### Abstract

Mathematical modeling of cancer development is aimed at assessing the risk factors leading to cancer. Aging is a common risk factor for all adult cancers. The risk of getting cancer in aging is presented by a hazard function that can be estimated from the observed incidence rates collected in cancer registries. Recent analyses of the SEER database show that the cancer hazard function initially increases with the age, and then it turns over and falls at the end of the lifetime. Such behavior of the hazard function is poorly modeled by the exponential or compound exponential-linear functions mainly utilized for the modeling. In this work, for mathematical modeling of cancer hazards, we proposed to use the Weibull-like function, derived from the Armitage-Doll multistage concept of carcinogenesis and an assumption that number of clones at age t developed from mutated cells follows the Poisson distribution. This function is characterized by three parameters, two of which (r and λ) are the conventional parameters of the Weibull probability distribution function, and an additional parameter (C_{0}) that adjusts the model to the observational data. Biological meanings of these parameters are: r-the number of stages in carcinogenesis, λ-an average number of clones developed from the mutated cells during the first year of carcinogenesis, and C_{0}-a data adjustment parameter that characterizes a fraction of the age-specific population that will get this cancer in their lifetime. To test the validity of the proposed model, the nonlinear regression analysis was performed for the lung cancer (LC) data, collected in the SEER 9 database for white men and women during 1975-2004. Obtained results suggest that: (i) modeling can be improved by the use of another parameter A- the age at the beginning of carcinogenesis; and (ii) in white men and women, the processes of LC carcinogenesis vary by A and C_{0}, while the corresponding values of r and λ are nearly the same. Overall, the proposed Weibull-like model provides an excellent fit of the estimates of the LC hazard function in aging. It is expected that the Weibull-like model can be applicable to fit estimates of hazard functions of other adult cancers as well.

Original language | English (US) |
---|---|

Pages (from-to) | 179-188 |

Number of pages | 10 |

Journal | Cancer Informatics |

Volume | 9 |

State | Published - Oct 1 2010 |

### Fingerprint

### Keywords

- Agin
- Cancer
- Cancer hazard
- Weibull distribution

### ASJC Scopus subject areas

- Oncology
- Cancer Research

### Cite this

*Cancer Informatics*,

*9*, 179-188.

**Weibull-like model of cancer development in aging.** / Mdzinarishvili, Tengiz; Sherman, Simon.

Research output: Contribution to journal › Article

*Cancer Informatics*, vol. 9, pp. 179-188.

}

TY - JOUR

T1 - Weibull-like model of cancer development in aging

AU - Mdzinarishvili, Tengiz

AU - Sherman, Simon

PY - 2010/10/1

Y1 - 2010/10/1

N2 - Mathematical modeling of cancer development is aimed at assessing the risk factors leading to cancer. Aging is a common risk factor for all adult cancers. The risk of getting cancer in aging is presented by a hazard function that can be estimated from the observed incidence rates collected in cancer registries. Recent analyses of the SEER database show that the cancer hazard function initially increases with the age, and then it turns over and falls at the end of the lifetime. Such behavior of the hazard function is poorly modeled by the exponential or compound exponential-linear functions mainly utilized for the modeling. In this work, for mathematical modeling of cancer hazards, we proposed to use the Weibull-like function, derived from the Armitage-Doll multistage concept of carcinogenesis and an assumption that number of clones at age t developed from mutated cells follows the Poisson distribution. This function is characterized by three parameters, two of which (r and λ) are the conventional parameters of the Weibull probability distribution function, and an additional parameter (C0) that adjusts the model to the observational data. Biological meanings of these parameters are: r-the number of stages in carcinogenesis, λ-an average number of clones developed from the mutated cells during the first year of carcinogenesis, and C0-a data adjustment parameter that characterizes a fraction of the age-specific population that will get this cancer in their lifetime. To test the validity of the proposed model, the nonlinear regression analysis was performed for the lung cancer (LC) data, collected in the SEER 9 database for white men and women during 1975-2004. Obtained results suggest that: (i) modeling can be improved by the use of another parameter A- the age at the beginning of carcinogenesis; and (ii) in white men and women, the processes of LC carcinogenesis vary by A and C0, while the corresponding values of r and λ are nearly the same. Overall, the proposed Weibull-like model provides an excellent fit of the estimates of the LC hazard function in aging. It is expected that the Weibull-like model can be applicable to fit estimates of hazard functions of other adult cancers as well.

AB - Mathematical modeling of cancer development is aimed at assessing the risk factors leading to cancer. Aging is a common risk factor for all adult cancers. The risk of getting cancer in aging is presented by a hazard function that can be estimated from the observed incidence rates collected in cancer registries. Recent analyses of the SEER database show that the cancer hazard function initially increases with the age, and then it turns over and falls at the end of the lifetime. Such behavior of the hazard function is poorly modeled by the exponential or compound exponential-linear functions mainly utilized for the modeling. In this work, for mathematical modeling of cancer hazards, we proposed to use the Weibull-like function, derived from the Armitage-Doll multistage concept of carcinogenesis and an assumption that number of clones at age t developed from mutated cells follows the Poisson distribution. This function is characterized by three parameters, two of which (r and λ) are the conventional parameters of the Weibull probability distribution function, and an additional parameter (C0) that adjusts the model to the observational data. Biological meanings of these parameters are: r-the number of stages in carcinogenesis, λ-an average number of clones developed from the mutated cells during the first year of carcinogenesis, and C0-a data adjustment parameter that characterizes a fraction of the age-specific population that will get this cancer in their lifetime. To test the validity of the proposed model, the nonlinear regression analysis was performed for the lung cancer (LC) data, collected in the SEER 9 database for white men and women during 1975-2004. Obtained results suggest that: (i) modeling can be improved by the use of another parameter A- the age at the beginning of carcinogenesis; and (ii) in white men and women, the processes of LC carcinogenesis vary by A and C0, while the corresponding values of r and λ are nearly the same. Overall, the proposed Weibull-like model provides an excellent fit of the estimates of the LC hazard function in aging. It is expected that the Weibull-like model can be applicable to fit estimates of hazard functions of other adult cancers as well.

KW - Agin

KW - Cancer

KW - Cancer hazard

KW - Weibull distribution

UR - http://www.scopus.com/inward/record.url?scp=77957158583&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77957158583&partnerID=8YFLogxK

M3 - Article

C2 - 20838610

AN - SCOPUS:77957158583

VL - 9

SP - 179

EP - 188

JO - Cancer Informatics

JF - Cancer Informatics

SN - 1176-9351

ER -