利用遗传和非遗传风险评估工具对英国生物库 246142 名女性进行乳腺癌风险分层。
Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank.
机构信息
Laboratory of Women's Health and Genetics, Genome Institute of Singapore, A∗STAR Research Entities, Singapore; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore.
出版信息
Genet Med. 2023 Oct;25(10):100917. doi: 10.1016/j.gim.2023.100917. Epub 2023 Jun 16.
PURPOSE
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.
METHODS
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.
RESULTS
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 (Gail > 0.5%: 47%, PRS 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 (AUC [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool increased discriminatory ability.
CONCLUSION
Risk-based BC screening may require a multipronged approach that includes PRS, predisposition genes, FH, and other recognized risk factors.
目的
尽管基于风险的筛查采用了个性化方法，但使用个体风险预测工具来识别乳腺癌（BC）筛查的高危个体的益处仍不确定。
方法
我们研究了在英国生物库中招募的 246142 名女性中预测的高危个体之间的重叠。评估的风险预测因子包括 Gail 模型（Gail）、BC 家族史（FH，二进制）、BC 多基因风险评分（PRS）和 BC 易感性基因中的功能丧失（LoF）变体的存在。使用 Youden J 指数选择定义高危的最佳阈值。
结果
总共有 147399 人被认为在未来 2 年内至少有 4 种风险预测工具中的 1 种存在发生 BC 的高风险（Gail > 0.5%：47%，PRS r > 0.7%：30%，FH：6%，和 LoF：1%）；92851 人（38%）仅被 1 种风险预测器标记。由于遗传（PRS）和 Gail 模型风险因素而被标记为高风险的个体之间存在 30%的重叠。表现最佳的组合模型包括由 PRS、FH 和 LoF 识别的高风险女性的并集（AUC [95%CI]：62.2 [60.8 至 63.6]）。为每个风险预测工具分配个体权重可提高判别能力。
结论
基于风险的 BC 筛查可能需要一种多管齐下的方法，包括 PRS、易感性基因、FH 和其他公认的风险因素。
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