Re: Discriminatory accuracy from single-nucleotide polymorphisms in models to predict breast cancer risk.

摘要

The advent of genome-wide association studies to identify low-penetrance common susceptibility alleles heralds the possibility of incorporating panels of gene variants into existing risk prediction models and of assessing improvement in model performance. However, to date, the updated models have shown only modest improvements in discrimination. Gail had previously shown that adding seven single-nucleotide polymorphisms (SNPs) identified from genome-wide association analyses to the original Breast Cancer Risk Assessment Tool had yielded only a modest improvement in area under the curve (AUC) from 0.607 to 0.632. Gail now reports that inclusion of 11 SNPs exhibits an even smaller improvement in the AUC (0.637) than that of the BRACTplus 7 model.