls the ICRP model "fatally flawed" when it comes to internal exposure. Radiation can cause cancer in most parts of the body, in all animals, and at any age, although radiation-induced solid tumors usually take 10–15 years, and can take up to 40 years, to become clinically manifest, and radiation-induced leukemias typically require 2–9 years to appear. Some people, such as those with nevoid basal cell carcinoma syndrome or retinoblastoma, are more susceptible than average to developing cancer from radiation exposure. Children and adolescents are twice as likely to develop radiation-induced leukemia as adults; radiation exposure before birth has ten times the effect. Radiation exposure can cause cancer in any living tissue, but high-dose whole-body external exposure is most closely associated with leukemia, reflecting the high radiosensitivity of bone marrow. Internal exposures tend to cause cancer in the organs where the radioactive material concentrates, so that radon predominantly causes lung cancer, iodine-131 for thyroid cancer is most likely to cause leukemia. Data sources Increased Risk of Solid Cancer with Dose for atomic blast survivors The associations between ionizing radiation exposure and the development of cancer are based primarily on the "LSS cohort" of Japanese atomic bomb survivors, the largest human population ever exposed to high levels of ionizing radiation. However this cohort was also exposed to high heat, both from the initial nuclear flash of infrared light and following the blast due their exposure to the firestorm and general fires that developed in both cities respectively, so the survivors also underwent Hyperthermia therapy to various degrees. Hyperthermia, or heat exposure following irradiation is well known in the field of radiation therapy to markedly increase the severity of free-radical insults to cells following irradiation. Presently however no attempts have been made to cater for this confounding factor, it is not included or corrected for in the dose-response curves for this group. Additional data has been collected from recipients of selected medical procedures and the 1986 Chernobyl disaster. There is a clear link (see the UNSCEAR 2000 Report, Volume 2: Effects) between the Chernobyl accident and the unusually large number, approximately 1,800, of thyroid cancers reported in contaminated areas, mostly in children. For low levels of radiation, the biological effects are so small they may not be detected in epidemiological studies. Although radiation may cause cancer at high doses and high dose rates, public health data regarding lower levels of exposure, below about 10 mSv (1,000 mrem), are harder to interpret. To assess the health impacts of lower radiation doses, researchers rely on models of the process by which radiation causes cancer; several models that predict differing levels of risk have emerged. Studies of occupational workers exposed to chronic low levels of radiation, above normal background, have provided mixed evidence regarding cancer and transgenerational effects. Cancer results, although uncertain, are consistent with estimates of risk based on atomic bomb survivors and suggest that these workers do face a small increase in the probability of developing leukemia and other cancers. One of the most recent and extensive studies of workers was published by Cardis, et al. in 2005 . There is evidence that low level, brief radiation exposures are not harmful. Modelling Alternative assumptions for the extrapolation of the cancer risk vs. radiation dose to low-dose levels, given a known risk at a high dose: supra-linearity (A), linear (B), linear-quadratic (C) and hormesis (D). The linear dose-response model suggests that any increase in dose, no matter how small, results in an incremental increase in risk. The linear no-threshold model (LNT) hypothesis is accepted by the International Commission on Radiological Protection (ICRP) and regulators around the world. According to this model, about 1% of the global population develop cancer as a result of natural background radiation at some point in their lifetime. For comparison, 13% of deaths in 2008 are attributed to cancer, so background radiation could plausibly be a small contributor. Many parties have criticized the ICRP's adoption of the linear no-threshold model for exaggerating the effects of low radiation doses. The most frequently cited alternatives are the “linear quadratic” model and the “hormesis” model. The linear quadratic model is widely viewed in radiotherapy as the best model of cellular survival, and it is the best fit to leukemia data from the LSS cohort. Linear no-threshold F(D)=α⋅D Linear quadratic F(D)=α⋅D+β⋅D2 Hormesis F(D)=α⋅D−β In all three cases, the values of alpha and beta must be determined by regression from human exposure data. Laboratory experiments on animals and tissue samples is of limited value. Most of the high quality human data available is from high dose individuals, above 0.1 Sv, so any use of the models at low doses is an extrapolation that might be under-conservative or over-conservative. There is not enough human data available to settle decisively which of these model might be most accurate at low doses. The consensus has been to assume linear no-threshold because it the simplest and most conservative of the three. Radiation hormesis is the conjecture that a low level of ionizing radiation (i.e., near the level of Earth's natural background radiation) helps "immunize" cells against DNA damage from other causes (such as free radicals or larger doses of ionizing radiation), and decreases the risk of cancer. The theory proposes that such low levels activate the body's DNA repair mechanisms, causing higher levels of cellular DNA-repair proteins to be present in the body, improving the body's ability to repair DNA damage. This assertion is very difficult to prove in humans (using, for example, statistical cancer studies) because the effects of very low ionizing radiation levels are too small to be statistically measured amid the "noise" of normal cancer rates. The idea of radiation hormesis is considered unproven by regulatory bodies. If the hormesis model turns out to be accurate, it is conceivable that current regulations based on the LNT model will prevent or limit the hormetic effect, and thus have a negative impact on health. Other non-linear effects have been observed, particularly for internal doses. For example, iodine-131 is notable in that high doses of the isotope are sometimes less dangerous than low doses, since they tend to kill thyroid tissues that would otherwise become cancerous as a result of the radiation. Most studies of very-high-dose I-131 for treatment of Graves disease have failed to find any increase in thyroid cancer, even though there is linear increase in thyroid cancer risk with I-131 absorption at moderate doses.
Radiation-induced cancer
Chronic radiation syndrome
Radiation burn
Spaceflight radiation carcinogenesis
Radiation damage
Metastatic breast cancer
Senile osteoporosis
Bone metastasis