Abstract of Meeting Paper

Society for Risk Analysis-Europe 1997 Annual Meeting

Cancer Risks at Low Doses of Ionizing Radiation or Chemicals. F. Granath, Dept. of Cancer Epidemiology, Radiumhemmet, Karolinska Hospital, 171 76 Stockholm, fax +46 8 32 61 13; and L. Ehrenberg, Dept. of Radiobiology, Stockholm University, 106 91 Stockholm, fax +46 8 16 64 88

The true shape of dose-response (dose-risk) relationships for cancer caused by low doses of radiations or chemicals are still debated.

This is due to the impossibility, for statistical reasons, to obtain informative observations of the incremental incidence below some dose. Below this detection limit, which will always exist although it can be decreased by increasing the size of the studied populations, the dose-risk curve may have any shape. The estimation of cancer risks in this "dark" region by linear extrapolation from higher doses, where informative observations can be made, may then be seen as an administratively practical measure rather than a scientifically based effort to describe "true" relationship. The uncertainty about the true dose-risk relationship at low doses recently led the Health Physics Society to recommend that risks should not be estimated at doses below 50 mSv (5 rem) in a year or 10 rem in a lifetime.

Recent cell-genetic studies have given proof of earlier assumptions that mutation is the key event in the carcinogenic action of ionizing radiation and so-called genotoxic chemicals. The mutations, e.g. in suppressor genes, caused by an exposure then interact with other inherited or acquired factors with influences on the probability of tumour development.

The key role of mutation in tumorigenesis renders it possible to elucidate the dose response relationships at the high resolving power of mutational systems. Such studies indicate, throughout, that the true dose-response relationships for induced mutation are linear (or somewhat, and perhaps negligeably, superlinear). It belongs to the rules of statistics that the absence of a no-effect threshold cannot be proved. However, the demonstration that the upper confidence limit for a possible no-effect threshold is below the lowest dose a cell can receive, viz. one hit, may serve as evidence of linearity.

According to the present state of the art, average attributable risk increments are best estimated by a linear multiplicative model. This is already applied in radiological protection, and should be used also for genotoxic chemicals.

 


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