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Updated: Jun 3, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Analysis of retinoblastoma age incidence data using a fully stochastic cancer model
Mark P Little1, Ruth A Kleinerman, Charles A Stiller
1Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, DHHS, NIH, Bethesda, MD 20852-7238, USA. mark.little@nih.gov
Abstract:
Retinoblastoma (RB) is an important ocular malignancy of childhood. It has been commonly accepted for some time that knockout of the two alleles of the RB1 gene is the principal molecular target associated with the occurrence of RB. In this article, we examine the validity of the two-hit theory for RB by comparing the fit of a stochastic model with two or more mutational stages. Unlike many such models, our model assumes a fully stochastic stem cell compartment, which is crucial to its behavior. Models are fitted to a population-based dataset comprising 1,553 cases of RB for the period 1962-2000 in Great Britain (England, Scotland and Wales). The population incidence of RB is best described by a fully stochastic model with two stages, although models with a deterministic stem cell compartment yield equivalent fit; models with three or more stages fit much less well. The results strongly suggest that knockout of the two alleles of the RB1 gene is necessary and may be largely sufficient for the development of RB, in support of Knudson's two-hit hypothesis.
Insights
Knudson's two-hit hypothesis is supported by new research on childhood retinoblastoma (RB). The study indicates that inactivating both RB1 gene alleles is necessary and likely sufficient for RB development.
Area of Science:
- Ophthalmology
- Genetics
- Cancer Biology
Background:
- Retinoblastoma (RB) is a significant childhood eye cancer.
- The prevailing theory suggests RB arises from the inactivation of both RB1 gene alleles.
Purpose of the Study:
- To rigorously test Knudson's two-hit hypothesis for retinoblastoma.
- To evaluate stochastic models of cancer development against population data.
Main Methods:
- A stochastic mathematical model with varying mutational stages was developed.
- The model was fitted to a large dataset of 1,553 British retinoblastoma cases (1962-2000).
- Model fit was assessed using a fully stochastic stem cell compartment.
Main Results:
- A two-stage stochastic model provided the best fit for the population incidence of retinoblastoma.
- Models with three or more stages demonstrated a significantly poorer fit.
- A deterministic stem cell compartment model showed equivalent fit to the two-stage stochastic model.
Conclusions:
- The findings strongly support that the knockout of both RB1 gene alleles is necessary and largely sufficient for retinoblastoma development.
- The study validates the core principles of Knudson's two-hit hypothesis in the context of retinoblastoma.
- A two-stage mutational process, likely involving RB1 inactivation, is the most parsimonious explanation for RB incidence.
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