A Breakthrough on Modeling Cancer Prevention and Elimination by Low Radiation Doses

Background Previously the author was unable to develop a formal mathematical characterization of his probability-based hormetic relative risk (HRR) model for cancer prevention/elimination by absorbed doses ( D ) of ionizing radiation in the hormetic zone where D < D t (population absorbed dose threshold for cancer induction). Objective To develop a formal mathematical characterization of the HRR model’s disease prevention function DPF ( D ), which is the cancer prevention/elimination probability. Approach Use distributed (over a population) individual-specific, natural-defenses-enhancing (E) and suppressing (S) dose thresholds. Results DPF ( D ) is now mathematically characterized based on Weibull-type E and S thresholds distributions. The E thresholds predominate at very low radiation doses and the S thresholds predominate at higher doses just below D t . This leads to a hormetic dose-response relationship for cancer relative risk RR ( D ) (= 1 − DPF ( D )) for doses from zero (representing natural background radiation exposure) to dose D t . The greatly improved HRR model is quite flexible and was applied to lung cancer and reticulum cell sarcoma prevention/elimination data from a study involving more than 15 000 gamma-ray exposed mice. Conclusion The System of Radiological Protection needs to be updated to account for health benefits rather than invalid LNT-hypothesis-based phantom radiation-caused cancers from radiation doses < D t .