Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information

Abstract

BackgroundThe 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.MethodsSeven SNPs associated with breast cancer risk were selected from the literature and genotyped in white non-Hispanic women in a nested case-control cohort of 1664 case patients and 1636 control subjects within the Women's Health Initiative Clinical Trial. SNP risk scores were computed based on previously published odds ratios assuming a multiplicative model. Combined risk scores were calculated by multiplying Gail risk estimates by the SNP risk scores. The independence of Gail risk and SNP risk was evaluated by logistic regression. Calibration of relative risks was evaluated using the Hosmer-Lemeshow test. The performance of the combined risk scores was evaluated using receiver operating characteristic curves. The net reclassification improvement (NRI) was used to assess improvement in classification of women into low (<1.5%), intermediate (1.5%-2%), and high (>2%) categories of 5-year risk. All tests of statistical significance were two-sided.ResultsThe SNP risk score was nearly independent of Gail risk. There was good agreement between predicted and observed SNP relative risks. In the analysis for receiver operating characteristic curves, the combined risk score was more discriminating, with area under the curve of 0.594 compared with area under the curve of 0.557 for Gail risk alone (P