The purpose of this project is the research and development of biostatistical methods and mathematical models appropriate for the analysis of epidemiologic studies related to cancer control and prevention. The various statistical problems studied under this project are derived from the needs of other activities in the Division. This research includes the development of mathematical models which can be used to predict and evaluate the effect of different intervention strategies. A two-stage model of the carcinogenic process, adapted from a model proposed by Moolgavkar, Venzon, and Knudson for studying the effects of cancer-inhibitory agents such as dietary retinoids is currently being developed and tested. In addition, the Armitage-Doll multistage model is being used to quantify the relationship between cigarette smoking prevalence and lung cancer mortality in the U.S. to estimate the effects of hypothetical changes in the future prevalence of cigarette smoking. The trend of lung cancer mortality is also being analyzed by regression models to project its future course which would be expected without any specific population intervention. Other methodolgic problems under investigation include the modification of logistic regression methods to incorporate knowledge of the sampling rates used in population-basec case-control studies of cancer, and development of a set of interactive computer programs which can be used to analyze the trends of cancer rates over time.
