Epidemiology and Stochastic Modelling

Because the Japanese atomic bomb survivors and other radiation-exposed groups have not been followed to extinction, it has been necessary to use a variety of risk projection models to estimate radiation-induced cancer risks to the end of life. Much use has been made (e.g. by the International Commission on Radiological Protection, the United Nations Scientific Committee on the Effects of Atomic Radiation) of the time-constant relative risk model for projecting radiation-induced cancer risks to the end of life. Solid cancer radiation risks (the largest part of total cancer risks) are dominated by risks for those exposed in childhood. However, solid cancer risks for this group are most uncertain: only now is this group of survivors in the Japanese cohort reaching the age at which substantial numbers of solid cancers are starting to appear. There have been indications from the recent Japanese atomic bomb survivor data and other medically exposed groups that solid cancer excess relative risks for those exposed in childhood might be reducing with time. Stochastic mechanistic models developed here explain these and other patterns of cancer induction by ionising radiation. Because of indications of lack of fit of the Armitage Doll model, we have developed generalisations of this model and also of the two mutation model of Moolgavkar, Venzon and Knudson.

There is much biological data suggesting that the initiating lesion in the multistage process leading to cancer might be one involving a destabilization of the genome resulting in elevation of mutation rates. Stochastic cancer models have also been developed that allow for this phenomenon of transmissible genomic instability

It has been generally accepted that most biological damage produced by ionizing radiation occurs when radiation interacts directly with DNA in the cell nucleus or indirectly through the action of free radicals. However, there have been a number of reports of cells exposed experimentally to α-particle radiation in which more cells showed damage than were traversed by α particles i.e. a bystander effect. This is observed for a number of end points, including cell killing, micronucleus induction, and mutation induction. The bystander effect implies that the dose response after broad-beam irradiation could be highly concave at low doses (i.e. with slope of the dose response generally decreasing with increasing dose) because of saturation of the bystander effect at high doses, so that predictions of low-dose effects obtained by linear extrapolation from data for high-dose exposures would be substantial underestimates. However, other forms of dose response are also possible, including ones exhibiting low-dose convexity. A number of stochastic models of this phenomenon have been developed and fitted to radiation data.