Population-based relative risks for specific family history constellations of breast cancer.

Research paper by Frederick S FS Albright, Wendy W Kohlmann, Leigh L Neumayer, Saundra S SS Buys, Cindy B CB Matsen, Kimberly A KA Kaphingst, Lisa A LA Cannon-Albright

Indexed on: 06 Sep '19Published on: 29 Apr '19Published in: Cancer Causes & Control


Using a large resource linking genealogy with decades of cancer data, a non-traditional approach was used to estimate individualized risk for breast cancer (BC) based on specific family history extending to first cousins, providing a clearer picture of the contribution of various aspects of both close and distant combinations of affected relatives. RRs for BC were estimated in 640,366 females for a representative set of breast cancer family history constellations that included number of first- (FDR), second-(SDR), and third-degree relatives (TDR), maternal and paternal relatives, and age at earliest diagnosis in a relative. RRs for first-degree relatives of BC cases ranged from 1.61 (= 1 FDR affected, CI 1.56, 1.67) to 5.00 (≥ 4 FDRs affected, CI 3.35, 7.18). RRs for second-degree relatives of probands with 0 affected FDRs ranged from 1.04 (= 1 SDR affected, CI 1.00, 1.08) to 1.71 (≥ 4 SDRs affected, CI 1.26, 2.27) and for second-degree relatives of probands with exactly 1 FDR from 1.54 (0 SDRs affected, CI 1.47, 1.61) to 4.78 (≥ 5 SDRs; CI 2.47, 8.35). RRs for third-degree relatives with no closer relatives affected were significantly elevated over population risk for probands with ≥ 5 affected TDRs RR = 1.32, CI 1.11, 1.57). The majority of females in the Utah resource had a positive family history of BC in FDRs to TDRs. Presence of any number of affected FDRs or SDRs significantly increased risk for BC over population risk; and more than four TDRs, even with no affected FDRs or SDRs, significantly increased risk over population risk. Risk prediction derived from the specific and extended family history constellation of affected relatives allows identification of females at increased risk even when they do not have a conventionally defined high-risk family; these risks could be a powerful, efficient tool to individualize cancer screening and prevention.