Table 1.

Partitions of Stochastic Events in Breast Cancer Model

Partition 1 – Woman and Tumor Characteristics
Stochastic Event	Order and Frequency	Controlling Input parameters
Date of non-breast cancer death	Once at beginning of lifetime	Life tables by birth cohort
Tumor onset	Once per time cycle	Age- and birth cohort specific onset rate
Tumor growth rate	Once at onset	Growth rate distribution
Tumor progression	Once per cycle post onset	Growth rate, Poisson process
Time to breast cancer death	Once at distant stage	Survival curve
Treatment type	Once at detection	Dissemination of adjuvant treatment
Treatment effectiveness	Once at detection	Likelihood of treatment effectiveness as function of tumor characteristics
Partition 2 – Clinical/Symptom Detection
Stochastic Event	Order	Controlling Input parameters
Detection	Once per time cycle post onset	Likelihood as a function of tumor size
Partition 3 – Screen Detection
Stochastic Event	Order	Controlling Input parameters
Assignment of screening schedule	Once at beginning of lifetime	Screening dissemination sub-model
Result of Mammogram	Once per screen if tumor	Sensitivity of mammography by tumor size