Highlights of This Issue

Abstract

The impact of screening mammography on breast cancer incidence is difficult to disentangle from cohort- and age-related effects. Gangnon and colleagues developed an age–period–cohort model of ductal carcinoma in situ (DCIS) and invasive breast cancer incidence in U.S. females using cancer registry data. Incidence with and without the mammography period effect was calculated. The authors report that mammography contributes to markedly elevated rates of DCIS and early-stage invasive cancers, but also contributes to substantial reductions in the incidence of metastatic breast cancer. While mammography is an important tool for reducing breast cancer burden, the challenge is to distinguish between indolent and potentially lethal early-stage breast cancers via mammography.Breast density assessment improves 5-year breast cancer risk prediction, but the value of sequential breast density measures is unknown. Kerlikowske and colleagues determined if two breast density measures improve the predictive accuracy, compared to one measure. The two-measure model had greater discriminatory accuracy than the one-measure model. Also, the two-measure model improves risk classification for women with a decrease in breast density.In observational studies, aspirin use has been associated with significant reductions in breast cancer mortality; however, it is unclear whether initiating aspirin use after diagnosis is associated with similar reductions in mortality. Barron and colleagues studied associations between de-novo post-diagnostic aspirin use and all-cause, breast cancer–specific mortality. The authors found no association between de-novo aspirin use and breast cancer–specific mortality. Similar null associations were found in women initiating aspirin use after breast cancer diagnosis.Recent studies have identified several putative low-penetrance susceptibility loci for melanoma. Using data from the population-based Genes, Environment, and Melanoma (GEM) Study, Gibbs and colleagues sought to determine the genetic predisposition for multiple primary melanoma. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) were associated with multiple primary melanoma. The authors also identified several SNPs that are significantly associated with multiple primary melanoma. The GEM Study provides additional evidence for the relevance of these genetic regions to melanoma risk.