In February, Mitchell H. Gail, M.D., Ph.D., a senior investigator in the Biostatistics Branch, presented the annual NIH Robert S. Gordon, Jr. Lecture in Epidemiology. His lecture was titled “Using risk models for breast cancer prevention.” David Murray, Ph.D., Associate Director for Disease Prevention and Director of the NIH Office of Disease Prevention, introduced Dr. Gail and noted, “I’m particularly honored to make this introduction, as I have benefitted personally from Dr. Gail’s methods work and cite his papers often in my own research.”
Dr. Gail uses statistical methods for the design and analysis of epidemiologic studies, including studies of genetic factors and models to predict the absolute risk of disease. To date, epidemiologic studies have established several risk factors for breast cancer, such as family history, age when giving birth for the first time, biopsy findings, and mammographic density. These factors can be combined with breast cancer incidence rates to construct models of absolute risk of breast cancer, which are useful for counseling women in clinical settings and in public health applications.
The public health applications of risk models include designing chemoprevention trials, implementing “high risk” prevention strategies that focus only on women who are at highest risk for breast cancer, assessing the potential of preventive interventions to reduce absolute risk of breast cancer in the population, and using risk estimates to allocate prevention resources under cost constraints. Dr. Gail’s lecture reviewed the usefulness of risk models in these applications and the potential of additional risk factors, such as single nucleotide polymorphisms, to improve the performance of these models.
The lecture series was established in 1995 as a tribute to Dr. Gordon for his distinguished service in coordinating prevention-related research and clinical trials across NIH. View a video of Dr. Gail’s lecture.