IN THIS ISSUE
Abstract
A New Model for Improved Breast Cancer Risk Estimation The Gail model is commonly used to estimate breast cancer risk in women based on individual clinical risk factors. Adding genetic information from a panel of single-nucleotide polymorphisms (SNPs) associated with breast cancer risk may improve the risk estimation, but this has not been validated in a cohort. Mealiffe et al. (p. 1618) tested the clinical validity of a risk estimation model by combining an individualâs SNP risk with Gail risk in a nested caseâcontrol cohort of non-Hispanic white women within the Womenâs Health Initiative Clinical Trial. The results showed that risk estimation was modestly improved in postmenopausal women in this cohort. Furthermore, the authors used net reclassification improvement (NRI), a relatively new statistic that measures changes in risk classification, to show a larger improvement in classification in a subset of women at intermediate Gail risk. In an editorial, Cook and Paynter (p. 1605) discuss the contribution of the current article in establishing the clinical utility of genetic information in breast cancer risk prediction and point out some remaining issues and questions concerning the methodology. estimated age-dependent, lifetime, radiationinduced cancer risks after adult radiation exposure. The model reproduced the