BACKGROUND The Gail model is widely used for the assessment of risk of invasive breast cancer based on recognized clinical risk factors. In recent years, a substantial number of single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified. However, it remains unclear how to effectively integrate clinical and genetic risk factors for risk assessment. METHODS S...

This paper examines the role of habit persistence in consumption in explaining persistent responses of inflation and output to money growth shocks. A monetary stochastic dynamic general equilibrium (DGE) model with a money-in-the-utility-function (MIU-) setup is augmented by habit formation in consumption and evaluated for both Taylor and Calvo price staggering. It is shown that in the benchmar...

INTRODUCTION Accurate individualised breast cancer risk assessment is essential to provide risk-benefit analysis prior to initiating interventions designed to lower breast cancer risk. Several mathematical models for the estimation of individual breast cancer risk have been proposed. However, no single model integrates family history, hormonal factors, and benign breast disease in a comprehensi...

Risk prediction algorithms are an important tool for identifying individuals at high risk of developing the disease who can then be offered individually tailored clinical management. Several algorithms that predict the probability of breast cancer incidence are currently used in clinical practice. It is uncertain, though, as to which of the breast cancer risk prediction models performs best for...

BACKGROUND Women and their clinicians are increasingly encouraged to use risk estimates derived from statistical models, primarily that of Gail et al., to aid decision making regarding potential prevention options for breast cancer, including chemoprevention with tamoxifen. METHODS We evaluated both the goodness of fit of the Gail et al. model 2 that predicts the risk of developing invasive b...

A multivariate model to assess breast cancer risk was developed by Gail et aL (M. H. Gail, 1. A. Brinton, D. B. Byar, D. K. Corle, S. B. Green, C. Schairer, and J. J. Mulvihill, J. NatI. Cancer Inst., 81: 1879-1886, 1989) based on data analysis of the Breast Cancer Detection and Demonstration Project. We evaluated the model’s usefulness for assigning women to risk groups for counseling and foll...