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Epidemiology

Minimum latency effects for cancer associated with exposures to radiation or other carcinogens

British Journal of Cancer volume 130, pages 819–829 (2024)Cite this article

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Abstract

Background

In estimating radiation-associated cancer risks a fixed period for the minimum latency is often assumed. Two empirical latency functions have been used to model latency, continuously increasing from 0. A stochastic biologically-based approach yields a still more plausible way of describing latency and can be directly estimated from clinical data.

Methods

We derived the parameters for a stochastic biologically-based model from tumour growth data for various cancers, and least-squares fitted the two types of empirical latency function to the stochastic model-predicted cumulative probability.

Results

There is wide variation in growth rates among tumours, particularly slow for prostate and thyroid cancer and particularly fast for leukaemia. The slow growth rate for prostate and thyroid tumours implies that the number of tumour cells required for clinical detection cannot greatly exceed 106. For all tumours, both empirical latency functions closely approximated the predicted biological model cumulative probability.

Conclusions

Our results, illustrating use of a stochastic biologically-based model using clinical data not tied to any particular carcinogen, have implications for estimating latency associated with any mutagen. They apply to tumour growth in general, and may be useful for example, in planning screenings for cancer using imaging techniques.

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Fig. 1
Fig. 2: The cumulative probability of detection of various types of solid cancer apart from lung cancer, as given by the parameters of Table 1.
Fig. 3: The cumulative probability of detection of leukaemia and lung cancer, assuming faster- and slower-growing leukaemia and lung cancer stochastic models, assuming Nlim = 109 cells, with least-squares-fitted latency functions of the type used by Kocher et al. [4] and given by Eq. (1).
Fig. 4: The cumulative probability of detection of leukaemia and lung cancer, assuming faster- and slower-growing leukaemia and lung cancer stochastic models, assuming Nlim = 109 cells, with least-squares-fitted latency functions of the type used by Ulanowski et al. [7] and given by Eq. (2).

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Data availability

All data used are given in Table 1, also in Appendix B, and are derived from the peer-reviewed literature.

Code availability

The various calculations used are given in an Excel spreadsheet, provided in Appendix B.

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Acknowledgements

The work of MPL was supported by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics. The work of MPL, ME, and AIA was done in conjunction with work done for ICRP Task Group TG122. ME would like to thank Dr Hannes Rennau (University of Rostock) for discussions on tumour sizes and development. The authors thank the three referees for their detailed and helpful remarks.

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Authors and Affiliations

  1. Radiation Epidemiology Branch, National Cancer Institute, Bethesda, MD, 20892-9778, USA

    Mark P. Little

  2. Faculty of Health and Life Sciences, Oxford Brookes University, Headington Campus, Oxford, OX3 0BP, UK

    Mark P. Little

  3. Federal Office for Radiation Protection, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany

    Markus Eidemüller & J. Christian Kaiser

  4. Oak Ridge Center for Risk Analysis, Inc., Oak Ridge, TN, 37830, USA

    A. Iulian Apostoaei

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Contributions

MPL conceived and designed the study, performed the analysis and assembled the first draft. MPL, AIA, ME and JCK performed literature searches and assembled the analytic database. All authors contributed equally to the writing and editing of subsequent drafts. All authors approved the final draft.

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Correspondence to Mark P. Little.

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Little, M.P., Eidemüller, M., Kaiser, J.C. et al. Minimum latency effects for cancer associated with exposures to radiation or other carcinogens. Br J Cancer 130, 819–829 (2024). https://doi.org/10.1038/s41416-023-02544-z

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