Cancer Care Ontario, Canada
Posters-Accepted Abstracts: J Appl Computat Math
Regular screening for breast cancer with mammography is widely recommended to reduce mortality due to breast cancer. However, whether breast cancer screening does more harm than good, has been constantly debated. Since a full evaluation of screening will take a follow-up of about 10 to 15 years to provide reliable estimate of the benefits, it is often unrealistic to expect each new modification of a screening technique to be evaluated in this way. Therefore, one needs measures of effects which are rapidly estimable. In this presentation, two measures of interest, the duration of pre-clinical state and the false negative rate, are discussed. Two estimation procedures are proposed to model the pre-clinical state duration, the false negative rate of screening exam and the underlying incidence rate in the screened population. Both methods assume the sojourn time follows a negative exponential distribution, but two different functions are used for the false negative rate: (1) constant over time and (2) an exponential distribution to reflect the fact that lesions may become easier to detect the closer in time that they are to being detected clinically. We show how to estimate those measures by using data on the observed prevalence of disease at a series of screens and on the incidence of disease during intervals between those screens. We illustrate the methods with data from the Ontario Breast Screening Program.
Journal of Applied & Computational Mathematics received 1282 citations as per Google Scholar report