Analysis of a hormesis effect in the leukemia-caused mortality among atomic bomb survivors

Alexander Tsodikov, John Dicello, Marco Zaider, Alexander Zorin, Andrei Y. Yakovlev

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Yakovlev and Polig (1996) developed a mechanistically motivated stochastic model of radiation carcinogenesis allowing for cell death. The key feature of the model is that it allows for radiation-induced cell killing to compete with the process of tumor promotion. This model describes and explains a wide range of experimental findings documented in the radiobiological literature, including the inverse dose-rate effect and radiation hormesis. The model has successfully been applied to various sets of experimental and epidemiological data to gain quantitative insight into the processes of tumorigenesis induced by radiation and chemical carcinogens. In this paper, we discuss the most recent application of the Yakovlev-Polig model to the analysis of epidemiological data on the mortality caused by radiation-induced leukemia (all types) among the atomic bomb survivors (Hiroshima and Nagasaki). Nonparametric estimates of the hazard function for leukemia latency time were obtained for three different dose groups identified in the Hiroshima cohort. The behavior of these estimates suggests the presence of the hormesis-type effect in relation to leukemia-caused mortality. A parsimonious version of the mechanistic model yields parametric estimates that are in good agreement with their nonparametric counterparts. Using the parametric model, we corroborated the presence of a moderate hormesis effect in the Hiroshima data. However, we have been unable to uncover the same effect with the Nagasaki cohort of the atomic bomb survivors.

Original languageEnglish (US)
Pages (from-to)829-847
Number of pages19
JournalHuman and Ecological Risk Assessment (HERA)
Volume7
Issue number4
StatePublished - 2001

Keywords

  • Atomic bomb
  • Leukemia
  • Radiation hormesis
  • Statistical analysis
  • Stochastic modeling
  • Survivors

ASJC Scopus subject areas

  • Ecological Modeling
  • Pollution
  • Health, Toxicology and Mutagenesis

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