Cancer susceptibility simulation [Health Services : Research Projects : Cancer Control Research : BC Cancer Research Centre]

Description

About 10% of cancer patients in Canada have a family history of the disease. The family history could have arisen because of genetic susceptibility that is inherited from parents, or because of non-genetic exposures that are shared between family members. A family history can also arise by chance, with probability affected by the size and structure of someone's family. Most family histories are likely the result of genetic factors, environmental exposures and chance combined.

A population-based program may be introduced to provide genetic testing services. The costs of the program include those of identifying high-risk families and providing services for people who are eligible. The program's benefits depend on the improvement that is achieved in the population's health, including changes in psychological and emotional outcomes, and reductions in morbidity and mortality.

The main objectives of the study are (1) to create a simulation model of cancer family history for people with germline mutations in cancer susceptibility genes, (2) estimate the sensitivity, specificity and post-test likelihoods associated with family history as a predictor of carrier status for various cancer susceptibility genes, and (3) estimate the number of carriers that are eligible for a population-based genetic testing program.

We will compare the simulation results with data from the Hereditary Cancer Program at the BC Cancer Agency, and with data from the HNPCC genetic testing program in Ontario. Hereditary cancer services are likely to expand substantially in the coming decades. The results of the study will determine efficient policies at the Hereditary Cancer Program of the BC Cancer Agency, and thereby inform similar programs in other regions of Canada. The project will create software with a simple, non-mathematical format. This knowledge-translation effort ensures that the fruits of our research can be used by health care planners and policy-makers to predict the efficiency of new provincial programs.