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Basic Equations and Computing Procedures for Frailty Modeling of Carcinogenesis: Application to Pancreatic Cancer Data

Modeling of cancer hazards at age t deals with a dichotomous population, a small part of which (the fraction at risk) will get cancer, while the other part will not. Therefore, we conditioned the hazard function, h(t), the probability density function (pdf), f(t), and the survival function, S(t), on...

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Detalles Bibliográficos
Autores principales: Mdzinarishvili, Tengiz, Sherman, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3583266/
https://www.ncbi.nlm.nih.gov/pubmed/23471174
http://dx.doi.org/10.4137/CIN.S8063
Descripción
Sumario:Modeling of cancer hazards at age t deals with a dichotomous population, a small part of which (the fraction at risk) will get cancer, while the other part will not. Therefore, we conditioned the hazard function, h(t), the probability density function (pdf), f(t), and the survival function, S(t), on frailty α in individuals. Assuming α has the Bernoulli distribution, we obtained equations relating the unconditional (population level) hazard function, h(U)(t), cumulative hazard function, H(U)(t), and overall cumulative hazard, H(0), with the h(t), f(t), and S(t) for individuals from the fraction at risk. Computing procedures for estimating h(t), f(t), and S(t) were developed and used to fit the pancreatic cancer data collected by SEER9 registries from 1975 through 2004 with the Weibull pdf suggested by the Armitage-Doll model. The parameters of the obtained excellent fit suggest that age of pancreatic cancer presentation has a time shift about 17 years and five mutations are needed for pancreatic cells to become malignant.