Decision Support Tools to Guide Cancer Control Planning for Prostate Cancer

Wednesday, May 14, 2008
12:00-1:00 p.m. EST

The National Cancer Institute’s (NCI) Office of Advocacy Relations hosted a Webinar focused on decision support tools aimed at guiding the implementation of cancer control interventions (i.e., screening and treatment) to optimally balance benefit and cost.

The advent of prostate-specific antigen (PSA) testing has produced a host of pressing questions in prostate cancer control. These questions relate not only to PSA screening but also to treatment of tumors detected during the PSA era. The value of PSA testing remains one of the most elusive questions facing older men and their physicians. Although prostate cancer death rates have declined by more than one third since the early 1990s, advances in treatment, shifting patterns of care, and changing public behavior may also have contributed to this decline. Ongoing screening trials should yield results in coming years; however, even if PSA screening is ultimately shown to reduce the risk of prostate cancer death, the question of how best to screen in order to balance cost and benefit remains unanswered. PSA screening is clearly associated with overdiagnosis, and strategies to avoid overtreatment while maximizing benefit must be devised. Given the imperfect and rapidly changing state of knowledge, modeling studies can provide insights into the potential benefits and costs of PSA screening and help design optimal intervention policies.

The models presented in the webinar are a product of NCI’s Cancer Intervention and Surveillance Modeling Network (CISNET), which is a consortium focused on modeling to improve our understanding of the impact of cancer control interventions (e.g., prevention, screening, and treatment) on population trends in incidence and mortality. These models have been developed to explain recent disease trends but may also be used to project future trends and to help determine optimal cancer control strategies.

The CISNET prostate program consists of three investigator groups who have developed models of prostate cancer progression, detection, and prognosis and have validated their models against US population trends. These groups are now ready to apply their models to address pressing policy issues in prostate cancer control and are enthusiastic about working with health policy planners towards this goal.

For the first half of the webinar, presenters gave an overview of the CISNET prostate program. They summarized the central concepts of each of the models and gave examples of the types of policy questions that they could potentially address. They also reviewed the major quandaries in prostate cancer control faced by clinicians today, and explained why available data do not adequately address these issues. In the second half of the call, callers were invited to ask questions about how these tools might be applied to issues of specific interest (e.g., cancer control planning, cost-effective screening strategies, use of preventive interventions, decisions about treatment). Interested callers were invited to follow up with the CISNET consortium members to outline possible collaborations. In most cases, some funds will be required to facilitate these collaborations.

Recording of the Webinar


Eric J. (Rocky) Feuer, PhD
Chief, Statistical Methodology and Applications Branch
CISNET Program Director
Surveillance Research Program
Division of Cancer Control and Population Sciences
National Cancer Institute
Overview of the CISNET Consortium

Ruth Etzioni, PhD
Translation and Outcomes Research
Fred Hutchinson Cancer Research Center
Seattle, Washington
The CISNET Prostate Program: Key Concepts and Potential Policy Applications

David Penson, MD
Associate Professor
Department of Urology
University of Southern California
Prostate Cancer Clinical Quandaries: A Need for Models


Alex Tsodikov, PhD, Department of Biostatistics, University of Michigan; and Harry de Koning, MD and Gerrit Draisma, PhD, Department of Public Health, Erasmus Medical Center, from the CISNET Prostate Cancer Modeling efforts, will also be available to answer questions.