New Paradigm of Breast Cancer Causation and Prevention- Phase II
Creators: name: University Of California Office Of The President
Publisher: name: University of California Office of the President
publisherIdentifier: https://ror.org/00dmfq477
publisherIdentifierScheme: ROR
Year: 2024

description: There is no one cause of breast cancer. Causes of breast cancer are actually multiple and include genetic, other biological, behavioral, environmental and social factors, all of which can interact and influence each other at various critical stages of life. Traditional studies that have tended to focus on one factor at a time, while trying to control or adjust for other factors and have given us much information. But the larger picture cannot be taken into account by these traditional methods. Our research uses a modeling approach to illustrate the complexity of the causes of breast cancer, first, to highlight the many different types of interacting influences that come into play, and, second, to estimate mathematically the impact of changes in various key factors that might be the target of prevention programs. In the first phase of this research we developed a model of postmenopausal breast cancer, the most common variety. Now in Phase II we plan to extend this model to include up-to-date evidence from new studies, to include premenopausal as well as postmenopausal breast cancer and to try to estimate the impact of some factors, mainly environmental chemicals, where data is lacking from human studies, but where animal experiments may be enlightening. We plan to disseminate this information, not only in scientific presentations and publications but also through the media and a website
 
 version that is accessible and understandable to the lay public.
 
 
 
 
 
 
 
 The question(s) or central hypotheses of the research:
 
 This research does not attempt to answer one specific question. Rather it seeks to illustrate breast cancer causation in general as a complex ecologic system with multiple factors influencing breast cancer occurrence at different levels of activity from the genetic and biologic to the social and physical environment. We have previously developed a new model to demonstrate this perspective, which has been published in the peerreviewed scientific literature. Simultaneously we have worked with graphic designers to create web-based visual representation of this model that can be used by the lay public and other interested parties.
 
 
 
 
 
 In the current project we propose to extend this work in three ways: First, we will develop a more systematic and transparent approach to reviewing the existing evidence and review the literature for the most up-to-date information to include. Second, we will modify the model to include premenopausal breast cancer that has some different risk factors than postmenopausal cancer. Third, and finally, we will seek to include evidence from animal experiments that in many cases provide evidence unavailable from human studies. The combination of human epidemiologic and animal experimental data is especially innovative and a novel approach to using all the science available to explain breast cancer causation and suggest avenues for prevention.
 
 
 
 
 
 
 
 The general methodology:
 
 Our approach is to use a team of experts in multiple subject areas to create two types of new models. The disciplines represented by the experts we have assembled include breast cancer epidemiology, human and animal toxicology, environmental health, health evaluation and intervention research, health policy, advocacy, risk assessment and modeling expertise. We will meet with this team six times over two years to review both the human and animal literature, discuss problems and decide on solutions and work to produce both a new large Conceptual Model and a smaller but still substantial Mathematical Model to show the effect of prevention
 
 measures at the population level.
 
 
 
 
 
 
 
 Innovative elements of the project:
 
 Our project is innovative in modeling breast cancer etiology as a complex system, in taking a transdisciplinary approach that includes the knowledge and judgment from a wide range of scientists and in, for the first time, including both human epidemiologic and animal experimental data in the model development.