Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank

生命银行 风险评估 乳腺癌 基因检测 医学 弗雷明翰风险评分 家族史 遗传倾向 危险分层 人口学 肿瘤科 癌症 内科学 遗传学 生物 计算机科学 疾病 计算机安全 社会学
作者
Peh Joo Ho,Elaine Lim,Mikael Hartman,Fuh Yong Wong,Jingmei Li
出处
期刊:Genetics in Medicine [Elsevier BV]
卷期号:25 (10): 100917-100917 被引量:5
标识
DOI:10.1016/j.gim.2023.100917
摘要

The benefit of using individual risk prediction tools to identify high-risk individuals for breast cancer (BC) screening is uncertain, despite the personalized approach of risk-based screening.We studied the overlap of predicted high-risk individuals among 246,142 women enrolled in the UK Biobank. Risk predictors assessed include the Gail model (Gail), BC family history (FH, binary), BC polygenic risk score (PRS), and presence of loss-of-function (LoF) variants in BC predisposition genes. Youden J-index was used to select optimal thresholds for defining high-risk.In total, 147,399 were considered at high risk for developing BC within the next 2 years by at least 1 of the 4 risk prediction tools examined (Gail2-year > 0.5%: 47%, PRS2-yea r > 0.7%: 30%, FH: 6%, and LoF: 1%); 92,851 (38%) were flagged by only 1 risk predictor. The overlap between individuals flagged as high-risk because of genetic (PRS) and Gail model risk factors was 30%. The best-performing combinatorial model comprises a union of high-risk women identified by PRS, FH, and, LoF (AUC2-year [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool increased discriminatory ability.Risk-based BC screening may require a multipronged approach that includes PRS, predisposition genes, FH, and other recognized risk factors.
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