Risk models used to counsel women for breast and ovarian cancer: a guide for clinicians.

摘要: Advances in the identification and treatment of breast ovarian cancer have lead to a need for reliable estimates susceptibility risk associated with these two cancers. These may be used clinical settings identify individuals at increased developing disease or being carrier allele. Accurate assessment probabilities is important given potential implications medical decision-making including patients who might benefit from preventive measures, genetic counseling entry into trials. A wide range empirical statistical models has been proposed, particularly prediction, those that utilize logistic regression Bayesian modeling. The specific data create various also varies include molecular, epidemiologic, information. This overview presents definitions oncology as well several more frequently methods estimation cancer. In addition, means by which different are able provide measure error uncertainty estimate will discussed.