The Wisconsin Breast Cancer Epidemiology Simulation Model is a discrete-event, stochastic simulation model using a systems-science modeling approach to replicate breast cancer incidence and mortality in the U.S. population from 1975 to 2000. Four interacting processes are modeled over time: (1) natural history of breast cancer, (2) breast cancer detection, (3) breast cancer treatment, and (4) competing cause mortality. These components form a complex interacting system simulating the lives of 2.95 million women (approximately 1/50 the U.S. population) from 1950 to 2000 in 6-month cycles. After a "burn in" of 25 years to stabilize prevalent occult cancers, the model outputs age-specific incidence rates by stage and age-specific mortality rates from 1975 to 2000. The model simulates occult as well as detected disease at the individual level and can be used to address "What if?" questions about effectiveness of screening and treatment protocols, as well as to estimate benefits to women of specific ages and screening histories.

Choosing among the efficient policies to guide current screening recommendations requires consideration of costs to promote participation in screening and measurement of acute quality-of-life effects of mammography.

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Women faculty perceived that gender climate created specific, serious obstacles to their professional development. Many of those obstacles (e.g., inconvenient meeting times and lack of child care) are remediable. These data suggest that medical schools can improve the climate and retain and promote women by more inclusive networking, attention to meeting times and child care, and improved professional interactions between men and women faculty.

The purpose of this study was to develop life tables by smoking status removing lung cancer as a cause of death. These life tables are inputs to studies that compare the effectiveness of lung cancer treatments or interventions, and provide a way to quantify time until death from causes other than lung cancer. The study combined actuarial and statistical smoothing methods, as well as data from multiple sources, to develop separate life tables by smoking status, birth cohort, by single year of age, and by sex. For current smokers, separate life tables by smoking quintiles were developed based on the average number of cigarettes smoked per day by birth cohort. The end product is the creation of six non-lung cancer life tables for males and six tables for females: five current smoker quintiles and one for never smokers. Tables for former smokers are linear combinations of the appropriate table based on the current smoker quintile prior to quitting smoking and the never smoker probabilities, plus added covariates for the smoking quit age and time since quitting.