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Mathematical modeling for breast cancer risk assessment. State of the art and role in medicine.

作者信息

Rubinstein Wendy S, O'Neill Suzanne M, Peters June A, Rittmeyer Laura J, Stadler Mona P

机构信息

Center for Medical Genetics, Evanston Northwestern Healthcare, Illinois 60201, USA.

出版信息

Oncology (Williston Park). 2002 Aug;16(8):1082-94; discussion 1094, 1097-9.

PMID:12201647
Abstract

Women at increased risk of breast cancer have important opportunities for early detection and prevention. There are, however, serious drawbacks to the available interventions. The magnitude of breast cancer risk is a crucial factor in the optimization of medical benefit when considering the efficacy of risk-reduction methods, the adverse effects of intervention, and economic and quality-of-life outcomes. Breast cancer risk assessment has become increasingly quantitative and is amenable to computerization. The assembly of risk factor information into practical, quantitative models for clinical and scientific use is relatively advanced for breast cancer, and represents a paradigm for broader risk management in medicine. Using a case-based approach, we will summarize the major breast cancer risk assessment models, compare and contrast their utility, and illustrate the role of genetic testing in risk management. Important considerations relevant to clinical oncology practice include the role of risk assessment in cancer prevention, the logistics of implementing risk assessment, the ramifications of conveying risk information with limited genetic counseling, and the mechanisms for genetics referral. Medical professionals can embrace new preventive medicine techniques more effectively by utilizing quantitative methods to assess their patients' risks.

摘要

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