© 2005 Oxford University Press
COMMENTARY |
Cancer Risk Prediction Models: A Workshop on Development, Evaluation, and Application
Affiliations of authors: Division of Cancer Control and Population Sciences (ANF, DS, RB-B) and Division of Cancer Epidemiology and Genetics (MHG, PH, RMP), National Cancer Institute, Bethesda, MD; Department of Epidemiology, Harvard School of Public Health, Boston, MA (GAC)
Correspondence to: Andrew N. Freedman, PhD, National Cancer Institute, National Institutes of Health, EPN 4005 MSC 7344, 6130 Executive Blvd., Bethesda, MD 20892–7344 (e-mail: Andrew_Freedman{at}nih.gov).
Cancer researchers, clinicians, and the public are increasingly interested in statistical models designed to predict the occurrence of cancer. As the number and sophistication of cancer risk prediction models have grown, so too has interest in ensuring that they are appropriately applied, correctly developed, and rigorously evaluated. On May 20–21, 2004, the National Cancer Institute sponsored a workshop in which experts identified strengths and limitations of cancer and genetic susceptibility prediction models that were currently in use and under development and explored methodologic issues related to their development, evaluation, and validation. Participants also identified research priorities and resources in the areas of 1) revising existing breast cancer risk assessment models and developing new models, 2) encouraging the development of new risk models, 3) obtaining data to develop more accurate risk models, 4) supporting validation mechanisms and resources, 5) strengthening model development efforts and encouraging coordination, and 6) promoting effective cancer risk communication and decision-making.
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