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Mutation and childhood cancer: a probabilistic model for the incidence of retinoblastoma.

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Knudson, A G, Hethcote, H W, Brown, B W·1975·Proceedings of the National Academy of Sciences

Abstract

The incidences of some childhood cancers have been shown to fit a two-mutation hypothesis for cancer initiation. According to this hypothesis, the first mutation can be either germinal or somatic while the second is always somatic. A probabilistic model involving the mean number of tumors per genetically susceptible individual is developed as a function of age and is compared with age incidence data for retinoblastoma. The change in the mean number of tumors with time is interpreted in terms of the growth of retinal cells. In patients who are not genetically susceptible, the times of occurrence of the first and second somatic mutations can be inferred from a comparison of familial and non-familial unilateral case incidences. The total incidences of hereditary and nonhereditary forms of retinoblastoma are related to germinal and somatic mutation rates. The even distribution of certain childhood cancers throughout the world suggests that their incidences are determined by spontaneous mutation rates rather than by local environmental mutagenic carcinogens.

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Metadata

Authors
Knudson, A. G., Hethcote, H. W., & Brown, B. W.
Venue
Proceedings of the National Academy of Sciences
Published
1975-12
Volume
72
Issue
12
Pages
5116-5120
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1972148644
Cited by
348
References
0
FWCI
21.40
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Mutation and childhood cancer: a probabilistic model for the incidence of retinoblastoma. https://app.cochat.ai/papers/10.1073/pnas.72.12.5116
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Knudson, A. G., Hethcote, H. W., & Brown, B. W. (1975). Mutation and childhood cancer: a probabilistic model for the incidence of retinoblastoma. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.72.12.5116

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.