Engel Christoph, Fischer Christine
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Germany.
Institute of Human Genetics, University of Heidelberg, Germany.
Breast Care (Basel). 2015 Feb;10(1):7-12. doi: 10.1159/000376600.
BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.
BRCA1/2基因的突变携带者患乳腺癌和卵巢癌的风险显著增加。对携带者及其他高危个体进行个性化临床管理,依赖于对癌症风险的精确了解。在本报告中,我们概述了目前有关经验性癌症风险的文献,并描述了当前在临床实践中用于个体风险评估的风险预测模型。不同研究之间的癌症风险差异很大。BRCA1突变携带者患乳腺癌的风险为40%-87%,BRCA2突变携带者为18%-88%。对于卵巢癌,BRCA1的风险估计在22%-65%之间,BRCA2为10%-35%。对侧乳腺癌的风险很高(首次患癌后10年风险,BRCA1为27%,BRCA2为19%)。人们提出了风险预测模型,利用家族史、主要基因的遗传模式以及其他遗传和非遗传风险因素等更多知识,提供更个性化的风险预测。已经开发出用户友好的软件工具,作为家庭咨询单位决策的依据。总之,需要进一步评估癌症风险并进行模型验证,理想情况下基于前瞻性队列研究。为了获得此类数据,对携带者及其他高危个体的临床管理应始终伴有标准化的科学记录。