Albright Frederick S, Kohlmann Wendy, Neumayer Leigh, Buys Saundra S, Matsen Cindy B, Kaphingst Kimberly A, Cannon-Albright Lisa A
Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City, UT, USA.
Huntsman Cancer Institute, University of Utah Health Sciences Center, 391 Chipeta Way, Suite D, Salt Lake City, UT, 84108, USA.
Cancer Causes Control. 2019 Jun;30(6):581-590. doi: 10.1007/s10552-019-01171-5. Epub 2019 Apr 27.
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.
利用一个将族谱与数十年癌症数据相联系的大型资源库，采用一种非传统方法，基于延伸至一级表亲的特定家族史来估计个体患乳腺癌（BC）的风险，从而更清晰地了解受影响亲属的近亲与远亲组合的各个方面所起的作用。
针对一组具有代表性的乳腺癌家族史情况，在640366名女性中估计BC的相对风险（RRs），这些情况包括一级亲属（FDR）、二级亲属（SDR）和三级亲属（TDR）的数量、母系和父系亲属以及亲属中最早诊断的年龄。
BC病例的一级亲属的RRs范围为1.61（=1名受影响的FDR，CI 1.56，1.67）至5.00（≥4名受影响的FDR，CI 3.35，7.18）。在先证者的二级亲属中，FDR无受影响者的RRs范围为1.04（=1名受影响的SDR，CI 1.00，1.08）至1.71（≥4名受影响的SDR，CI 1.26，2.27）；在先证者有1名FDR的二级亲属中，RRs范围为1.54（0名受影响的SDR，CI 1.47，1.61）至4.78（≥5名受影响的SDR；CI 2.47，8.35）。对于没有更近亲属受影响的三级亲属，在先证者有≥5名受影响的TDR时，RRs显著高于总体风险（RR = 1.32，CI 1.11，1.57）。
犹他州资源库中的大多数女性在FDR至TDR中有BC的阳性家族史。任何数量的受影响FDR或SDR的存在都会使BC风险显著高于总体风险；超过四名TDR，即使没有受影响的FDR或SDR，也会使风险显著高于总体风险。从受影响亲属的特定和扩展家族史情况得出的风险预测能够识别出即使没有传统定义的高风险家族但风险增加的女性；这些风险可能是用于个体化癌症筛查和预防的有力、有效的工具。
