Medical decision making

Prediction model for breast cancer, and mathematical modeling of breast cancer progression

We developed models for risk prediction of invasive breast cancer incidence for women with certain risk factors, such as age and families with breast cancer, and identified the predictors of competing mortality to invasive breast cancer. We also modeled the progression of breast cancer using a partially observable Markov model, and estimated the progression parameters and the probabilities of false negative mammogram and physical examination. The results of this research enhance the knowledge of breast cancer risk factors and improve the prediction of breast cancer incidence and mortality rates.

Evaluating breast cancer screening policies

We first proposed a model to evaluate the effect of different screening intervals on reduction of breast cancer mortality. We then included both screening and treatment stages of breast cancer, and developed a simulation model to evaluate various screening policies to study the impact of screening for age-based subpopulations of women in Canada. The results of these models are expected to improve the health of Canadian women, and produce efficient policies for the starting and ending ages of breast screening, as well as screening frequency.