Commentary and Review Series 1-04
Commentary: Mechanistic models for radiation carcinogenesis and the atomic bomb survivor data
Pierce DARadiat Res 160(6):718-23, 2003
Summary
Recently, Heidenreich et al. (Radiat. Res., 158, 607-617, 2002) suggested that the Radiation Effects Research Foundation (RERF) A-bomb survivor cohort study is not large enough to discriminate between various possible carcinogenic mechanisms. At least with the current follow-up, this is true to some extent, but I think the specific issues are rather different than they suggest. In particular, I do not think it is true—as they further indicate—that various models fit the data about equally well while estimating very different patterns of excess risk, which would imply that these patterns cannot be reasonably well characterized. I will point to specific criticisms of their approach to the data and offer some more general comments on mechanistic modeling approaches. Although there are important distinctions, I suggest on a very optimistic note that the two major approaches may be converging, and soon the main differences may not be in the assumptions made but in the aims of the modeling.
(c) 2003 by Radiation Research Society
Reprinted by permission of Radiation Research Society
Recently, Heidenreich et al. (Radiat. Res., 158, 607-617, 2002) suggested that the Radiation Effects Research Foundation (RERF) A-bomb survivor cohort study is not large enough to discriminate between various possible carcinogenic mechanisms. At least with the current follow-up, this is true to some extent, but I think the specific issues are rather different than they suggest. In particular, I do not think it is true—as they further indicate—that various models fit the data about equally well while estimating very different patterns of excess risk, which would imply that these patterns cannot be reasonably well characterized. I will point to specific criticisms of their approach to the data and offer some more general comments on mechanistic modeling approaches. Although there are important distinctions, I suggest on a very optimistic note that the two major approaches may be converging, and soon the main differences may not be in the assumptions made but in the aims of the modeling.
(c) 2003 by Radiation Research Society
Reprinted by permission of Radiation Research Society
Age-time patterns of radiogenic cancer risk: Their nature and likely explanations
Pierce DA
J Radiol Prot 22(3A):A147-54, 2002
J Radiol Prot 22(3A):A147-54, 2002
Summary
It is important for both radiation protection and scientific reasons to understand the age-time patterns of radiation cancer risk. This is surprisingly difficult even for acute exposures and much more so for prolonged exposures. I shall provide current information on this for solid cancers among atomic-bomb survivors, pointing out some of the difficulties in description and interpretation. I shall then take up some stochastic considerations regarding accumulation of mutations, which may help in dealing with these difficulties. These considerations are highly idealised, and their consequences should mainly be used only for guidance rather than as a primary basis for descriptive analyses. They are particularly suitable for this because they provide insights fairly independent of parameter values in the stochastic models involved.
(c) 2002 IOP Publishing Ltd
Reprinted by permission of Institute of Physics Publishing
It is important for both radiation protection and scientific reasons to understand the age-time patterns of radiation cancer risk. This is surprisingly difficult even for acute exposures and much more so for prolonged exposures. I shall provide current information on this for solid cancers among atomic-bomb survivors, pointing out some of the difficulties in description and interpretation. I shall then take up some stochastic considerations regarding accumulation of mutations, which may help in dealing with these difficulties. These considerations are highly idealised, and their consequences should mainly be used only for guidance rather than as a primary basis for descriptive analyses. They are particularly suitable for this because they provide insights fairly independent of parameter values in the stochastic models involved.
(c) 2002 IOP Publishing Ltd
Reprinted by permission of Institute of Physics Publishing