Polygenic Breast Cancer Risk for Women Veterans in the Million Veteran Program.

IF 5.6 2区 医学 Q1 ONCOLOGY JCO precision oncology Pub Date : 2021-07-21 eCollection Date: 2021-07-01 DOI:10.1200/PO.20.00541
Jessica Minnier, Nallakkandi Rajeevan, Lina Gao, Byung Park, Saiju Pyarajan, Paul Spellman, Sally G Haskell, Cynthia A Brandt, Shiuh-Wen Luoh
{"title":"Polygenic Breast Cancer Risk for Women Veterans in the Million Veteran Program.","authors":"Jessica Minnier,&nbsp;Nallakkandi Rajeevan,&nbsp;Lina Gao,&nbsp;Byung Park,&nbsp;Saiju Pyarajan,&nbsp;Paul Spellman,&nbsp;Sally G Haskell,&nbsp;Cynthia A Brandt,&nbsp;Shiuh-Wen Luoh","doi":"10.1200/PO.20.00541","DOIUrl":null,"url":null,"abstract":"<p><p>Accurate breast cancer (BC) risk assessment allows personalized screening and prevention. Prospective validation of prediction models is required before clinical application. Here, we evaluate clinical- and genetic-based BC prediction models in a prospective cohort of women from the Million Veteran Program.</p><p><strong>Materials and methods: </strong>Clinical BC risk prediction models were validated in combination with a genetic polygenic risk score of 313 (PRS313) single-nucleotide polymorphisms in genetic females without prior BC diagnosis (n = 35,130, mean age 49 years) with 30% non-Hispanic African ancestry (AA). Clinical risk models tested were Breast and Prostate Cancer Cohort Consortium, literature review, and Breast Cancer Risk Assessment Tool, and implemented with or without PRS313. Prediction accuracy and association with incident breast cancer was evaluated with area under the receiver operating characteristic curve (AUC), hazard ratios, and proportion with high absolute lifetime risk.</p><p><strong>Results: </strong>Three hundred thirty-eight participants developed incident breast cancers with a median follow-up of 3.9 years (2.5 cases/1,000 person-years), with 196 incident cases in women of European ancestry and 112 incident cases in AA women. Individualized Coherent Absolute Risk Estimator-literature review in combination with PRS313 had an AUC of 0.708 (95% CI, 0.659 to 0.758) in women with European or non-African ancestries and 0.625 (0.539 to 0.711) in AA women. Breast Cancer Risk Assessment Tool with PRS313 had an AUC of 0.695 (0.62 to 0.729) in European or non-AA and 0.675 (0.626 to 0.723) in AA women. Incorporation of PRS313 with clinical models improved prediction in European but not in AA women. Models estimated up to 9% of European and 18% of AA women with absolute lifetime risk > 20%.</p><p><strong>Conclusion: </strong>Clinical and genetic BC risk models predict incident BC in a large prospective multiracial cohort; however, more work is needed to improve genetic risk estimation in AA women.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":" ","pages":""},"PeriodicalIF":5.6000,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345920/pdf/po-5-po.20.00541.pdf","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JCO precision oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1200/PO.20.00541","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/7/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 3

Abstract

Accurate breast cancer (BC) risk assessment allows personalized screening and prevention. Prospective validation of prediction models is required before clinical application. Here, we evaluate clinical- and genetic-based BC prediction models in a prospective cohort of women from the Million Veteran Program.

Materials and methods: Clinical BC risk prediction models were validated in combination with a genetic polygenic risk score of 313 (PRS313) single-nucleotide polymorphisms in genetic females without prior BC diagnosis (n = 35,130, mean age 49 years) with 30% non-Hispanic African ancestry (AA). Clinical risk models tested were Breast and Prostate Cancer Cohort Consortium, literature review, and Breast Cancer Risk Assessment Tool, and implemented with or without PRS313. Prediction accuracy and association with incident breast cancer was evaluated with area under the receiver operating characteristic curve (AUC), hazard ratios, and proportion with high absolute lifetime risk.

Results: Three hundred thirty-eight participants developed incident breast cancers with a median follow-up of 3.9 years (2.5 cases/1,000 person-years), with 196 incident cases in women of European ancestry and 112 incident cases in AA women. Individualized Coherent Absolute Risk Estimator-literature review in combination with PRS313 had an AUC of 0.708 (95% CI, 0.659 to 0.758) in women with European or non-African ancestries and 0.625 (0.539 to 0.711) in AA women. Breast Cancer Risk Assessment Tool with PRS313 had an AUC of 0.695 (0.62 to 0.729) in European or non-AA and 0.675 (0.626 to 0.723) in AA women. Incorporation of PRS313 with clinical models improved prediction in European but not in AA women. Models estimated up to 9% of European and 18% of AA women with absolute lifetime risk > 20%.

Conclusion: Clinical and genetic BC risk models predict incident BC in a large prospective multiracial cohort; however, more work is needed to improve genetic risk estimation in AA women.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
百万退伍军人计划中女性退伍军人的多基因乳腺癌风险。
准确的乳腺癌(BC)风险评估允许个性化筛查和预防。在临床应用前需要对预测模型进行前瞻性验证。在这里,我们评估了来自百万退伍军人计划的女性前瞻性队列中基于临床和遗传学的BC预测模型。材料和方法:临床BC风险预测模型结合遗传多基因风险评分313 (PRS313)单核苷酸多态性,验证无BC诊断的遗传女性(n = 35130,平均年龄49岁)30%非西班牙裔非洲血统(AA)的临床BC风险预测模型。测试的临床风险模型包括乳腺癌和前列腺癌队列联盟、文献综述和乳腺癌风险评估工具,并在有或没有PRS313的情况下实施。通过受试者工作特征曲线下面积(AUC)、风险比和高绝对终生风险比例来评估预测准确性和与乳腺癌发病率的相关性。结果:338名参与者发生了乳腺癌,中位随访时间为3.9年(2.5例/ 1000人年),其中欧洲血统女性196例,AA女性112例。个体化连贯绝对风险估计值-文献综述结合PRS313,欧洲或非非洲血统女性的AUC为0.708 (95% CI, 0.659至0.758),AA女性的AUC为0.625(0.539至0.711)。使用PRS313的乳腺癌风险评估工具,欧洲或非AA女性的AUC为0.695(0.62至0.729),AA女性的AUC为0.675(0.626至0.723)。将PRS313纳入临床模型改善了欧洲女性的预测,但在AA女性中没有改善。模型估计高达9%的欧洲女性和18%的AA女性的绝对终生风险大于20%。结论:临床和遗传BC风险模型可预测大型前瞻性多种族队列中的BC事件;然而,需要做更多的工作来改善AA女性的遗传风险评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
9.10
自引率
4.30%
发文量
363
期刊最新文献
Tale of Two Tumors: Drug Development in Urothelial and Germ Cell Cancers. Modeling Individual-Level Uncertainty From Missing Data in Multifactorial Breast Cancer Risk Prediction. Prognostic Significance of Isolated Tumor Cells and the Role of Immunohistochemistry in Nodal Evaluation in Breast Cancer: A SEER-Based Analysis and Reappraisal. Exceptional Response to Durvalumab and Tremelimumab in Pancreatic Acinar Cell Carcinoma With Ultramutated Phenotype Associated With a DNA Polymerase-ε Mutation. Multi-Institutional Study Evaluating the Role of Early Circulating Tumor DNA Dynamics During Treatment With Immune Checkpoint Inhibitors in Patients With Advanced-Stage Melanoma.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1