Summary
Objectives:
Cancer epidemiologists are often asked by members of the interested public about
possible associations between suspected carcinogens and apparently increased small-area
cancer incidence rates. Frequently, no systematic incidence differences can be demonstrated.
Nevertheless, it is necessary to address public concerns about suspected cancer clusters.
To facilitate explanations about the large random variation of small-area tumor incidence,
we implemented a software simulation tool in R.
Methods:
Under the assumption of no cancer causes other than chance, the tool simulates a
small village population with an average number of five inhabitants per house and
allows graphical visualisation of ten streets with 100 houses. Published age-specific
incidence and mortality data are used for event sampling based on the binomial distribution.
Program parameters include sample size, age distribution, cancer incidence, and mortality
rates.
Results:
On average, 22 percent (2.2/10) of all houses per street have been inhabited by at
least one cancer patient during the last five years in our simulated small village.
A situation where all (10) houses in a street have been inhabited by at least one
cancer patient during the last five years appears to be very rare (less than one in
a million streets).
Conclusions:
Our software tool can be used effectively for numerical and graphical visualisation
of small-area tumour incidence and prevalence rates due to chance alone. The explanation
of basic epidemiological concepts to members of the public can help to increase public
motivation and support for population-based cancer registration. Our simulation tool
can be used to support this goal.
Keywords
Small area - cancer - incidence - simulation - chance
