Volume 12 - Article 10 | Pages 237–272  

Mathematical Models for Human Cancer Incidence Rates

By Konstantin Arbeev, Svetlana Ukraintseva, Lyubov S. Arbeeva, Anatoli Yashin

Abstract

The overall cancer incidence rate declines at old ages. Possible causes of this decline include the effects of cross-sectional data which transform cohort dynamics into age pattern, population heterogeneity which selects out individuals susceptible to cancer, decline in some carcinogenic exposures in the old, effects of individual aging which slow down major physiological processes in an organism, etc.
We discuss several mathematical models contributing to the explanation of this phenomenon. We extend the Strehler and Mildvan model of aging and mortality and apply it to the analysis of data on cancer incidence at old ages. The model explains time trends and age patterns of cancer incidence rates. Applications to cancer incidence data provided by the International Agency for Research on Cancer illustrate the models.

Author's Affiliation

• Konstantin Arbeev - Duke University, United States of America EMAIL
• Svetlana Ukraintseva - Duke University, United States of America EMAIL
• Lyubov S. Arbeeva - Ulyanovsk State University, Russian Federation EMAIL
• Anatoli Yashin - Duke University, United States of America EMAIL

Other articles by the same author/authors in Demographic Research

Decline in Human Cancer Incidence Rates at Old Ages: Age-Period-Cohort Considerations
Volume 12 - Article 11

Individual Aging and Cancer Risk: How are They Related?
Volume 9 - Article 8

Two proofs of a recent formula by Griffith Feeney
Volume 14 - Article 3

Most recent similar articles in Demographic Research

The influence of parental cancer on the mental health of children and young adults: Evidence from Norwegian register data on healthcare consultations
Volume 50 - Article 27    | Keywords: cancer, children, fixed effects, longitudinal, mental health, parents registers

Ageing and diversity: Inequalities in longevity and health in low-mortality countries
Volume 50 - Article 12    | Keywords: aging, health, lifespan inequality, longevity, old-age threshold, regional differences, socioeconomic status

The contributions of stochastic demography and social inequality to lifespan variability
Volume 49 - Article 13    | Keywords: heterogeneity, inequality, lifetime reproduction, longevity, stochasticity, variance decomposition

Frailty at death: An examination of multiple causes of death in four low mortality countries in 2017
Volume 49 - Article 2    | Keywords: aging, causes of mortality, mortality, multiple causes of death

World population aging as a function of period demographic conditions
Volume 48 - Article 13    | Keywords: aging, demographic transition, population