Cancer risk prediction models: A workshop on development, evaluation, and application

Andrew N. Freedman, Daniela Seminara, Mitchell H. Gail, Patricia Hartge, Graham A. Colditz, Rachel Ballard-Barbash, Ruth M. Pfeiffer

Research output: Contribution to journalArticlepeer-review

196 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)715-723
Number of pages9
JournalJournal of the National Cancer Institute
Volume97
Issue number10
DOIs
StatePublished - May 18 2005

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