This project supports research to improve methods for estimating absolute and attributable risk and collaborative studies to estimate such risks for various cancers. We found that mammographic density was a promising predictor of breast cancer risk using data from the Breast Cancer Detection and Demonstration Project (BCDDP), and we gathered additional information on mammographic density from BCDDP to construct a risk model that incorporates this factor. We validated a previously developed model for projecting breast cancer risk using independent data from the Breast Cancer Prevention Trial. We incorporated a version of this model for projecting the risk of invasive breast cancer into a computer program that also offers other medical information useful in deciding whether or not to take tamoxifen to prevent breast cancer. This material has been distributed widely on diskette by NCIs Office of Cancer Communications. We published decision diagrams and algorithms based on individualized estimates of breast cancer risk to help women in their forties decide whether to begin regular screening with mammography. We analyzed the strengths and weaknesses of the kin-cohort design for estimating the risk of disease from an autosomal dominant gene. This design requires somewhat smaller sample sizes than competing designs. It can be implemented rapidly, and it yields information on genetic effects for several diseases from a single study. The kin-cohort design is subject to certain biases, however, including ascertainment bias and bias that results from ignoring non-genetic sources of intrafamilial correlation. We developed methods to analyze data from a population-based case-control study with cluster sampling to estimate the absolute and relative risk of non- melanoma skin cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Intramural Research (Z01)
Project #
1Z01CP010111-04
Application #
6289534
Study Section
Special Emphasis Panel (BB)
Project Start
Project End
Budget Start
Budget End
Support Year
4
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Division of Cancer Epidemiology and Genetics
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Gail, MH; Costantino, JP; Bryant, J et al. (2000) RESPONSE: re: weighing the risks and benefits of tamoxifen treatment for preventing breast cancer J Natl Cancer Inst 92:758
Gail, M H; Costantino, J P; Bryant, J et al. (2000) Re: Risk/benefit assessment of tamoxifen to prevent breast cancer-still a work in progress? J Natl Cancer Inst 92:574-5
Gail, M H; Costantino, J P; Bryant, J et al. (1999) Weighing the risks and benefits of tamoxifen treatment for preventing breast cancer. J Natl Cancer Inst 91:1829-46
Costantino, J P; Gail, M H; Pee, D et al. (1999) Validation studies for models projecting the risk of invasive and total breast cancer incidence. J Natl Cancer Inst 91:1541-8